An aggregation analysis method and device for distributed energy storage in a substation participating in secondary frequency regulation services

Abstract

A method and device for aggregate analysis of distributed energy storage participating in secondary frequency regulation services in a substation area. The method obtains substation load data through a neural network; constructs an optimized operation model of a distributed ESS in a substation area to obtain the day-ahead optimization result of the output behavior of the distributed ESS in the substation area under the condition of meeting user needs; constructs a DSAP bidding strategy model to obtain the optimal bidding capacity of DSAP in each period and the secondary frequency regulation capacity contribution of each substation area; formulates a step-by-step quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market; constructs a clearing model of the day-ahead secondary frequency regulation market to obtain the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market; formulates a DSAP intraday secondary frequency regulation response optimization strategy to optimize the frequency regulation capacity allocation adjustment, frequency regulation response output regulation and frequency regulation revenue respectively. The present invention provides a solution for DSAP to obtain the optimal bidding target, and improves the real-time frequency regulation effect of DSAP.

Description

Technical Field

[0001] The present invention belongs to the technical field of secondary frequency regulation of electric power systems, and in particular relates to an aggregation analysis method and device for distributed energy storage in an area participating in secondary frequency regulation services. Background Art

[0002] In order to cope with a series of problems such as energy crisis and greenhouse effect caused by the massive consumption of fossil energy, it has become a consensus to vigorously develop clean renewable energy and take a sustainable development path. By the end of December 2023, the total installed capacity of power generation in China will be about 2.92 billion kW, with wind power and photovoltaic (PV) installed capacity reaching 440 million kW and 610 million kW respectively. Among them, the cumulative grid-connected capacity of distributed PV is 254 million kW, and the newly added capacity in 2023 is 96 million kW. Distributed new energy will show a rapid development trend in the future.

[0003] However, with the explosive growth of distributed renewable energy in the distribution network, new challenges have been brought to the normal operation and control of the distribution network. On the one hand, problems such as power fluctuations in distribution network lines, reverse overload of distribution transformers, and voltage over-limit have seriously restricted the effective integration and efficient utilization of renewable energy; on the other hand, the high degree of power electronics in the new power system has made the power system show more and more obvious low inertia characteristics, and the traditional frequency regulation resources on the power generation side have gradually become scarce, and it is urgent to further explore reliable frequency regulation resources from the distribution side. Energy Storage System (ESS) is considered to be one of the key supporting technologies for adapting to the large-scale access of renewable energy and building a highly reliable energy supply system in the new power system due to its high flexibility in operation and regulation. In particular, distributed ESS has been widely used and developed due to its flexible advantages in installation and operation.

[0004] With policy support, Shandong, Henan, Shenzhen and other places in my country have successively carried out a number of distributed ESS pilot projects in substations: Shandong, Henan and other places have piloted the construction of substation ESS to cope with the pressure of insufficient new energy absorption capacity of distribution networks; in Shenzhen, Shanghai and other places, ESS is an important part of the smart microgrid demonstration project, used to smooth the output of renewable energy, improve the reliability and power supply quality of microgrids. However, at present, the distributed ESS resources in my country are often difficult to meet the minimum entry threshold requirements for ancillary services due to the characteristics of scattered geographical location, small individual installation capacity, multiple operating entities and uncertain output time. This has caused some substation ESS to be idle, and also brought obstacles to the exploration of the regulation potential of distributed ESS. In order to fully explore the flexible characteristics of distributed ESS in substations, an aggregation service provider (Distributed Energy Storage Aggregation Service Provider, DSAP) only for distributed ESS is introduced to build an overall operation architecture of hierarchical management, flexibly aggregate the capacity of distributed ESS in substations and manage it on a large scale, and DSAP acts as an agent for distributed ESS in substations to participate in the ancillary service market. How to reasonably motivate distributed ESS in substations to participate in aggregation, optimize the dispatch of ESS output to respond to the needs of the ancillary service market, and obtain economic benefits has become the key to promoting the sustainable development of this framework.

[0005] At present, the research focus of distributed ESS is mainly on the optimization configuration and operation strategy of ESS on the power supply side or distribution network side, so as to promote the consumption of distributed new energy, optimize the load curve, and improve the reliability and economy of the power system. However, the distributed ESS in the substation close to the user end is usually configured with the main goal of ensuring reliable energy supply to the microgrid, building or community users, and its capacity utilization is significantly affected by the output of renewable energy such as PV and the price difference of electricity. In order to better realize the effective utilization of ESS, it is necessary to aggregate and manage the capacity of distributed ESS in the decentralized substation, form a large-scale dispatchable resource, participate in the power auxiliary service market, and fully tap its flexibility and commercial value.

[0006] In addition, distributed resources mainly participate in the market through the aggregation of integrated entities such as load aggregators, virtual power plants, and integrated energy systems. Load aggregators provide a platform for small and medium-sized demand response resources to participate in system operation and control; virtual power plants are an aggregation management system that can realize the coordinated control and multi-energy complementary operation of various types of renewable energy distributed in different regions; integrated energy systems integrate various forms of energy through intelligent control and coordinated operation. The research on the aggregation strategy and market participation mechanism of distributed resources has provided a lot of experience for the aggregation management of distributed ESS in the substation area. Most of the existing research work is based on the physical operation characteristics of various aggregated resources, and there is still a need to supplement the research on the adjustable capacity of response resources. At the same time, the economic benefits of aggregators are a necessary condition for maintaining their active organization of distributed resources to participate in the power market. Combined with the objective aggregation conditions and market operation mechanism of distributed ESS in the substation area, there is currently a lack of research on the aggregation of distributed ESS in the substation area to participate in the secondary frequency regulation auxiliary service market. The existing distributed resource aggregation strategies are mostly based on the physical operation characteristics of various aggregated resources, and there is still a need to supplement the research on the adjustable capacity of response resources. At the same time, the research on the secondary frequency regulation response dispatch strategy of distributed ESS in the substation area is also incomplete.

[0007] Therefore, with the continuous advancement of my country's power market reform and ESS market-oriented operation, it is necessary to study the participation of distributed ESS in the auxiliary service market. Formulating the day-ahead bidding and real-time regulation strategy for the participation of distributed ESS in the secondary frequency regulation auxiliary service market, giving full play to its flexible regulation ability, and tapping its economic value will help promote the further development and application of distributed ESS in the substation. Summary of the invention

[0008] To this end, the present invention provides an aggregation analysis method and device for the participation of distributed energy storage in the secondary frequency regulation service in the substation area. By proposing a method for calculating the dispatchable capacity of the distributed ESS in the substation area, the utilization rate of energy storage resources is improved; by proposing a bidding strategy for DSAP to participate in the day-ahead secondary frequency regulation auxiliary service market, a solution is provided for DSAP to obtain the optimal bidding target; by proposing a rolling optimization allocation model for the secondary frequency regulation capacity of the distributed ESS in the substation area within the day, it is beneficial to improve the real-time frequency regulation effect of DSAP.

[0009] In order to achieve the above-mentioned purpose, the present invention provides the following technical solution: an aggregation analysis method for distributed energy storage in a substation participating in secondary frequency regulation service, comprising:

[0010] The user load and photovoltaic output data of the substation are predicted by a neural network to obtain the load data of the substation; a distributed ESS optimization operation model of the substation is constructed, and the obtained load data of the substation is optimized by the distributed ESS optimization operation model of the substation to obtain the day-ahead optimization result of the output behavior of the distributed ESS of the substation under the condition of meeting the user demand;

[0011] Construct a DSAP bidding strategy model, and obtain the optimal bidding capacity of DSAP in each time period and the secondary frequency regulation capacity contribution of each substation through the DSAP bidding strategy model; formulate a tiered quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation and the substation contract declaration price;

[0012] Constructing a clearing model for the day-ahead secondary frequency regulation market, and obtaining the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market through the clearing model of the day-ahead secondary frequency regulation market;

[0013] According to the total amount of DSAP's secondary frequency regulation capacity bids in each time period and the real-time operating status of each distributed ESS in each substation, a DSAP intraday secondary frequency regulation response optimization strategy is formulated; through the DSAP intraday secondary frequency regulation response optimization strategy, the DSAP intraday distributed ESS secondary frequency regulation capacity allocation adjustment, the DSAP intraday distributed ESS secondary frequency regulation response output regulation and the DSAP intraday distributed ESS secondary frequency regulation revenue are optimized respectively.

[0014] As a preferred scheme for the aggregation analysis method of distributed energy storage participating in secondary frequency regulation service in a substation, the objective function expression of the distributed ESS optimization operation model in the substation is:

[0015] min C day =C ele +C decay +C loss

[0016]

[0017]

[0018]

[0019]

[0020] In the formula, C day is the daily operation cost of the area, C ele is the daily electricity cost of ESS users in the area, C decay is the daily operating life attenuation cost of the ESS in the substation, C lossis the operating loss cost of the distribution transformer in the substation; t is the load sampling time; T is the operating cycle; P trans (t), Q trans (t) are the active power and reactive power of the distribution transformer at time t; C TOU (t) is the time-of-use electricity price at time t; ξ is the daily operating capacity decay of the ESS in the substation. Usually, when the ESS capacity decays to 80% of the rated capacity, the ESS is considered retired; C E 、E rate , C P , P rate They are ESS capacity unit cost, rated capacity, PCS power unit cost, and energy storage rated power; P loss (t) is the active power loss of the transformer; P K is the transformer short-circuit loss; U N is the rated voltage of the transformer; S N is the rated capacity.

[0021] As a preferred scheme for the aggregation analysis method of distributed energy storage participating in secondary frequency regulation services in a substation area, the objective function expression of the DSAP bidding strategy model is:

[0022]

[0023]

[0024]

[0025] In the formula, R DSAP,DA is the net profit of DSAP under the day-ahead bidding strategy; R FR The secondary frequency regulation compensation fee settled by the secondary frequency regulation market to DSAP; R ESS,n The payment fee for DSAP to each substation for energy storage secondary frequency regulation; N represents the total number of aggregated substations, n = 1, 2, 3…, N; They are the upward and downward adjustment capacities declared by DSAP respectively; The secondary frequency regulation capacity forecast price and frequency regulation mileage forecast price for upward and downward services respectively; They are the historical secondary frequency modulation performance indicators and frequency modulation mileage call rate of DSAP in the upward and downward services respectively; They are the historical performance indicators of the up- and down-regulation of the energy storage in the substation n in response to the DSAP control command, i.e., the accuracy of the distributed ESS in the substation tracking the control command to issue the secondary frequency regulation output target; are the contribution of the upward and downward regulation capacity of the substation n at time t respectively; They respectively represent the expected price of secondary frequency regulation capacity and the expected price of frequency regulation mileage declared by substation n at time t for providing upward and downward services.

[0026] As a preferred scheme for the aggregation analysis method of distributed energy storage participating in secondary frequency regulation services in a substation area, the objective function expression of the clearing model of the day-ahead secondary frequency regulation market is:

[0027]

[0028]

[0029] In the formula, is the total cost of secondary frequency regulation auxiliary service in period t, They are the comprehensive quotation of the mth-order secondary frequency regulation of frequency regulation resource y in period t and the winning capacity of secondary frequency regulation; They are the adjusted capacity quotation, mileage quotation and opportunity cost respectively.

[0030] As a preferred scheme for the aggregation analysis method of distributed energy storage participating in secondary frequency regulation services in a substation, the DSAP intraday secondary frequency regulation response optimization strategy includes constructing a DSAP intraday distributed ESS secondary frequency regulation capacity rolling optimization model, formulating a DSAP intraday distributed ESS secondary frequency regulation response output regulation strategy, and constructing a DSAP intraday distributed ESS secondary frequency regulation auxiliary service revenue settlement model;

[0031] The objective function expression of the DSAP intra-day distributed ESS secondary frequency modulation capacity rolling optimization model is:

[0032]

[0033]

[0034]

[0035] In the formula, They are the net income of DSAP on the operation day, the frequency compensation fee settled by the secondary frequency regulation market to DSAP, and the payment fee contributed by DSAP to the secondary frequency regulation of distributed ESS in each substation; N is the total number of aggregated substations, n = 1, 2, 3…, N; They represent the upward and downward capacity of the DSAP winning bid respectively; They are the secondary frequency regulation capacity clearing price and frequency regulation mileage clearing price for downward regulation services respectively; They are the historical secondary frequency regulation performance indicators of DSAP in the upward service and downward service, respectively. The two indicators are not updated during the rolling process, but the actual secondary frequency regulation performance indicators and mileage call rate of each dispatch period on the operation day are recalculated when calculating the DSAP settlement income; They represent the upward and downward capacity allocation of the substation n at time t respectively;

[0036] The implementation steps of the DSAP intra-day distributed ESS secondary frequency response output control strategy are as follows:

[0037] The real-time operating load rate of the distribution transformer in the set area is calculated through the load rate calculation formula;

[0038] According to the real-time operating load rate of the distribution transformer of the set substation, the operating state of the set substation is judged. If the set substation is in a heavy overload state during the sampling period, the set substation is restricted from responding to the output of the downward adjustment signal; if the set substation is in a reverse heavy overload state during the sampling period, the set substation is restricted from responding to the output of the upward adjustment signal; if the operating state of the set substation is normal during the sampling period, the set substation responds to the downward adjustment signal or the upward adjustment signal output;

[0039] The adjustable capacity of the distributed ESS in the set area is calculated by using an adjustable capacity calculation formula;

[0040] According to the distribution transformer operation state of the set substation and the adjustable capacity of the distributed ESS of the set substation, the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation are obtained; by performing data processing on the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation, the optimal output of the distributed ESS upward adjustment response and the optimal output of the distributed ESS downward adjustment response of the set substation are obtained;

[0041] Updating the real-time operation SOC of the distributed ESS in the set area;

[0042] The actual secondary frequency regulation performance index of the distributed ESS in the set area is calculated by the actual secondary frequency regulation performance index calculation formula; the actual frequency regulation mileage call rate of the distributed ESS in the set area is calculated by the actual frequency regulation mileage call rate calculation formula;

[0043] The DSAP intra-day distributed ESS secondary frequency regulation auxiliary service revenue settlement model is calculated based on the actual frequency regulation mileage call rate of the distributed ESS in the set area and the actual secondary frequency regulation performance index of the distributed ESS in the set area to obtain the secondary frequency regulation service revenue of the distributed ESS in the set area and the secondary frequency regulation service revenue of the DSAP.

[0044] The present invention also provides an aggregation analysis processing device for distributed energy storage in a substation participating in a secondary frequency regulation service, which adopts the above-mentioned aggregation analysis method for distributed energy storage in a substation participating in a secondary frequency regulation service, and comprises:

[0045] The distributed ESS optimization operation model construction and processing module is used to predict the user load and photovoltaic output data of the substation area through a neural network to obtain the load data of the substation area; construct the distributed ESS optimization operation model of the substation area, optimize the obtained load data of the substation area through the distributed ESS optimization operation model of the substation area, and obtain the day-ahead optimization result of the output behavior of the distributed ESS in the substation area under the condition of meeting the user demand;

[0046] DSAP bidding strategy model construction and processing module, used to construct a DSAP bidding strategy model, and obtain the optimal bidding capacity of DSAP in each period and the secondary frequency regulation capacity contribution of each substation through the DSAP bidding strategy model; formulate a tiered quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation and the substation contract declaration price;

[0047] A clearing model construction and processing module for the day-ahead secondary frequency regulation market is used to construct a clearing model for the day-ahead secondary frequency regulation market, and obtain the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market through the clearing model for the day-ahead secondary frequency regulation market;

[0048] The DSAP intraday secondary frequency regulation response optimization strategy formulation and implementation module is used to formulate the DSAP intraday secondary frequency regulation response optimization strategy according to the total amount of DSAP secondary frequency regulation capacity bids in each time period and the real-time operation status of each substation distributed ESS; through the DSAP intraday secondary frequency regulation response optimization strategy, the DSAP intraday substation distributed ESS secondary frequency regulation capacity allocation adjustment, DSAP intraday substation distributed ESS secondary frequency regulation response output regulation and DSAP intraday substation distributed ESS secondary frequency regulation benefits are optimized respectively.

[0049] As a preferred scheme for an aggregation analysis and processing device for participating in secondary frequency regulation services of distributed energy storage in a substation, in the substation distributed ESS optimization operation model construction and processing module, the objective function expression of the substation distributed ESS optimization operation model is:

[0050] min C day =C ele +C decay +C loss

[0051]

[0052]

[0053]

[0054]

[0055] In the formula, C day is the daily operation cost of the area, C ele is the daily electricity cost of ESS users in the area, C decay is the daily operating life attenuation cost of the ESS in the substation, C loss is the operating loss cost of the distribution transformer in the substation; t is the load sampling time; T is the operating cycle; P trans (t), Q trans (t) are the active power and reactive power of the distribution transformer at time t; C TOU (t) is the time-of-use electricity price at time t; ξ is the daily operating capacity decay of the ESS in the substation. Usually, when the ESS capacity decays to 80% of the rated capacity, the ESS is considered retired; C E 、E rate , C P , P rate They are ESS capacity unit cost, rated capacity, PCS power unit cost, and energy storage rated power; P loss (t) is the transformer active power loss; P K is the transformer short-circuit loss; U N is the rated voltage of the transformer; S Nis the rated capacity.

[0056] As a preferred solution for an aggregation analysis and processing device for distributed energy storage participating in secondary frequency regulation services in a substation, in the DSAP bidding strategy model construction and processing module, the objective function expression of the DSAP bidding strategy model is:

[0057]

[0058]

[0059]

[0060] In the formula, R DSAP,DA is the net profit of DSAP under the day-ahead bidding strategy; R FR The secondary frequency regulation compensation fee settled by the secondary frequency regulation market to DSAP; R ESS,n The payment fee for DSAP to each substation for energy storage secondary frequency regulation; N represents the total number of aggregated substations, n = 1, 2, 3…, N; They are the upward and downward adjustment capacities declared by DSAP respectively; The secondary frequency regulation capacity forecast price and frequency regulation mileage forecast price for upward and downward services respectively; They are the historical secondary frequency modulation performance indicators and frequency modulation mileage call rate of DSAP in the upward and downward services respectively; They are the historical performance indicators of the up- and down-regulation of the energy storage in the substation n in response to the DSAP control command, i.e., the accuracy of the distributed ESS in the substation tracking the control command to issue the secondary frequency regulation output target; are the contribution of the upward and downward regulation capacity of the substation n at time t respectively; They respectively represent the expected price of secondary frequency regulation capacity and the expected price of frequency regulation mileage declared by substation n at time t for providing upward and downward services.

[0061] As a preferred scheme for an aggregation analysis and processing device for distributed energy storage in a substation area to participate in secondary frequency regulation services, in the clearing model construction and processing module of the day-ahead secondary frequency regulation market, the objective function expression of the clearing model of the day-ahead secondary frequency regulation market is:

[0062]

[0063]

[0064] In the formula, is the total cost of secondary frequency regulation auxiliary service in period t, They are the comprehensive quotation of the mth-order secondary frequency regulation of frequency regulation resource y in period t and the winning capacity of secondary frequency regulation; They are the adjusted capacity quotation, mileage quotation and opportunity cost respectively.

[0065] As a preferred scheme for an aggregation analysis and processing device for participating in secondary frequency regulation services of distributed energy storage in a substation, in the DSAP intraday secondary frequency regulation response optimization strategy formulation and implementation module, the DSAP intraday secondary frequency regulation response optimization strategy includes constructing a DSAP intraday substation distributed ESS secondary frequency regulation capacity rolling optimization model, formulating a DSAP intraday substation distributed ESS secondary frequency regulation response output regulation strategy, and constructing a DSAP intraday substation distributed ESS secondary frequency regulation auxiliary service revenue settlement model;

[0066] The objective function expression of the DSAP intra-day distributed ESS secondary frequency modulation capacity rolling optimization model is:

[0067]

[0068]

[0069]

[0070] In the formula, They are the net income of DSAP on the operation day, the frequency compensation fee settled by the secondary frequency regulation market to DSAP, and the payment fee contributed by DSAP to the secondary frequency regulation of distributed ESS in each substation; N is the total number of aggregated substations, n = 1, 2, 3…, N; They represent the upward and downward capacity of the DSAP winning bid respectively; They are the secondary frequency regulation capacity clearing price and frequency regulation mileage clearing price for downward regulation services respectively; They are the historical secondary frequency regulation performance indicators of DSAP in the upward service and downward service, respectively. The two indicators are not updated during the rolling process, but the actual secondary frequency regulation performance indicators and mileage call rate of each dispatch period on the operation day are recalculated when calculating the DSAP settlement income; They represent the upward and downward capacity allocation of the substation n at time t respectively;

[0071] The implementation steps of the DSAP intra-day distributed ESS secondary frequency response output control strategy are as follows:

[0072] The real-time operating load rate of the distribution transformer in the set area is calculated through the load rate calculation formula;

[0073] According to the real-time operating load rate of the distribution transformer of the set substation, the operating state of the set substation is judged. If the set substation is in a heavy overload state during the sampling period, the set substation is restricted from responding to the output of the downward adjustment signal; if the set substation is in a reverse heavy overload state during the sampling period, the set substation is restricted from responding to the output of the upward adjustment signal; if the operating state of the set substation is normal during the sampling period, the set substation responds to the downward adjustment signal or the upward adjustment signal output;

[0074] The adjustable capacity of the distributed ESS in the set area is calculated by using an adjustable capacity calculation formula;

[0075] According to the distribution transformer operation state of the set substation and the adjustable capacity of the distributed ESS of the set substation, the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation are obtained; by performing data processing on the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation, the optimal output of the distributed ESS upward adjustment response and the optimal output of the distributed ESS downward adjustment response of the set substation are obtained;

[0076] Updating the real-time operation SOC of the distributed ESS in the set area;

[0077] The actual secondary frequency regulation performance index of the distributed ESS in the set area is calculated by the actual secondary frequency regulation performance index calculation formula; the actual frequency regulation mileage call rate of the distributed ESS in the set area is calculated by the actual frequency regulation mileage call rate calculation formula;

[0078] The DSAP intra-day distributed ESS secondary frequency regulation auxiliary service revenue settlement model is calculated based on the actual frequency regulation mileage call rate of the distributed ESS in the set area and the actual secondary frequency regulation performance index of the distributed ESS in the set area to obtain the secondary frequency regulation service revenue of the distributed ESS in the set area and the secondary frequency regulation service revenue of the DSAP.

[0079] The present invention has the following advantages: predicting the user load and photovoltaic output data of the substation area through a neural network to obtain the substation area load data; constructing a substation area distributed ESS optimization operation model, optimizing the obtained substation area load data through the substation area distributed ESS optimization operation model, and obtaining the day-ahead optimization result of the output behavior of the substation area distributed ESS under the condition of meeting user needs; constructing a DSAP bidding strategy model, and obtaining the optimal bidding capacity of DSAP in each time period and the secondary frequency regulation capacity contribution of each substation area through the DSAP bidding strategy model; formulating a step-by-step quotation for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation area and the substation area contract declaration price. Strategy; construct a clearing model for the day-ahead secondary frequency regulation market, and obtain the winning bids of DSAP's secondary frequency regulation capacity in the day-ahead secondary frequency regulation market, the cleared secondary frequency regulation capacity price and mileage price information through the clearing model of the day-ahead secondary frequency regulation market; formulate a DSAP intraday secondary frequency regulation response optimization strategy based on the total winning bids of DSAP's day-ahead secondary frequency regulation capacity in each time period and the real-time operating status of each area's distributed ESS; through the DSAP intraday secondary frequency regulation response optimization strategy, respectively optimize the DSAP intraday area distributed ESS secondary frequency regulation capacity allocation adjustment, DSAP intraday area distributed ESS secondary frequency regulation response output regulation and control, and DSAP intraday area distributed ESS secondary frequency regulation revenue. The present invention proposes a method for calculating the dispatchable capacity of an area distributed ESS, which can more accurately predict the charging and discharging behavior of a distributed ESS by predicting the user load and photovoltaic output of the area on the operating day; based on the prediction results of the area resource output characteristics, further explore the dispatchable capacity of the area distributed ESS, which is helpful to improve the energy utilization efficiency and the economy of system operation. A bidding strategy for DSAP to participate in the day-ahead secondary frequency regulation auxiliary service market is proposed. Based on the prediction of energy storage charging and discharging behavior under the load of the substation and user demand, with the goal of maximizing the net profit of DSAP participating in the secondary frequency regulation market, a bidding optimization model for DSAP to participate in the day-ahead secondary frequency regulation market is established, which is helpful to improve the market competitiveness and economic benefits of DSAP; a distributed energy storage aggregator ladder quotation strategy adapted to the existing secondary frequency regulation market clearing mechanism is proposed, which provides a solution for DSAP to obtain the optimal bidding target. A rolling optimization allocation model for the secondary frequency regulation capacity of energy storage in the substation during the day is established, with the goal of maximizing the profit of distributed energy storage aggregators to optimize the allocation of the secondary frequency regulation capacity of the substation in the next dispatching period; secondly, with the goal of optimizing the frequency regulation effect during the dispatching period, the substation energy storage output is optimized and its operating status is tracked, and the secondary frequency regulation capacity of the next period is rolled according to the operating status of the substation energy storage at the end of the period, which is conducive to improving the real-time frequency regulation effect of DSAP. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0081] Figure 1 A schematic flow chart of an aggregation analysis method for a distributed energy storage system in a substation participating in a secondary frequency regulation service provided in Embodiment 1 of the present invention;

[0082] Figure 2 A schematic diagram of a DSAP secondary frequency regulation capacity step quotation format in an aggregate analysis method for distributed energy storage in a substation participating in a secondary frequency regulation service provided in Example 1 of the present invention;

[0083] Figure 3 A schematic diagram of a rolling optimization strategy for the intraday secondary frequency regulation response of DSAP in an aggregate analysis method for the participation of distributed energy storage in a secondary frequency regulation service provided in Example 1 of the present invention;

[0084] Figure 4 A schematic diagram of a DSAP intra-day secondary frequency regulation response process in an aggregate analysis method for a distributed energy storage system in a substation participating in a secondary frequency regulation service provided in Example 1 of the present invention;

[0085] Figure 5 This is a schematic diagram of a day-ahead load prediction result of a substation in a possible embodiment provided in Embodiment 1 of the present invention;

[0086] Figure 6 A schematic diagram of time-of-use electricity prices for users in a substation area in a possible embodiment provided in Embodiment 1 of the present invention;

[0087] Figure 7 A schematic diagram of the optimization operation results of a distributed ESS in a substation area in a possible embodiment provided in Embodiment 1 of the present invention;

[0088] Figure 8 A schematic diagram of the price declaration for secondary frequency modulation services in each substation in a possible embodiment provided in Embodiment 1 of the present invention;

[0089] Fig. 9 This is a schematic diagram of the result of the ladder declaration of secondary frequency regulation capacity in the DSAP day-ahead secondary frequency regulation market in a possible embodiment provided in Embodiment 1 of the present invention;

[0090] Fig.10 A schematic diagram of the proportion of secondary frequency modulation capacity in each substation in a possible embodiment provided in Embodiment 1 of the present invention;

[0091] Fig.11 This is a schematic diagram of the tiered quotation results of the DSAP day-ahead secondary frequency modulation market in a possible embodiment provided in Embodiment 1 of the present invention;

[0092] Fig.12 A schematic diagram of regional day-ahead secondary frequency modulation capacity demand in a possible embodiment provided in Embodiment 1 of the present invention;

[0093] Fig.13 A schematic diagram of the recent winning bid results of the secondary frequency modulation capacity of the secondary frequency modulation market DSAP in a possible embodiment provided in Embodiment 1 of the present invention;

[0094] Fig.14 A schematic diagram of the day-ahead secondary frequency modulation market clearing price in a possible embodiment provided in Embodiment 1 of the present invention;

[0095] Fig.15 A schematic diagram of the allocation result of the daily increased capacity in each substation in a possible embodiment provided in Embodiment 1 of the present invention;

[0096] Fig.16 A schematic diagram of the allocation results of the capacity reduction in each substation within a day in a possible embodiment provided in Embodiment 1 of the present invention;

[0097] Fig.17 This is a schematic diagram of DSAP intraday secondary frequency modulation performance indicators in a possible embodiment provided in Embodiment 1 of the present invention;

[0098] Fig.18 This is an architecture diagram of an aggregation analysis and processing device for distributed energy storage in a substation participating in secondary frequency regulation services provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0099] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0100] Example 1

[0101] See also Figure 1 Embodiment 1 of the present invention provides an aggregation analysis method for distributed energy storage in a substation participating in secondary frequency regulation service, comprising the following steps:

[0102] S1. Predict the user load and photovoltaic output data of the substation area through a neural network to obtain the substation area load data; construct a substation area distributed ESS optimization operation model, optimize the obtained substation area load data through the substation area distributed ESS optimization operation model, and obtain the day-ahead optimization result of the substation area distributed ESS output behavior under the condition of meeting user needs;

[0103] S2. Construct a DSAP bidding strategy model, and obtain the optimal bidding capacity of DSAP in each period and the secondary frequency regulation capacity contribution of each substation through the DSAP bidding strategy model; formulate a tiered quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation and the substation contract declaration price;

[0104] S3. Construct a clearing model for the day-ahead secondary frequency regulation market, and obtain the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market through the clearing model of the day-ahead secondary frequency regulation market;

[0105] S4. According to the total amount of DSAP secondary frequency regulation capacity bids in each time period and the real-time operating status of each area's distributed ESS, formulate a DSAP intraday secondary frequency regulation response optimization strategy; through the DSAP intraday secondary frequency regulation response optimization strategy, the DSAP intraday distributed ESS secondary frequency regulation capacity allocation adjustment, the DSAP intraday distributed ESS secondary frequency regulation response output regulation and the DSAP intraday distributed ESS secondary frequency regulation revenue are optimized respectively.

[0106] In this embodiment, in step S1, the obtained load data of the substation area is optimized by constructing an optimized operation model of the substation area distributed ESS to obtain the day-ahead optimization result of the output behavior of the substation area distributed ESS under the condition of meeting the user demand;

[0107] Specifically, using the predicted load data of the substation, taking the optimal daily economic benefits of the ESS users in the substation as the goal, and considering the safety and reliability constraints of the substation operation, an optimized operation model of the distributed ESS in the substation is established, and the day-ahead optimization results of the ESS output behavior under user demand are obtained to guide the mining of the aggregatable capacity of the substation.

[0108] A distributed ESS optimization operation model for the substation area is constructed. The objective function expression of the distributed ESS optimization operation model for the substation area is shown in formula (1):

[0109] minC day =C ele +C decay +C loss (1)

[0110]

[0111]

[0112]

[0113]

[0114] In the formula, C day is the daily operation cost of the area; C ele is the daily electricity cost of ESS users in the area; C decay is the daily operating life attenuation cost of the ESS in the substation area; C loss is the operating loss cost of the distribution transformer in the substation; t is the load sampling time; T is the operating cycle; P trans (t), Q trans (t) is the active power and reactive power of the distribution transformer at time t; C TOU (t) is the time-of-use electricity price at time t; ξ is the daily operating capacity decay of the ESS in the substation. Usually, when the ESS capacity decays to 80% of the rated capacity, the ESS is considered retired; C E 、E rate , C P , P rate They are ESS capacity unit cost, rated capacity, PCS power unit cost, and energy storage rated power; P loss (t) is the active power loss of the transformer; P K is the transformer short-circuit loss; U N is the rated voltage of the transformer; S N is the rated capacity.

[0115] The model constraints include area power balance constraints, distribution transformer safe operation constraints, and ESS operation constraints, as shown below:

[0116]

[0117]

[0118]

[0119] SOC min ≤SOC(t)≤SOC max (9)

[0120] SOC(t ini )=SOC(t end ) (10)

[0121]

[0122]

[0123] Flag dis +Flag ch ≤1 (13)

[0124] -Q essmax ≤Q ess (t)≤Q essmax (14)

[0125]

[0126] in, P ess (t) are the predicted value of user active power load, PV power generation and ESS charging and discharging power at time t; f lr is the upper limit of the load factor of the distribution transformer, usually 0.8; SOC(t) is the SOC of the ESS at time t; P ess (t) is the ESS operating power; η is the battery charging and discharging efficiency at standard temperature; Δt is the duration of a single scheduling period; Flag ch and Flag dis They are charge and discharge states, both of which are 0-1 variables; SOC max and SOC min are the upper and lower limits of the state of charge of the ESS, usually 0.9 and 0.1; SOC(t ini ) and SOC(t end ) are the SOC of the ESS at the start and end of the operation optimization cycle; and are the ESS discharge power and charging power respectively, and the discharge is assumed to be positive; Q ess (t) is the PCS reactive power output; Q essmax is the maximum reactive power output of PCS; S essmax It is the PCS rated capacity.

[0127] In this embodiment, in step S2, a DSAP bidding strategy model is constructed, and the optimal bidding capacity of DSAP in each time period and the secondary frequency regulation capacity contribution of each substation are obtained through processing by the DSAP bidding strategy model;

[0128] Specifically, the DSAP bidding strategy model takes the contribution of the secondary frequency regulation capacity of the substation in each time period as the decision variable, and takes the maximization of the daily net operating profit of DSAP participating in the secondary frequency regulation market as the goal. It considers the temporal coupling relationship of the dispatchable capacity of the distributed ESS in the substation to obtain the optimal bidding capacity of DSAP at each moment. At the same time, based on the contribution of the distributed ESS secondary frequency regulation capacity of each substation within the aggregated total capacity at each moment and its contract quotation, a step-by-step bidding strategy for DSAP participating in the secondary frequency regulation auxiliary service market is obtained.

[0129] The objective function of the DSAP bidding strategy model is shown in formula (16):

[0130]

[0131]

[0132]

[0133] In the formula, R DSAP,DA is the net profit of DSAP under the day-ahead bidding strategy; R FR The secondary frequency regulation compensation fee settled by the secondary frequency regulation market to DSAP; R ESS,n The payment fee for DSAP to each substation for energy storage secondary frequency regulation; N represents the total number of aggregated substations, n = 1, 2, 3…, N; They are the upward and downward adjustment capacities declared by DSAP respectively; The secondary frequency regulation capacity forecast price and frequency regulation mileage forecast price for upward and downward services respectively; They are the historical secondary frequency modulation performance indicators and frequency modulation mileage call rate of DSAP in the upward and downward services respectively; They are the historical performance indicators of the up- and down-regulation of the energy storage in the substation n in response to the DSAP control command, i.e., the accuracy of the distributed ESS in the substation tracking the control command to issue the secondary frequency regulation output target; are the contribution of the upward and downward regulation capacity of the substation n at time t respectively; They respectively represent the expected price of secondary frequency regulation capacity and the expected price of frequency regulation mileage declared by substation n at time t for providing upward and downward services.

[0134] The model constraints include bidding capacity constraints, ESS operation external characteristics constraints, and station reliability constraints, as shown below:

[0135]

[0136]

[0137]

[0138]

[0139]

[0140]

[0141]

[0142]

[0143] Where P rate,n 、E rate,n are the rated power and rated capacity of the distributed ESS in area n respectively; P ess,n (t) is the charging and discharging power of energy storage under the demand of ESS users in the substation area; P cap,threshold The entry threshold for the secondary frequency regulation auxiliary service market; cap,limit The upper limit of the secondary frequency regulation capacity reported in a single period; SOC n (t) represents the charge state of station n at time t; e u 、e d They represent the ratio of the electric energy change that may be caused by the unit secondary frequency regulation capacity in the upward and downward services to the secondary frequency regulation capacity, and can be statistically analyzed using the historical dispatching data of the week before the operation day; x n (t) is the charging and discharging sign of the distributed ESS in the area; P ess,n (t) greater than 0 represents discharge; x n (t) is 0, P ess,n (t) is less than 0, which means charging; x n (t) is 1; P trans,n (t) is the active power of the distribution transformer in the area when the distributed ESS in the area outputs power according to user demand.

[0144] Formulate a tiered quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the secondary frequency regulation capacity contribution of each substation and the substation contract declared price;

[0145] Specifically, the bidding strategy model proposed in the present invention is used to optimize the optimal bidding capacity of DSAP in each period under the guidance price and the secondary frequency regulation capacity contribution of each substation. According to the secondary frequency regulation capacity contribution of each substation and the substation contract declaration price, a tiered quotation scheme for DSAP to participate in the secondary frequency regulation auxiliary service market is formulated. The tiered quotation form is as follows: Figure 2 shown.

[0146] The following is an example of the steps to formulate a DSAP quotation increase plan:

[0147] T1. Calculate the ranking price of each area according to formula (27) Sort each area according to the sorting price.

[0148]

[0149] T2. After the substations are ranked, the substations are divided into M groups according to the set quotation step number M. According to formula (28), the sum of the secondary frequency regulation capacity contribution of the m-th group of substations Φ(m) is calculated as the m-th order declared capacity declared by DSAP. m=1,2,3,…M.

[0150]

[0151] After T3 and DSAP determine the declared capacity at each stage, they formulate the secondary frequency regulation capacity quotation and frequency regulation mileage quotation at each stage: select the maximum frequency regulation mileage declared price of the mth group of substations and determine it as the mth frequency regulation mileage quotation declared by DSAP As shown in formula (29); The mth order secondary frequency regulation capacity quotation Then take the difference between the maximum sorting price of the m-group station area and the m-order mileage quotation, which can be obtained by formula (30), where A 0-1 variable that indicates whether station n contributes to secondary frequency modulation capacity during period t.

[0152]

[0153]

[0154] If the capacity declared for secondary frequency regulation in the mth stage of DSAP is 0, the mth stage capacity quotation and mileage quotation are both 0. Similarly, the method for formulating the secondary frequency regulation capacity ladder quotation plan when DSAP participates in the downward adjustment market is the same as the above steps. Through the above steps, DSAP can establish a bidding strategy for participating in the secondary frequency regulation ancillary service market based on the guidance price information. When formulating the bidding strategy, the model takes into account the temporal coupling relationship of the dispatchable capacity of the distributed ESS in the substation area. The final bidding plan enables DSAP to participate in the centralized bidding of the secondary frequency regulation ancillary service market in the form of ladder quotation. The ladder quotation form adapts to the existing secondary frequency regulation ancillary service market mechanism and clearing model, and there is no need to readjust the clearing model of the secondary frequency regulation ancillary service market for ESS, thereby promoting the more extensive participation of distributed ESS in the substation area in other types of power spot markets such as secondary frequency regulation ancillary services.

[0155] In this embodiment, in step S3, a clearing model of the day-ahead secondary frequency regulation market is constructed, and the day-ahead secondary frequency regulation market clearing model is used for processing to obtain the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market;

[0156] Specifically, the secondary frequency regulation market targets distinguish between two one-way secondary frequency regulation services, namely, upward frequency regulation and downward frequency regulation. The two secondary frequency regulation services are cleared separately, but the calculation model used in the clearing process is the same. The present invention takes the upward frequency regulation service as an example to establish a clearing model for the day-ahead secondary frequency regulation market. To simplify the description, "frequency regulation resources" are used to represent the market entities that provide secondary frequency regulation auxiliary services in the secondary frequency regulation market, including traditional generators, new energy and ESS, or their agents, etc.

[0157] Each frequency regulation resource participating in the spot market is required to declare secondary frequency regulation capacity, capacity quotation and mileage quotation. The market operator adjusts the quotation based on the mileage-to-capacity ratio of its historical frequency regulation period and the secondary frequency regulation performance indicators of each frequency regulation resource, and calculates the opportunity cost of providing secondary frequency regulation auxiliary services to form a comprehensive quotation, as shown in equations (31)-(33).

[0158]

[0159]

[0160]

[0161] In the formula, are the adjusted upper frequency regulation capacity quotation, mileage quotation, and opportunity cost respectively; Ω represents the frequency regulation resource set participating in the secondary frequency regulation auxiliary service market; is its historical secondary frequency modulation performance index, and the calculation formula is shown in formula (34); is the ratio of the frequency regulation mileage to capacity of the frequency regulation resource y in history; C LMP (t) represents the node marginal electricity price for clearing the electricity market; P is the market price of the electric energy of frequency regulation resource y; y (t) are respectively the winning bid quantity of frequency regulation resource y in the electric energy market and the economic operating point under the clearing electricity price; since DSAP in the present invention only participates in the secondary frequency regulation market but not in the electric energy market, and the opportunity cost is the loss caused by the frequency regulation resource not being able to fully participate in the energy market due to providing secondary frequency regulation, there is no opportunity cost for frequency regulation resources such as DSAP that do not participate in the electric energy market.

[0162]

[0163] In the formula, i and I are the sampling points and total number of samples of the secondary frequency modulation signal in the scheduling period respectively; are the actual secondary frequency modulation response amount and the secondary frequency modulation target signal of the frequency modulation resource y at time i respectively; It is the average value of the absolute value of the secondary frequency modulation signal within the scheduling period.

[0164] The secondary frequency regulation ancillary service market clearing is sorted by comprehensive quotations, taking into account the system secondary frequency regulation capacity and mileage requirements. The objective function of the clearing model is shown in Equation (35), and the constraints are shown in Equations (36)-(40).

[0165]

[0166]

[0167]

[0168]

[0169]

[0170]

[0171] In the formula, is the total cost of secondary frequency regulation auxiliary service in period t; They are the comprehensive quotation for the mth-order secondary frequency regulation of frequency regulation resource y in period t, the secondary frequency regulation winning capacity, the declared capacity and the total winning capacity; They are respectively the system secondary frequency regulation auxiliary service capacity and mileage requirements in time period t; among them, the mileage requirement is the minimum value among the average frequency regulation mileage in the past 7 days, the ratio of the historical frequency regulation mileage to capacity of the whole system and the capacity demand, and the ratio of the historical frequency regulation mileage to capacity of each winning frequency regulation resource and the winning capacity.

[0172] The above model can be used to calculate the comprehensive clearing price of secondary frequency regulation, that is, the comprehensive clearing price of secondary frequency regulation of marginal frequency regulation resources. The comprehensive clearing price of secondary frequency regulation will be decomposed into two parts: mileage clearing price and capacity clearing price. The highest mileage bid among the winning resources is selected as the mileage clearing price. The capacity clearing price is the difference between the comprehensive clearing price and the product of the mileage clearing price and the system's historical mileage-capacity ratio, as shown in equations (41)-(42).

[0173]

[0174]

[0175] In the formula, They represent the frequency regulation mileage clearing price, capacity clearing price and secondary frequency regulation comprehensive clearing price of the upward regulation service in period t respectively; A 0-1 variable indicating the winning bid status of the mth order increase capacity for frequency regulation resource i; Adjust the mileage-capacity ratio for the system history.

[0176] The revenue of frequency regulation resource i in the ancillary service market consists of two parts: capacity and mileage. Among them, the capacity revenue is settled according to the day-ahead clearing results, and the deviation settlement is done in real time; the mileage revenue is settled in the future according to the actual frequency regulation mileage on the operation day. At the same time, the settlement needs to consider the secondary frequency regulation performance indicators of each frequency regulation resource on the operation day to adjust the settlement fee. Taking the frequency regulation service as an example, the specific revenue calculation formula is shown in formula (43).

[0177]

[0178] In the formula, Settle the service fee for frequency modulation resource y. It is the actual frequency regulation mileage-capacity ratio during period t of the operating day.

[0179] In this embodiment, in step S4, a DSAP intraday secondary frequency regulation response optimization strategy is formulated according to the total amount of DSAP's secondary frequency regulation capacity bids in each time period and the real-time operation status of each distributed ESS in each substation area;

[0180] Specifically, after completing the market clearing of the day-ahead secondary frequency regulation auxiliary service, DSAP obtains the secondary frequency regulation winning capacity, capacity clearing price and mileage clearing price for the upward and downward regulation services on the operation day. In the real-time response stage on the operation day, DSAP needs to respond to the secondary frequency regulation signal issued by the dispatch center according to the secondary frequency regulation winning capacity and allocate the winning capacity to each substation. Since there is a difference between the guidance price used as the reference for the quotation strategy and the day-ahead secondary frequency regulation market clearing price, the actual winning capacity of DSAP may also be different from the declared capacity, which makes it difficult to match the real-time operation situation with the secondary frequency regulation capacity contribution of each substation under the bidding strategy as the secondary frequency regulation capacity allocation of the substation on the operation day. At the same time, during the real-time secondary frequency regulation process on the operation day, the load forecast deviation of the substation and the uncertainty of the secondary frequency regulation signal will affect the actual available regulation capacity of the distributed ESS in the substation. Therefore, during the operation day, DSAP needs to update the operating status of the distributed ESS in each substation in real time, and make rolling adjustments to the secondary frequency regulation capacity allocation of the distributed ESS in each dispatching period to improve the actual frequency regulation effect of each substation.

[0181] The present invention proposes a DSAP intraday secondary frequency modulation response optimization control strategy, and its control framework is as follows: Figure 3Before entering each dispatching period t on the operation day, DSAP establishes a rolling optimization allocation model for the secondary frequency regulation capacity of the distributed ESS in each substation considering the coupling of multiple periods based on the total amount of secondary frequency regulation capacity winning bids in each period and the real-time operation status of the distributed ESS in each substation, and adjusts the secondary frequency regulation capacity allocation of each substation in the next dispatching period; after entering the dispatching period t, DSAP issues the secondary frequency regulation capacity allocation for period t to each substation The secondary frequency modulation signal with a time granularity of 4s is used to optimize and control the charging and discharging behavior of ESS in real time to respond to the secondary frequency modulation instruction. The distributed ESS in the substation tracks the secondary frequency modulation signal and feeds back its real-time operating status to DSAP at the end of each scheduling period to carry out optimization and control in the next scheduling period.

[0182] The DSAP intraday secondary frequency regulation response optimization strategy includes constructing a DSAP intraday distributed ESS secondary frequency regulation capacity rolling optimization model, formulating a DSAP intraday distributed ESS secondary frequency regulation response output regulation strategy, and constructing a DSAP intraday distributed ESS secondary frequency regulation auxiliary service revenue settlement model;

[0183] The process of constructing the DSAP intra-day distributed ESS secondary frequency modulation capacity rolling optimization model is as follows:

[0184] Since the revenue of DSAP in the secondary frequency regulation market is positively correlated with the secondary frequency regulation performance, in the rolling optimization allocation of DSAP secondary frequency regulation capacity, DSAP is allocated from the starting scheduling period t j The goal is to maximize the net profit from (j=1,2,…,T) to the end of the entire operation day. The established model uses 1h as the time granularity, that is, every 1h, the secondary frequency regulation capacity allocation of the distributed ESS in the next scheduling period is optimized in a rolling manner, and only the capacity allocation plan of the first period is taken as the capacity allocation plan of period t j The objective function expression of the DSAP intra-day distributed ESS secondary frequency regulation capacity rolling optimization model is shown in formula (44):

[0185]

[0186]

[0187]

[0188] In the formula, They are the net income of DSAP on the operation day, the frequency compensation fee settled by the secondary frequency regulation market to DSAP, and the payment fee contributed by DSAP to the secondary frequency regulation of distributed ESS in each substation; N is the total number of aggregated substations, n = 1, 2, 3…, N; They represent the upward and downward capacity of the DSAP winning bid respectively; They are the secondary frequency regulation capacity clearing price and frequency regulation mileage clearing price for downward regulation services respectively; They are the historical secondary frequency regulation performance indicators of DSAP in the upward service and downward service, respectively. The two indicators are not updated during the rolling process, but the actual secondary frequency regulation performance indicators and mileage call rate of each dispatch period on the operation day are recalculated when calculating the DSAP settlement income; They represent the upward and downward capacity allocation of area n at time t respectively.

[0189] The model constraints include secondary frequency regulation capacity allocation constraints, substation secondary frequency regulation capacity constraints, and substation distributed ESS operation external characteristics constraints. The secondary frequency regulation capacity allocation constraints are shown in equations (47)-(48); the substation secondary frequency regulation capacity constraints and substation distributed ESS operation external characteristics constraints are shown in equations (19)-(25), and the substation upper and lower frequency regulation capacity contributions are Replaced with the upper and lower frequency regulation capacity allocation of the station area respectively

[0190]

[0191]

[0192] The starting scheduling period t is obtained through rolling optimization of the above model. j The secondary frequency regulation capacity allocation for each substation is calculated and issued to each substation. The distributed ESS in the substation realizes the secondary frequency regulation response during the scheduling period through charging and discharging.

[0193] The process of formulating the DSAP intra-day distributed ESS secondary frequency regulation response output control strategy is as follows:

[0194] Each substation receives the secondary frequency regulation capacity allocation plan before DSAP. During the real-time operation of the dispatching period, the dispatching center sends a secondary frequency regulation signal to DSAP every 4 seconds. DSAP receives the signal and sends it to the distributed ESS in the substation for response. Since the secondary frequency regulation auxiliary service income of the distributed ESS in the substation is positively correlated with the secondary frequency regulation performance, improving the accuracy of tracking the secondary frequency regulation signal is used as the control target of the secondary frequency regulation response output of the distributed ESS in the substation. After each dispatching period, the real-time operating status of the distributed ESS in the substation is updated and fed back to DSAP to complete the secondary frequency regulation capacity allocation for the next dispatching period. At the same time, the secondary frequency regulation performance index of the substation in the dispatching period is calculated for the settlement of the secondary frequency regulation service of the distributed ESS in the substation during the dispatching period. The secondary frequency regulation response output control strategy of the distributed ESS in the substation proposed in this section, through real-time monitoring of the operating status of the distribution transformer in the substation, explores the real-time adjustable capacity of the substation, and determines the optimal secondary frequency regulation response output power of the substation. The complete process of DSAP intraday secondary frequency regulation response is as follows: Figure 4 shown.

[0195] First, calculate the real-time operating load rate of the distribution transformer in the substation:

[0196]

[0197]

[0198] In the formula, They are the real-time distribution transformer operating power, load and photovoltaic output; It is the real-time load rate of the distribution transformer.

[0199] Whether the substation has a heavy overload or reverse heavy overload problem is determined based on the distribution transformer operating load rate. If the substation i is in a heavy overload state at the sampling time, it is restricted from continuing to respond to the downward signal output, otherwise the heavy overload problem of the substation will be aggravated; similarly, if the substation is in a reverse heavy overload state, its upward service response output will be zero.

[0200] After determining the real-time operating status of the distribution transformer in the substation, analyze the adjustable capacity of the distributed ESS in the substation:

[0201]

[0202]

[0203] In the formula, are the upward and downward remaining adjustable capacities of the distributed ESS in area n at time i; S n is the distribution transformer capacity of substation n; Δi is the sampling interval of the secondary frequency modulation signal, which is 4s.

[0204] According to the operating status of the distribution transformer and the remaining adjustable capacity of the substation, the upper and lower output limits of the distributed ESS in the substation are obtained respectively.

[0205]

[0206]

[0207] Then the optimal output of the secondary frequency modulation response of the distributed ESS in area n at time i can be obtained by equations (55)-(56).

[0208]

[0209]

[0210] In the formula, They are respectively for the area to increase or decrease the optimal response output; are the standardized secondary frequency modulation target signals of the distributed ESS in the area at time i within the dispatch period t, and the two signals are not positive at the same time; the terms on the right side of the brackets in equations (55)-(56) are the target outputs of the area at time i.

[0211] At the same time, the real-time operation SOC of the distributed ESS in the substation is updated through equation (56):

[0212]

[0213] After completing the secondary frequency regulation response of a dispatching period, the secondary frequency regulation performance index and real-time mileage call rate of the distributed ESS in the dispatching period are counted. Actual secondary frequency regulation performance index The calculation method of reference formula (34) is as follows:

[0214]

[0215]

[0216] In the formula, are the actual frequency regulation mileage call rates of the distributed ESS in the dispatching period t, are the actual upward and downward target signals at time t respectively.

[0217] The proposed strategy for optimizing the secondary frequency regulation output of the distributed ESS in the substation area improves the frequency regulation effect of the substation area and increases the real-time secondary frequency regulation benefits of the substation area. By real-time tracking of the distributed ESS in the substation area, the real-time SOC and real-time secondary frequency regulation performance indicators of the distributed ESS in each substation area are fed back to the DSAP at the end of the scheduling period, so as to realize the information interaction between the substation area and the DSAP, and guide the DSAP to complete the optimization of the secondary frequency regulation capacity allocation plan of the substation area in the next scheduling period.

[0218] The DSAP intra-day distributed ESS secondary frequency regulation auxiliary service revenue settlement model is calculated based on the actual frequency regulation mileage call rate of the distributed ESS in the set area and the actual secondary frequency regulation performance index of the distributed ESS in the set area to obtain the secondary frequency regulation service revenue of the distributed ESS in the set area and the secondary frequency regulation service revenue of the DSAP.

[0219] Specifically, the secondary frequency regulation service revenue settlement of the distributed ESS in the substation area refers to formula (46), and the historical secondary frequency regulation performance indicators and frequency regulation mileage call rate of the distributed ESS in the substation area are replaced by the real-time statistical results of the operation day to complete the calculation.

[0220] DSAP secondary frequency regulation service revenue settlement:

[0221]

[0222]

[0223] The actual secondary frequency regulation performance of DSAP in each scheduling period on the operating day is calculated by equations (60) and (61), and the secondary frequency regulation service settlement fee of DSAP is calculated by referring to equation (45). It is also necessary to replace the historical secondary frequency regulation performance indicators and frequency regulation mileage call rate data in equations (60) and (61) with the real-time statistical results on the operating day.

[0224] In a possible embodiment, specific example implementation steps are provided as follows:

[0225] M1. Distributed energy storage output forecast in the substation under user demand:

[0226] See also Figure 5 , showing the load output prediction of 6 types of substations, using the substation distributed ESS optimization operation model, the distributed ESS output curves of 6 typical substations are optimized. The configuration of distributed ESS in each substation is shown in Table 1. The time-of-day electricity price of the substation is as follows Figure 6 As shown in the figure, the reasonable operating range of the forward and reverse load rates of the distribution transformer in the substation is set within 80%. The optimization results are as follows Figure 7 shown.

[0227]

[0228]

[0229] Table 1 Energy storage configuration in the substation area

[0230] M2, the bidding strategy of the distributed energy storage aggregator in the substation area:

[0231] Set the size of the distributed ESS in the DSAP aggregation area. Expand the above 6 types of areas, each of which is expanded to 5, and expand 5 additional types of areas 6 and set different secondary frequency modulation contract prices for comparison, counted as area 7, a total of 35 areas. The average clearing price of the peak and valley section of the secondary frequency modulation market in the past seven days is used as the reference price for DSAP to participate in the secondary frequency modulation market. Each area declares the frequency modulation mileage price and the secondary frequency modulation capacity price, such as Figure 8 shown.

[0232] The historical secondary frequency regulation performance indicators of the substation are all set to 0.98, the historical up- and down-regulation mileage-capacity ratios of the substation are set to 16.63 and 16.35 respectively, the historical up- and down-regulation energy-capacity ratios are set to 0.5059 and 0.4941, and the substation load conditions and ESS output behaviors are all in accordance with the day-ahead forecast results. The upper and lower limits of the secondary frequency regulation capacity declared in a single DSAP dispatch period are set to 5MW and 2MW respectively. Using the bidding strategy proposed in the present invention, the number of DSAP secondary frequency regulation capacity declaration steps is set to 4, so the 7 types of substations are divided into 4 groups, and the secondary frequency regulation capacity optimization bidding strategy for DSAP participating in the day-ahead secondary frequency regulation market is obtained, such as Fig. 9 As shown in the application strategy, the secondary frequency regulation capacity of each area is as follows: Fig.10 As shown; the secondary frequency regulation capacity and frequency regulation mileage marginal price reported in each period are as follows Fig.11 shown.

[0233] M3, the results of the secondary frequency modulation market clearing the day before:

[0234] Regional secondary frequency regulation market capacity demand Fig.12 As shown in Figure 2, the historical frequency regulation mileage-capacity ratios of the system for upward and downward adjustments are 15.45 and 14.92 respectively; the information of other bidding entities is shown in Table 2, and the bidding capacity of each bidding entity is divided into four stages for tiered quotation.

[0235]

[0236]

[0237] Table 2 Information submitted by other bidding entities

[0238] The day-ahead secondary frequency regulation auxiliary service market clearing model established by the present invention is used to clear the upward and downward services respectively, and the winning bid capacity of DSAP and the secondary frequency regulation market clearing price are obtained, such as Fig.13 , Fig.14 shown.

[0239] M4, the secondary frequency modulation response effect of the distributed aggregator in the substation area during the day:

[0240] After entering the operation day, DSAP allocates the secondary frequency regulation capacity of each dispatching period to the substation according to the winning bid of the secondary frequency regulation capacity in the day-ahead market and the clearing price of the secondary frequency regulation market, using the distributed energy storage aggregator's intraday secondary frequency regulation optimization strategy proposed in this invention. In order to illustrate the effectiveness of the proposed rolling optimization allocation model for secondary frequency regulation capacity, the following two scenarios are set for comparative analysis.

[0241] Scenario 1: During the dispatch period, each ESS in each substation responds to secondary frequency modulation according to the previous day's optimization allocation plan for secondary frequency modulation capacity in the substation. That is, the secondary frequency modulation capacity allocation plan is optimized only before the day of operation. In real-time operation, each substation uses the previous day's optimization results to respond to secondary frequency modulation signals.

[0242] Scenario 2: DSAP uses the method proposed in this paper to optimize the allocation of secondary frequency regulation capacity on a daily rolling basis and regulates the ESS in the substation area to respond to secondary frequency regulation.

[0243] The secondary frequency regulation capacity allocation of the substation in each dispatching period during the operation day under the two scenarios is as follows: Fig.15 , Fig.16 As shown, it can be seen that the upward capacity allocation schemes of scenario 1 and scenario 2 during the operation day have large differences in the PV high-incidence and subsequent periods, while the difference in the downward capacity allocation schemes in the two scenarios is relatively small; at the same time, the deviation in the daily load forecast of the previous area, especially the deviation in the load forecast of the reverse heavy overload area during the PV high-incidence period, will greatly affect the adjustable capacity of the area upward.

[0244] In the two scenarios, the DSAP intraday secondary frequency modulation performance indicators are as follows: Fig.17 It can be seen that the method of daily rolling optimization allocation of secondary frequency regulation capacity in scenario 2 is helpful to improve the DSAP secondary frequency regulation performance indicators.

[0245] In summary, the present invention predicts the user load and photovoltaic output data of the substation through a neural network to obtain the substation load data; constructs a substation distributed ESS optimization operation model, optimizes the obtained substation load data through the substation distributed ESS optimization operation model, and obtains the day-ahead optimization result of the output behavior of the substation distributed ESS under the condition of meeting user needs; constructs a DSAP bidding strategy model, and obtains the optimal bidding capacity of DSAP in each time period and the secondary frequency regulation capacity contribution of each substation through the DSAP bidding strategy model; formulates a step-by-step quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation and the substation contract declaration price. Omitted; construct a clearing model for the day-ahead secondary frequency regulation market, and obtain the winning bids of DSAP's secondary frequency regulation capacity in the day-ahead secondary frequency regulation market, the cleared secondary frequency regulation capacity price and mileage price information through the clearing model of the day-ahead secondary frequency regulation market; formulate a DSAP intraday secondary frequency regulation response optimization strategy based on the total winning bids of DSAP's day-ahead secondary frequency regulation capacity in each time period and the real-time operation status of each area's distributed ESS; through the DSAP intraday secondary frequency regulation response optimization strategy, respectively optimize the DSAP intraday area distributed ESS secondary frequency regulation capacity allocation adjustment, DSAP intraday area distributed ESS secondary frequency regulation response output regulation and DSAP intraday area distributed ESS secondary frequency regulation revenue. The present invention proposes a method for calculating the dispatchable capacity of an area distributed ESS, which can more accurately predict the charging and discharging behavior of the distributed ESS by predicting the user load and photovoltaic output of the area on the operating day; based on the prediction results of the area resource output characteristics, further explore the dispatchable capacity of the area distributed ESS, which is helpful to improve the energy utilization efficiency and the economy of system operation. A bidding strategy for DSAP to participate in the day-ahead secondary frequency regulation auxiliary service market is proposed. Based on the prediction of energy storage charging and discharging behavior under the load of the substation and user demand, with the goal of maximizing the net profit of DSAP participating in the secondary frequency regulation market, a bidding optimization model for DSAP to participate in the day-ahead secondary frequency regulation market is established, which is helpful to improve the market competitiveness and economic benefits of DSAP; a distributed energy storage aggregator ladder quotation strategy adapted to the existing secondary frequency regulation market clearing mechanism is proposed, which provides a solution for DSAP to obtain the optimal bidding target. A rolling optimization allocation model for the secondary frequency regulation capacity of energy storage in the substation during the day is established, with the goal of maximizing the profit of distributed energy storage aggregators to optimize the allocation of the secondary frequency regulation capacity of the substation in the next dispatching period; secondly, with the goal of optimizing the frequency regulation effect during the dispatching period, the substation energy storage output is optimized and its operating status is tracked, and the secondary frequency regulation capacity of the next period is rolled according to the operating status of the substation energy storage at the end of the period, which is conducive to improving the real-time frequency regulation effect of DSAP.

[0246] It should be noted that the method of the embodiment of the present disclosure can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described method.

[0247] It should be noted that the above describes some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0248] Example 2

[0249] See also Fig.18 Embodiment 2 of the present invention further provides an aggregation analysis processing device for distributed energy storage in a substation participating in a secondary frequency regulation service, which adopts an aggregation analysis method for distributed energy storage in a substation participating in a secondary frequency regulation service in the above embodiment 1, including:

[0250] The distributed ESS optimization operation model construction and processing module 001 is used to predict the user load and photovoltaic output data of the substation area through a neural network to obtain the load data of the substation area; construct the distributed ESS optimization operation model of the substation area, optimize the obtained load data of the substation area through the distributed ESS optimization operation model of the substation area, and obtain the day-ahead optimization result of the output behavior of the distributed ESS in the substation area under the condition of meeting the user demand;

[0251] DSAP bidding strategy model construction and processing module 002 is used to construct a DSAP bidding strategy model, and obtain the optimal bidding capacity of DSAP in each time period and the secondary frequency regulation capacity contribution of each substation through the DSAP bidding strategy model; formulate a tiered quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation and the substation contract declaration price;

[0252] The clearing model construction and processing module 003 of the day-ahead secondary frequency regulation market is used to construct the clearing model of the day-ahead secondary frequency regulation market, and obtain the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market through the clearing model of the day-ahead secondary frequency regulation market;

[0253] DSAP intraday secondary frequency regulation response optimization strategy formulation and implementation module 004 is used to formulate DSAP intraday secondary frequency regulation response optimization strategy based on the total amount of DSAP secondary frequency regulation capacity bids in each time period and the real-time operating status of each distributed ESS in each substation; through the DSAP intraday secondary frequency regulation response optimization strategy, the DSAP intraday distributed ESS secondary frequency regulation capacity allocation adjustment, DSAP intraday distributed ESS secondary frequency regulation response output regulation and DSAP intraday distributed ESS secondary frequency regulation benefits are optimized respectively.

[0254] In this embodiment, in the substation distributed ESS optimization operation model construction and processing module 001, the objective function expression of the substation distributed ESS optimization operation model is:

[0255] min C day =C ele +C decay +C loss

[0256]

[0257]

[0258]

[0259]

[0260] In the formula, C day is the daily operation cost of the area, C ele is the daily electricity cost of ESS users in the area, C decay is the daily operating life attenuation cost of the ESS in the substation, C loss is the operating loss cost of the distribution transformer in the substation; t is the load sampling time; T is the operating cycle; P trans (t), Q trans (t) are the active power and reactive power of the distribution transformer at time t; C TOU (t) is the time-of-use electricity price at time t; ξ is the daily operating capacity decay of the ESS in the substation. Usually, when the ESS capacity decays to 80% of the rated capacity, the ESS is considered retired; C E 、E rate , C P , P rate They are ESS capacity unit cost, rated capacity, PCS power unit cost, and energy storage rated power; P loss (t) is the active power loss of the transformer; P K is the transformer short-circuit loss; U N is the rated voltage of the transformer; S N is the rated capacity.

[0261] In this embodiment, in the DSAP bidding strategy model construction and processing module 002, the objective function expression of the DSAP bidding strategy model is:

[0262]

[0263]

[0264]

[0265] In the formula, R DSAP,DA is the net profit of DSAP under the day-ahead bidding strategy; R FR The secondary frequency regulation compensation fee settled by the secondary frequency regulation market to DSAP; R ESS,n The payment fee for DSAP to each substation for energy storage secondary frequency regulation; N represents the total number of aggregated substations, n = 1, 2, 3…, N; They are the upward and downward adjustment capacities declared by DSAP respectively; The secondary frequency regulation capacity forecast price and frequency regulation mileage forecast price for upward and downward services respectively; They are the historical secondary frequency modulation performance indicators and frequency modulation mileage call rate of DSAP in the upward and downward services respectively; They are the historical performance indicators of the up- and down-regulation of the energy storage in the substation n in response to the DSAP control command, i.e., the accuracy of the distributed ESS in the substation tracking the control command to issue the secondary frequency regulation output target; are the contribution of the upward and downward regulation capacity of the substation n at time t respectively; They respectively represent the expected price of secondary frequency regulation capacity and the expected price of frequency regulation mileage declared by substation n at time t for providing upward and downward services.

[0266] In this embodiment, in the clearing model construction and processing module 003 of the day-ahead secondary frequency modulation market, the objective function expression of the clearing model of the day-ahead secondary frequency modulation market is:

[0267]

[0268]

[0269] In the formula, is the total cost of secondary frequency regulation auxiliary service in period t, They are the comprehensive quotation of the mth-order secondary frequency regulation of frequency regulation resource y in period t and the winning capacity of secondary frequency regulation; They are the adjusted capacity quotation, mileage quotation and opportunity cost respectively.

[0270] In this embodiment, in the DSAP intraday secondary frequency regulation response optimization strategy formulation and implementation module 004, the DSAP intraday secondary frequency regulation response optimization strategy includes constructing a DSAP intraday distributed ESS secondary frequency regulation capacity rolling optimization model, formulating a DSAP intraday distributed ESS secondary frequency regulation response output regulation strategy, and constructing a DSAP intraday distributed ESS secondary frequency regulation auxiliary service revenue settlement model;

[0271] The objective function expression of the DSAP intra-day distributed ESS secondary frequency modulation capacity rolling optimization model is:

[0272]

[0273]

[0274]

[0275] In the formula, They are the net income of DSAP on the operation day, the frequency compensation fee settled by the secondary frequency regulation market to DSAP, and the payment fee contributed by DSAP to the secondary frequency regulation of distributed ESS in each substation; N is the total number of aggregated substations, n = 1, 2, 3…, N; They represent the upward and downward capacity of the DSAP winning bid respectively; They are the secondary frequency regulation capacity clearing price and frequency regulation mileage clearing price for downward regulation services respectively; They are the historical secondary frequency regulation performance indicators of DSAP in the upward service and downward service, respectively. The two indicators are not updated during the rolling process, but the actual secondary frequency regulation performance indicators and mileage call rate of each dispatch period on the operation day are recalculated when calculating the DSAP settlement income; Represents the historical performance index of the distributed ESS in area n in response to the DSAP up- and down-regulation instructions; They represent the upward and downward capacity allocation of the substation n at time t respectively;

[0276] The implementation steps of the DSAP intra-day distributed ESS secondary frequency response output control strategy are as follows:

[0277] The real-time operating load rate of the distribution transformer in the set area is calculated through the load rate calculation formula;

[0278] According to the real-time operating load rate of the distribution transformer of the set substation, the operating state of the set substation is judged. If the set substation is in a heavy overload state during the sampling period, the set substation is restricted from responding to the output of the downward adjustment signal; if the set substation is in a reverse heavy overload state during the sampling period, the set substation is restricted from responding to the output of the upward adjustment signal; if the operating state of the set substation is normal during the sampling period, the set substation responds to the downward adjustment signal or the upward adjustment signal output;

[0279] The adjustable capacity of the distributed ESS in the set area is calculated by using an adjustable capacity calculation formula;

[0280] According to the distribution transformer operation state of the set substation and the adjustable capacity of the distributed ESS of the set substation, the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation are obtained; by performing data processing on the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation, the optimal output of the distributed ESS upward adjustment response and the optimal output of the distributed ESS downward adjustment response of the set substation are obtained;

[0281] Updating the real-time operation SOC of the distributed ESS in the set area;

[0282] The actual secondary frequency regulation performance index of the distributed ESS in the set area is calculated by the actual secondary frequency regulation performance index calculation formula; the actual frequency regulation mileage call rate of the distributed ESS in the set area is calculated by the actual frequency regulation mileage call rate calculation formula;

[0283] The DSAP intra-day distributed ESS secondary frequency regulation auxiliary service revenue settlement model is calculated based on the actual frequency regulation mileage call rate of the distributed ESS in the set area and the actual secondary frequency regulation performance index of the distributed ESS in the set area to obtain the secondary frequency regulation service revenue of the distributed ESS in the set area and the secondary frequency regulation service revenue of the DSAP.

[0284] It should be noted that the information interaction, execution process and other contents between the modules of the above-mentioned device are based on the same concept as the method embodiment in Example 1 of the present application, and the technical effects they bring are the same as those of the method embodiment of the present application. For specific contents, please refer to the description in the method embodiment shown in the previous part of the present application, and will not be repeated here.

[0285] Example 3

[0286] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which a program code for an aggregation analysis method for distributed energy storage in a substation participating in a secondary frequency regulation service is stored, and the program code includes instructions for executing embodiment 1 or any possible implementation method thereof, a method for aggregation analysis of distributed energy storage in a substation participating in a secondary frequency regulation service.

[0287] The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0288] Example 4

[0289] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0290] The processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute an aggregation analysis method for distributed energy storage in a substation participating in secondary frequency regulation services in accordance with Example 1 or any possible implementation thereof.

[0291] Specifically, the processor can be implemented by hardware or by software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor implemented by reading software codes stored in a memory. The memory can be integrated in the processor or can be located outside the processor and exist independently.

[0292] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center.

[0293] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0294] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. An aggregate analysis method for distributed energy storage in a substation participating in secondary frequency regulation services, characterized in that: include: The user load and photovoltaic output data of the substation are predicted through neural network to obtain the substation load data; Constructing an optimized operation model of the distributed ESS in the substation area, optimizing the obtained load data of the substation area through the optimized operation model of the distributed ESS in the substation area, and obtaining a day-ahead optimized result of the output behavior of the distributed ESS in the substation area under the condition of meeting user demand; Construct a DSAP bidding strategy model for distributed energy storage system aggregation service providers, and obtain the optimal bidding capacity of DSAP in each period and the secondary frequency regulation capacity contribution of each substation through the DSAP bidding strategy model; formulate a tiered quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation and the substation contract declaration price; Constructing a clearing model for the day-ahead secondary frequency regulation market, and obtaining the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market through the clearing model of the day-ahead secondary frequency regulation market; According to the total amount of DSAP's secondary frequency regulation capacity bids in each time period and the real-time operation status of each area's distributed ESS, a DSAP intraday secondary frequency regulation response optimization strategy is formulated; through the DSAP intraday secondary frequency regulation response optimization strategy, the DSAP intraday area distributed ESS secondary frequency regulation capacity allocation adjustment, the DSAP intraday area distributed ESS secondary frequency regulation response output regulation, and the DSAP intraday area distributed ESS secondary frequency regulation benefits are optimized respectively; The objective function expression of the distributed ESS optimization operation model in the substation area is: minC day =C ele +C decay +C loss In the formula, C day is the daily operation cost of the area, C ele is the daily electricity cost of ESS users in the area, C decay is the daily operating life attenuation cost of the ESS in the substation, C loss The operating loss cost of the distribution transformer in the substation area; t is the load sampling time; T is the operation cycle; P trans (t), Q trans (t) are the active power and reactive power of the distribution transformer at time t; C TOU (t) is the time-of-use electricity price at time t; ξ is the daily operating capacity decay of the ESS in the substation. Usually, when the ESS capacity decays to 80% of the rated capacity, the ESS is considered retired; C E 、E rate , C P , P rate They are ESS capacity unit cost, rated capacity, PCS power unit cost, and energy storage rated power; P loss (t) is the active power loss of the transformer; P K is the transformer short-circuit loss; U N is the rated voltage of the transformer; S N is the rated capacity; The objective function expression of the DSAP bidding strategy model is: In the formula, R DSAP,DA is the net profit of DSAP under the day-ahead bidding strategy; R FR The secondary frequency regulation compensation fee settled by the secondary frequency regulation market to DSAP; R ESS,n The payment fee for DSAP to each substation for energy storage secondary frequency regulation; N represents the total number of aggregated substations, n = 1, 2, 3…, N; They are the upward and downward adjustment capacities declared by DSAP respectively; The secondary frequency regulation capacity forecast price and frequency regulation mileage forecast price for upward and downward services respectively; They are the historical secondary frequency modulation performance indicators and frequency modulation mileage call rate of DSAP in the upward and downward services respectively; They are the historical performance indicators of the up- and down-regulation of the energy storage in the substation n in response to the DSAP control command, i.e., the accuracy of the distributed ESS in the substation tracking the control command to issue the secondary frequency regulation output target; are the contribution of the upward and downward regulation capacity of the substation n at time t respectively; They respectively represent the expected price of secondary frequency regulation capacity and the expected price of frequency regulation mileage declared by substation n at time t for providing upward and downward services.

2. According to claim 1, a method for aggregate analysis of distributed energy storage participating in secondary frequency regulation service in a substation, characterized in that: The objective function expression of the clearing model of the day-ahead secondary frequency modulation market is: In the formula, is the total cost of secondary frequency regulation auxiliary service in period t, They are the comprehensive quotation of the mth-order secondary frequency regulation of frequency regulation resource y in period t and the winning capacity of secondary frequency regulation; They are the adjusted capacity quotation, mileage quotation and opportunity cost respectively.

3. According to claim 2, a method for aggregate analysis of distributed energy storage participating in secondary frequency regulation service in a substation, characterized in that: The DSAP intraday secondary frequency regulation response optimization strategy includes constructing a DSAP intraday distributed ESS secondary frequency regulation capacity rolling optimization model, formulating a DSAP intraday distributed ESS secondary frequency regulation response output regulation strategy, and constructing a DSAP intraday distributed ESS secondary frequency regulation auxiliary service revenue settlement model; The objective function expression of the DSAP intra-day distributed ESS secondary frequency modulation capacity rolling optimization model is: In the formula, They are the net income of DSAP on the operation day, the frequency compensation fee settled by the secondary frequency regulation market to DSAP, and the payment fee contributed by DSAP to the secondary frequency regulation of distributed ESS in each substation; N is the total number of aggregated substations, n = 1, 2, 3…, N; They represent the upward and downward capacity of the DSAP winning bid respectively; They represent the frequency regulation mileage clearing price and capacity clearing price of the upward service in period t respectively; They are the secondary frequency regulation capacity clearing price and frequency regulation mileage clearing price for downward regulation services respectively; They are the historical secondary frequency regulation performance indicators of DSAP in the upward service and downward service, respectively. The two indicators are not updated during the rolling process, but the actual secondary frequency regulation performance indicators and mileage call rate of each dispatch period on the operation day are recalculated when calculating the DSAP settlement income; Represents the historical performance index of the distributed ESS in area n in response to the DSAP up- and down-regulation instructions; They represent the upward and downward capacity allocation of the substation n at time t respectively; The implementation steps of the DSAP intra-day distributed ESS secondary frequency response output control strategy are as follows: The real-time operating load rate of the distribution transformer in the set area is calculated through the load rate calculation formula; According to the real-time operating load rate of the distribution transformer in the set area, the operating state of the set area is judged. If the set area is in a heavy overload state during the sampling period, the set area is restricted from responding to the output reduction signal; If the set area is in a reverse heavy overload state during the sampling period, the set area is restricted from responding to the increase signal output; If the operation status of the set area is normal during the sampling period, the output of the signal is lowered or increased in response; The adjustable capacity of the distributed ESS in the set area is calculated by using an adjustable capacity calculation formula; According to the distribution transformer operation state of the set substation and the adjustable capacity of the distributed ESS of the set substation, the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation are obtained; by performing data processing on the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation, the optimal output of the distributed ESS upward adjustment response and the optimal output of the distributed ESS downward adjustment response of the set substation are obtained; Updating the real-time operation SOC of the distributed ESS in the set area; The actual secondary frequency regulation performance index of the distributed ESS in the set area is calculated by the actual secondary frequency regulation performance index calculation formula; the actual frequency regulation mileage call rate of the distributed ESS in the set area is calculated by the actual frequency regulation mileage call rate calculation formula; The DSAP intra-day distributed ESS secondary frequency regulation auxiliary service revenue settlement model is calculated based on the actual frequency regulation mileage call rate of the distributed ESS in the set area and the actual secondary frequency regulation performance index of the distributed ESS in the set area to obtain the secondary frequency regulation service revenue of the distributed ESS in the set area and the secondary frequency regulation service revenue of the DSAP.

4. An aggregate analysis and processing device for distributed energy storage in a substation participating in a secondary frequency regulation service, using an aggregate analysis method for distributed energy storage in a substation participating in a secondary frequency regulation service as claimed in any one of claims 1 to 3, characterized in that: include: The distributed ESS optimization operation model construction and processing module is used to predict the user load and photovoltaic output data of the substation area through a neural network to obtain the load data of the substation area; construct the distributed ESS optimization operation model of the substation area, optimize the obtained load data of the substation area through the distributed ESS optimization operation model of the substation area, and obtain the day-ahead optimization result of the output behavior of the distributed ESS in the substation area under the condition of meeting the user demand; DSAP bidding strategy model construction and processing module, used to construct a DSAP bidding strategy model, and obtain the optimal bidding capacity of DSAP in each period and the secondary frequency regulation capacity contribution of each substation through the DSAP bidding strategy model; formulate a tiered quotation strategy for DSAP to participate in the secondary frequency regulation auxiliary service market based on the obtained secondary frequency regulation capacity contribution of each substation and the substation contract declaration price; A clearing model construction and processing module for the day-ahead secondary frequency regulation market is used to construct a clearing model for the day-ahead secondary frequency regulation market, and obtain the secondary frequency regulation capacity winning amount, cleared secondary frequency regulation capacity price and mileage price information of DSAP in the day-ahead secondary frequency regulation market through the clearing model for the day-ahead secondary frequency regulation market; The DSAP intraday secondary frequency regulation response optimization strategy formulation and implementation module is used to formulate the DSAP intraday secondary frequency regulation response optimization strategy according to the total amount of DSAP's secondary frequency regulation capacity bids in each time period and the real-time operation status of each area's distributed ESS; through the DSAP intraday secondary frequency regulation response optimization strategy, the DSAP intraday area distributed ESS secondary frequency regulation capacity allocation adjustment, DSAP intraday area distributed ESS secondary frequency regulation response output regulation and DSAP intraday area distributed ESS secondary frequency regulation benefits are optimized respectively; In the construction and processing module of the distributed ESS optimization operation model in the substation area, the objective function expression of the distributed ESS optimization operation model in the substation area is: minC day =C ele +C decay +C loss In the formula, C day is the daily operation cost of the area, C ele is the daily electricity cost of ESS users in the area, C decay is the daily operating life attenuation cost of the ESS in the substation, C loss The operating loss cost of the distribution transformer in the substation area; t is the load sampling time; T is the operation cycle; P trans (t), Q trans (t) are the active power and reactive power of the distribution transformer at time t; C TOU (t) is the time-of-use electricity price at time t; ξ is the daily operating capacity decay of the ESS in the substation. Usually, when the ESS capacity decays to 80% of the rated capacity, the ESS is considered retired; C E 、E rate , C P , P rate They are ESS capacity unit cost, rated capacity, PCS power unit cost, and energy storage rated power; P loss (t) is the transformer active power loss; P K is the transformer short-circuit loss; U N is the rated voltage of the transformer; S N is the rated capacity; In the DSAP bidding strategy model construction and processing module, the objective function expression of the DSAP bidding strategy model is: In the formula, R DSAP,DA is the net profit of DSAP under the day-ahead bidding strategy; R FR The secondary frequency regulation compensation fee settled by the secondary frequency regulation market to DSAP; R ESS,n The payment fee for DSAP to each substation for energy storage secondary frequency regulation; N represents the total number of aggregated substations, n = 1, 2, 3…, N; They are the upward and downward adjustment capacities declared by DSAP respectively; The secondary frequency regulation capacity forecast price and frequency regulation mileage forecast price for upward and downward services respectively; They are the historical secondary frequency modulation performance indicators and frequency modulation mileage call rate of DSAP in the upward and downward services respectively; They are the historical performance indicators of the up- and down-regulation of the energy storage in the substation n in response to the DSAP control command, i.e., the accuracy of the distributed ESS in the substation tracking the control command to issue the secondary frequency regulation output target; are the contribution of the upward and downward regulation capacity of the substation n at time t respectively; They respectively represent the expected price of secondary frequency regulation capacity and the expected price of frequency regulation mileage declared by substation n at time t for providing upward and downward services.

5. According to claim 4, a device for analyzing and processing distributed energy storage participating in secondary frequency regulation service in a substation, characterized in that: In the clearing model construction and processing module of the day-ahead secondary frequency modulation market, the objective function expression of the clearing model of the day-ahead secondary frequency modulation market is: In the formula, is the total cost of secondary frequency regulation auxiliary service in period t, They are the comprehensive quotation of the mth-order secondary frequency regulation of frequency regulation resource y in period t and the winning capacity of secondary frequency regulation; They are the adjusted capacity quotation, mileage quotation and opportunity cost respectively.

6. The aggregation analysis and processing device for distributed energy storage participating in secondary frequency regulation service in a substation according to claim 5 is characterized in that: In the DSAP intraday secondary frequency regulation response optimization strategy formulation and implementation module, the DSAP intraday secondary frequency regulation response optimization strategy includes constructing a DSAP intraday distributed ESS secondary frequency regulation capacity rolling optimization model, formulating a DSAP intraday distributed ESS secondary frequency regulation response output regulation strategy, and constructing a DSAP intraday distributed ESS secondary frequency regulation auxiliary service revenue settlement model; The objective function expression of the DSAP intra-day distributed ESS secondary frequency modulation capacity rolling optimization model is: In the formula, They are the net income of DSAP on the operation day, the frequency compensation fee settled by the secondary frequency regulation market to DSAP, and the payment fee contributed by DSAP to the secondary frequency regulation of distributed ESS in each substation; N is the total number of aggregated substations, n = 1, 2, 3…, N; They represent the upward and downward capacity of the DSAP winning bid respectively; They represent the frequency regulation mileage clearing price and capacity clearing price of the upward service in period t respectively; They are the secondary frequency regulation capacity clearing price and frequency regulation mileage clearing price for downward regulation services respectively; They are the historical secondary frequency regulation performance indicators of DSAP in the upward service and downward service, respectively. The two indicators are not updated during the rolling process, but the actual secondary frequency regulation performance indicators and mileage call rate of each dispatch period on the operation day are recalculated when calculating the DSAP settlement income; They represent the upward and downward capacity allocation of the substation n at time t respectively; The implementation steps of the DSAP intra-day distributed ESS secondary frequency response output control strategy are as follows: The real-time operating load rate of the distribution transformer in the set area is calculated through the load rate calculation formula; According to the real-time operating load rate of the distribution transformer in the set area, the operating state of the set area is judged. If the set area is in a heavy overload state during the sampling period, the set area is restricted from responding to the output reduction signal; If the set area is in a reverse heavy overload state during the sampling period, the set area is restricted from responding to the increase signal output; If the operation status of the set area is normal during the sampling period, the output of the signal is lowered or increased in response; The adjustable capacity of the distributed ESS in the set area is calculated by using an adjustable capacity calculation formula; According to the distribution transformer operation state of the set substation and the adjustable capacity of the distributed ESS of the set substation, the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation are obtained; by performing data processing on the upper limit of the output of the distributed ESS upward adjustment response and the upper limit of the output of the distributed ESS downward adjustment response of the set substation, the optimal output of the distributed ESS upward adjustment response and the optimal output of the distributed ESS downward adjustment response of the set substation are obtained; Updating the real-time operation SOC of the distributed ESS in the set area; The actual secondary frequency regulation performance index of the distributed ESS in the set area is calculated by the actual secondary frequency regulation performance index calculation formula; the actual frequency regulation mileage call rate of the distributed ESS in the set area is calculated by the actual frequency regulation mileage call rate calculation formula; The DSAP intra-day distributed ESS secondary frequency regulation auxiliary service revenue settlement model is calculated based on the actual frequency regulation mileage call rate of the distributed ESS in the set area and the actual secondary frequency regulation performance index of the distributed ESS in the set area to obtain the secondary frequency regulation service revenue of the distributed ESS in the set area and the secondary frequency regulation service revenue of the DSAP.

Images