A user-side distributed energy storage facility aggregation management and control method and system

Abstract

The application provides a user-side distributed energy storage facility aggregation management and control method and system, comprising: obtaining information of all accessed distributed energy storage facilities and power grid interaction targets of various application scenarios; performing characteristic analysis on the information of the distributed energy storage facilities to obtain adjustment conditions of the distributed energy storage facilities under various application scenarios; aggregating all the distributed energy storage facilities based on the adjustment conditions of all the distributed energy storage facilities to obtain adjustment capabilities of various distributed energy storage categories under various application scenarios; and generating adjustment instructions for managing and controlling various energy storage facility categories based on the power grid interaction targets of various application scenarios and the adjustment capabilities of various distributed energy storage categories, which can effectively solve the problems that the existing user-side distributed energy storage is scattered in multiple points, small in scale, difficult to be effectively aggregated, and unable to participate in power grid interaction, while the flexible adjustment characteristics of energy storage resources are utilized, the power balance level of the distribution network is improved, clean energy generation and consumption are promoted, and the power supply quality and reliability of the regional distribution network are improved.

Description

Technical Field

[0001] The present invention relates to the field of aggregation and control of distributed energy storage facilities on the user side of a distribution network, and in particular to a method and system for aggregation and control of distributed energy storage facilities on the user side. Background Art

[0002] With the rapid development of new energy, the power system has become more prominent with its "double high" and "double peak" characteristics (a high proportion of renewable energy and power electronic equipment; peak loads in summer and winter). The randomness, volatility, and anti-peaking characteristics of new energy cause the net load of the system to fluctuate significantly, which puts tremendous pressure on the balance of power and electricity. Electrochemical energy storage has the ability to quickly and flexibly adjust in both directions. It can be widely penetrated into all aspects of power generation, transmission, and distribution, improving the flexibility of the power system and becoming an optimal solution to the problems of new power systems with new energy as the main body. As of the end of 2020, China has invested a cumulative installed capacity of 3269.2MW of electrochemical energy storage. With the further development of new energy, the scale of distributed energy storage on the user side will explode in the future.

[0003] Behind-the-meter energy storage encompasses various forms, including "independent behind-the-meter energy storage," "distributed photovoltaics + energy storage," "distribution network-side energy storage," and "electric vehicles." These storage facilities are characterized by being small-scale, dispersed, and independently managed. Currently, various energy storage facilities primarily rely on local operation and control, resulting in ineffective coordination between storage facilities and other power sources. This hinders interaction between sources, grids, loads, and storage on the behind-the-meter side. Furthermore, due to the relatively small scale of behind-the-meter energy storage, it struggles to meet the minimum capacity requirements for grid interactions such as peak load regulation and demand response, hindering the effective utilization of the flexible adjustment capabilities of behind-the-meter distributed energy storage. Summary of the Invention

[0004] To address the existing issues of the difficulty in effectively aggregating distributed energy storage on the user side of the distribution network, the difficulty in interacting with the source, grid, load, and storage, and the inability to participate in grid interaction, the present invention proposes a method for aggregating and controlling distributed energy storage facilities on the user side, including:

[0005] Obtain information on all connected distributed energy storage facilities and grid interaction targets for each application scenario;

[0006] Analyze the characteristics of the information of each distributed energy storage facility to obtain the regulation status of each distributed energy storage facility in each application scenario;

[0007] Based on the regulation status of all distributed energy storage facilities, all distributed energy storage facilities are aggregated to obtain the regulation capacity of each distributed energy storage category in each application scenario;

[0008] Based on the grid interaction goals of each application scenario and the regulation capabilities of each distributed energy storage category, regulation instructions for controlling each energy storage facility category are generated.

[0009] Preferably, the adjustment conditions of each distributed energy storage facility include: maximum adjustable power increase, maximum adjustable power decrease and adjustment time.

[0010] Preferably, the maximum adjustable power increase is calculated as follows:

[0011] ΔP adj,up =P d,max -P curr

[0012] Where ΔP adj,up P is the maximum adjustable power increase of the energy storage facility; d,max is the maximum discharge power of the energy storage facility; P curr is the current power of the energy storage facility;

[0013] The maximum adjustable power reduction is calculated as follows:

[0014] ΔP adj,down =P c,max -P curr

[0015] Where ΔP adj,down P is the maximum adjustable power reduction of the energy storage facility; c,max is the maximum discharge power of the energy storage facility; P curr is the current power of the energy storage facility;

[0016] The adjustment time is calculated as follows:

[0017]

[0018] Where, T adj The adjustment time corresponding to the energy storage facility adjustment power ΔP; ΔP is the adjustment power; Q spe is the rated capacity of energy storage; SOC is the state of charge; P curr is the current power of the energy storage facility; P d,max is the maximum allowable discharge power of the energy storage facility; P c,max The maximum allowable charging power of the energy storage facility.

[0019] Preferably, the adjustment range of the adjustment power is determined by the following formula:

[0020] ΔP adj,down ≤ΔP≤ΔP adj,up

[0021] Where ΔP adj,down is the maximum adjustable power reduction of the energy storage facility; ΔP adj,up Increase the maximum adjustable power of energy storage facilities.

[0022] Preferably, the step of aggregating all distributed energy storage facilities based on their regulation conditions to obtain the regulation capabilities of each distributed energy storage category in each application scenario includes:

[0023] Constructing a clustering feature set based on all distributed energy storage facilities, information about the distributed energy storage facilities, and a clustering indicator set set for each application scenario;

[0024] Based on the cluster feature set, the distance between any two distributed energy storage facilities in the cluster feature set is calculated to construct a proximity matrix:

[0025] Based on the proximity matrix, clustering the distributed energy storage facilities using K-MEANS, and determining the regulation capacity of each distributed energy storage category;

[0026] The regulation capability includes: power regulation capability, power regulation capability and regulation response time;

[0027] The application scenarios include at least one or more of the following: participating in grid frequency regulation, participating in grid peak regulation, and participating in demand response.

[0028] Preferably, the clustering feature set is constructed based on all distributed energy storage facilities, information about the distributed energy storage facilities, and a clustering indicator set set for each application scenario, including:

[0029] Build a facility collection based on all connected distributed energy storage facilities:

[0030] Based on the information and regulation status of all connected distributed energy storage facilities, a set of energy storage facility clustering characteristic indicators is constructed:

[0031] constructing an initial set based on the facility set and the indicator set;

[0032] A clustering feature set is constructed based on the clustering indicator set and the initial set set for each application scenario.

[0033] Preferably, the cluster feature set is as follows:

[0034]

[0035] Where M is the clustering feature set; AS is the initial set; IN is the clustering feature index set; ST i is the i-th distributed energy storage facility, CT i is the i-th clustering feature index; M l is the characteristic value of the lth distributed energy storage facility; v ij is the value of the jth characteristic index of the i-th distributed energy storage facility; IN kis the parameter of the kth characteristic indicator; n is the number of aggregated energy storage facilities, and m is the number of clustering characteristic indicators.

[0036] Preferably, the power regulation capability of each distributed energy storage category is calculated as follows:

[0037]

[0038] Where ΔP ass,i is the power regulation capability of the i-th category; ΔP j is the adjustable power implemented by the jth distributed energy storage in this category; o is the number of distributed energy storage facilities in this category;

[0039] The power regulation capability of each distributed energy storage category is calculated as follows:

[0040]

[0041] Where ΔQ ass,i is the power regulation capability of the i-th category; ΔQ j is the adjustable power of the jth distributed energy storage in this category;

[0042] The regulation response time of each distributed energy storage type is calculated as follows:

[0043]

[0044] Where, t ass,i is the adjustment response time of the i-th category; t j is the regulation response time of the jth distributed energy storage implementation in this category.

[0045] Preferably, the generating of regulation instructions for controlling each energy storage facility category based on the grid interaction target of each application scenario and the regulation capability of each distributed energy storage category includes:

[0046] Convert the interaction goals of each application scenario into various adjustment capabilities and set the maximum adjustment response time;

[0047] Determine an objective function with the goal of economic optimization, and set constraints for the objective function;

[0048] Solving the objective function based on the respective regulation capabilities, maximum regulation response time and constraint conditions to obtain respective regulation capability values ​​of respective distributed energy storage categories;

[0049] The adjustment capability values ​​of the distributed energy storage categories are used as control instructions for the distributed energy storage categories.

[0050] Preferably, the objective function is as follows:

[0051] f=min{c 1,i ×ΔP i +c 2,i ×ΔQ i}

[0052] The constraints are as follows:

[0053]

[0054] Where c 1,i is the electricity regulation cost of the ith category; c 2,i is the power regulation cost of the i-th category; ΔP i The regulation power provided for the i-th category; ΔQ i The amount of regulation provided for the i-th category; t i is the adjustment response time of the i-th category.

[0055] Preferably, the obtaining of information of all connected distributed energy storage facilities includes:

[0056] Obtain information about each distributed energy storage facility based on a pre-built distributed energy storage data model;

[0057] The distributed energy storage data model includes: basic information, control characteristics, operation information and regulation information;

[0058] The basic information includes at least one or more of the following: facility type, energy storage medium, voltage level, rated capacity, rated power, commissioning date, owner and aggregator;

[0059] The control characteristics include at least one or more of the following: whether controllable, charging response time, discharging response time, charging adjustment time, discharging adjustment time, charging to discharging conversion time and discharging to charging conversion time;

[0060] The operation information includes at least one or more of the following: operation status, state of charge, charging power, discharging power, charging capacity and discharging capacity;

[0061] The control information includes at least one or more of the following: a controlled state, a chargeable amount, a dischargeable amount, a maximum discharge power allowable value, a maximum charging power allowable value, a maximum discharge power available time, and a maximum charging power available time.

[0062] Based on the same inventive concept, the present invention also provides a user-side distributed energy storage facility aggregated management and control system, comprising:

[0063] The access layer is used to obtain information about all connected distributed energy storage facilities and the grid interaction goals of each application scenario;

[0064] The application layer is used to perform characteristic analysis on the information of each distributed energy storage facility to obtain the regulation status of each distributed energy storage facility in each application scenario; aggregate all distributed energy storage facilities based on the regulation status of all distributed energy storage facilities to obtain the regulation capability of each distributed energy storage category in each application scenario; and generate regulation instructions for controlling each energy storage facility category based on the grid interaction goals of each application scenario and the regulation capability of each distributed energy storage category.

[0065] Preferably, the system further comprises a device layer;

[0066] The equipment layer includes connected distributed energy storage facilities;

[0067] The access layer is used to obtain information about all connected distributed energy storage facilities and grid interaction targets for each application scenario based on the device layer.

[0068] Compared with the prior art, the present invention has the following beneficial effects:

[0069] 1. The present invention provides a method and system for aggregated control of user-side distributed energy storage facilities, including: obtaining information of all connected distributed energy storage facilities and grid interaction targets for each application scenario; performing characteristic analysis on the information of each distributed energy storage facility to obtain the regulation status of each distributed energy storage facility under each application scenario; aggregating all distributed energy storage facilities based on the regulation status of all distributed energy storage facilities to obtain the regulation capability of each distributed energy storage category under each application scenario; generating regulation instructions for controlling each energy storage facility category based on the grid interaction targets for each application scenario and the regulation capability of each distributed energy storage category, thereby enabling the aggregation of distributed energy storage to participate in grid interaction, solving the problem that distributed energy storage cannot participate due to the high threshold for power peak shaving services and demand response, effectively alleviating energy storage costs, and giving full play to the flexible regulation resource characteristics of energy storage;

[0070] 2. The technical solution provided by the present invention can also achieve wide access to various types of distributed energy storage facilities, effectively aggregate decentralized distributed energy storage resources, and solve the problem of coordinated control of distributed energy storage;

[0071] 3. The technical solution provided by the present invention can also enable distributed energy storage to participate in source-grid-load-storage interaction, active power regulation, etc., give full play to the flexible adjustment characteristics of energy storage resources, improve the power balance level of the distribution network, promote clean energy generation and consumption, and enhance the power supply quality and reliability of the regional distribution network;

[0072] 4. The technical solution provided by the present invention can effectively solve the problems of existing user-side distributed energy storage being dispersed at multiple points, small in scale, difficult to effectively aggregate, and unable to participate in grid interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 A flowchart of the method for aggregated control of distributed energy storage facilities on the user side provided by the present invention;

[0074] Figure 2 This is a schematic diagram of the distributed energy storage data model;

[0075] Figure 3 This is a schematic diagram of the operating characteristics analysis;

[0076] Figure 4 This is the architecture diagram of the user-side distributed energy storage facility aggregation management and control system of the present invention. DETAILED DESCRIPTION

[0077] In order to better understand the present invention, the present invention is further described below with reference to the accompanying drawings and examples.

[0078] Example 1:

[0079] The present invention proposes a method for aggregated control of distributed energy storage facilities on the user side. Figure 1 Shown, including:

[0080] S1. Obtain information on all connected distributed energy storage facilities and grid interaction targets for each application scenario;

[0081] S2. Analyze the characteristics of the information of each distributed energy storage facility to obtain the regulation status of each distributed energy storage facility in each application scenario;

[0082] S3. Aggregate all distributed energy storage facilities based on their regulation conditions to obtain the regulation capabilities of each distributed energy storage category in each application scenario;

[0083] S4. Generate regulation instructions for controlling each energy storage facility category based on the grid interaction goals of each application scenario and the regulation capabilities of each distributed energy storage category.

[0084] It is of great significance to effectively aggregate various distributed energy storage resources, widely participate in grid interaction, promote the balance of power and electricity in the distribution network, and ensure the safe and reliable operation of the distribution network.

[0085] Wherein, in step S1, information of each distributed energy storage facility is obtained through a pre-built distributed energy storage data model;

[0086] like Figure 2 As shown, the distributed energy storage data model includes: basic information, control characteristics, operation information and regulation information;

[0087] The basic information includes at least one or more of the following: facility type, energy storage medium, voltage level, rated capacity, rated power, commissioning date, owner and aggregator;

[0088] The control characteristics include at least one or more of the following: whether controllable, charging response time, discharging response time, charging adjustment time, discharging adjustment time, charging to discharging conversion time and discharging to charging conversion time;

[0089] The operation information includes at least one or more of the following: operation status, state of charge, charging power, discharging power, charging capacity and discharging capacity;

[0090] The control information includes at least one or more of the following: a controlled state, a chargeable amount, a dischargeable amount, a maximum discharge power allowable value, a maximum charging power allowable value, a maximum discharge power available time, and a maximum charging power available time.

[0091] Here, building a distributed energy storage data model can achieve information access for various distributed energy storage facilities and is the basis for user-side distributed energy storage aggregation. The data model includes:

[0092] 1. Basic information, including at least the following data items:

[0093] ① Facility type: independent energy storage on the user side, energy storage in distributed photovoltaic configuration, energy storage on the distribution network side,

[0094] Electric vehicle charging piles, etc.

[0095] ②Energy storage medium: lead acid, lithium ion, liquid flow, etc.

[0096] ③ Voltage level: 200(380)V, 10kV, etc.

[0097] ④Rated capacity

[0098] ⑤Rated power

[0099] ⑥ Commissioning date

[0100] ⑦Owner

[0101] ⑧Aggregator

[0102] 2. Control characteristics, including at least the following data items:

[0103] ① Is it controllable: Yes, No

[0104] ②Charging response time

[0105] ③Discharge response time

[0106] ④Charging adjustment time

[0107] ⑤Discharge adjustment time

[0108] ⑥Charge to discharge conversion time

[0109] ⑦Discharge to charge conversion time

[0110] 3. Operation information, including at least the following data items:

[0111] ①Operation status: shutdown, standby, charging, discharging, fault, etc.

[0112] ②State of charge (SOC)

[0113] ③Charging power

[0114] ④Discharge power

[0115] ⑤Charge capacity

[0116] ⑥Discharge capacity

[0117] 4. Regulatory information, including at least the following data items:

[0118] ①Controlled state: remote control (discharging), remote control (charging), local control, etc.

[0119] ②Rechargeable capacity

[0120] ③Dischargeable capacity

[0121] ④ Maximum allowable discharge power

[0122] ⑤ Maximum charging power allowed

[0123] ⑥ Maximum discharge power available time

[0124] ⑦ Maximum charging power available time.

[0125] Step S2 performs characteristic analysis on the information of each distributed energy storage facility to obtain the regulation status of each distributed energy storage facility in each application scenario, specifically including:

[0126] Based on the data model, the operating characteristics of distributed energy storage facilities are analyzed.

[0127] Analyze the operating constraints and adjustable capabilities of distributed energy storage facilities in different scenarios, and obtain the adjustable power range and adjustment time of distributed energy storage facilities. The analysis results are as follows: Figure 3 As shown, it provides support for the aggregation of various distributed energy storage facilities. The regulation of each distributed energy storage facility includes the maximum adjustable power increase, the maximum adjustable power reduction, and the regulation time.

[0128] 1. The maximum adjustable power increase is calculated as follows:

[0129] ΔP adj,up =P d,max -P curr

[0130] Where ΔP adj,upis the maximum adjustable power increase (kW); P d,max is the maximum discharge power of the energy storage facility (kW); P curr It is the current power (kW) of the energy storage facility, which is negative during charging and positive during discharging.

[0131] 2. The maximum adjustable power reduction is calculated as follows:

[0132] ΔP adj,down =P c,max -P curr

[0133] Where ΔP adj,down P is the maximum adjustable power of the energy storage facility (kW); c,max is the maximum discharge power of the energy storage facility (kW), which is a negative value; P curr It is the current power (kW) of the energy storage facility, which is negative during charging and positive during discharging.

[0134] 3. Adjust the time and calculate it according to the following formula:

[0135]

[0136] Where, T adj is the adjustment time (h) corresponding to the power adjustment ΔP; ΔP is the adjustment power, which is positive when increasing and negative when decreasing. The adjustment range is ΔP adj,down ≤ΔP≤ΔP adj,up ;Q spe is the rated capacity of energy storage (kWh); SOC is the state of charge (%); P curr is the current power of the energy storage facility, with discharge being a positive value and charge being a negative value; P d,max is the maximum allowable discharge power of the energy storage facility; P c,max is the maximum allowable charging power of the energy storage facility; ΔP adj,up Increase the maximum adjustable power of energy storage facilities.

[0137] Step S3: Aggregate all distributed energy storage facilities based on their regulation status to obtain the regulation capability of each distributed energy storage category in each application scenario, specifically including:

[0138] 1. Construct all connected user-side distributed energy storage facilities into a facility set ST:

[0139] ST={ST1, ST2, ..., ST n}

[0140] 2. Based on the data model and operational characteristic analysis results, a cluster characteristic indicator set CT of energy storage facilities is constructed:

[0141] CT={CT1,CT2,...,CTm}

[0142] The CT item includes operating status, whether it is controllable, charging response time, discharging response time, charging adjustment time, discharging adjustment time, charging to discharging conversion time, discharging to charging conversion time, SOC, adjustable power increase, adjustable power increase, etc.

[0143] 3. Based on the facility set and indicator set, construct an initial set AS of n×m:

[0144]

[0145] Where, v ij is the value of the jth characteristic indicator of the i-th distributed energy storage facility, 1≤i≤n, 1≤j≤m.

[0146] 4. For distributed energy storage aggregation participating in grid frequency regulation, peak regulation, demand response and other application scenarios, different clustering indicator sets IN are set:

[0147]

[0148] In the formula, IN k is the parameter of the kth characteristic index, 1≤k≤m.

[0149] 5. Construct the clustering feature set M based on the initial set AS and the clustering indicator set IN:

[0150]

[0151] Where M is the clustering feature set; AS is the initial set; IN is the clustering feature index set; ST i is the i-th distributed energy storage facility, CT i is the i-th clustering feature index M l is the characteristic value of the lth distributed energy storage facility, 1≤l≤m; v ij is the value of the jth characteristic index of the i-th distributed energy storage facility; IN k is the parameter of the kth characteristic indicator; n is the number of aggregated energy storage facilities, and m is the number of clustering characteristic indicators.

[0152] 6. According to the cluster feature set M, calculate the distance between each two points and construct the proximity matrix PM:

[0153]

[0154] Where s ij The distance between the characteristic value of the i-th distributed energy storage facility and the characteristic value of the j-th distributed energy storage facility, 1≤i≤n, 1≤j≤n.

[0155] 7. For the proximity matrix PM, the K-MEANS algorithm is used to realize the clustering of distributed energy storage aggregation in different application scenarios such as frequency regulation, peak regulation, and demand response.

[0156] 8. Evaluate the power and electricity regulation capabilities and regulation response time of each distributed energy storage category to provide a basis for distributed energy storage to participate in grid interaction.

[0157] ① Power regulation capability of the i-th category:

[0158]

[0159] Where ΔP ass,i is the power regulation capacity of the i-th category (kW); ΔP j is the adjustable power of the jth distributed energy storage implementation in this category. When calculating the adjustable capacity, it is equal to the maximum adjustable power increase; when calculating the adjustable capacity, it is equal to the maximum adjustable power reduction; o is the number of distributed energy storage facilities in this category.

[0160] ②Power regulation capability of the i-th category:

[0161]

[0162] Where ΔQ ass,i is the power regulation capability of the i-th category (kWh); ΔQ j The adjustable power of the jth distributed energy storage implementation in this category is equal to the dischargeable capacity when calculating the adjustable energy, and equal to the chargeable capacity when calculating the adjustable energy downward.

[0163] ③ Adjustment response time of the i-th category:

[0164]

[0165] Where, t ass,i is the adjustment response time of the i-th category (s); t j The regulation response time of the jth distributed energy storage in this category can be the charging response time, the discharging response time, the charging to discharging conversion time, the discharging to charging conversion time, etc.

[0166] Step S4, generating regulation instructions for controlling each energy storage facility category based on the grid interaction goals of each application scenario and the regulation capabilities of each distributed energy storage category, specifically includes:

[0167] 1. Divide the interactive objectives of grid frequency regulation, peak regulation, and demand response into power ΔP tar , power ΔQ tar Adjustment capability requirements, set the maximum adjustment response time t max ;

[0168] 2. Taking economic optimization as the goal and setting constraints for the objective function;

[0169] The objective function is as follows:

[0170] f=min{c 1,i ×ΔP i +c 2,i ×ΔQ i}

[0171] The constraints are as follows:

[0172]

[0173] Where c 1,i is the electricity regulation cost of the ith category (yuan / kW); c 2,i is the electricity regulation cost of the i-th category (yuan / kWh); ΔP i The regulated power provided for the i-th category (kW); ΔQ i The regulated power provided for the i-th category (kWh); t i is the adjustment response time (s) of the i-th category.

[0174] 3. Based on the adjustment capabilities, maximum adjustment response time and constraints, the objective function is solved to obtain the adjustment capability values ​​of each distributed energy storage category; the adjustment capability values ​​of each distributed energy storage category are used as the control instructions of each distributed energy storage category to determine the power and electricity adjustment instructions provided by the distributed energy storage category that meets the requirements.

[0175] Example 2:

[0176] Based on the same inventive concept, the present invention also provides a user-side distributed energy storage facility aggregation management and control system, such as Figure 4 As shown in the figure, the system consists of a three-layer architecture consisting of the facility layer, the access layer, and the application layer:

[0177] Facility layer: covers various forms of distributed energy storage facilities, including "user-side independent energy storage", "distributed photovoltaic + energy storage", "distribution network-side energy storage", "electric vehicle charging piles", etc.

[0178] Access layer: This layer enables communication between the facility layer and the application layer. Various distributed energy storage facilities can be connected to the system through "user or energy enterprise self-built management systems," "station area intelligent fusion terminals," "collection terminals," and other means.

[0179] Application layer: Used to deploy distributed energy storage aggregation management and control systems and enable communication with other systems such as power distribution, marketing, and electricity markets.

[0180] The facility layer supports the aggregated management and control of various types of user-side distributed energy storage facilities. Among them, "distributed photovoltaics + energy storage" refers to the energy storage facilities configured as required during the construction of distributed photovoltaics, which operate jointly with distributed photovoltaics; "distribution network-side energy storage" refers to energy storage facilities funded and built by power companies and installed in locations such as transformers and substations; "user-side independent energy storage" refers to independently operated energy storage facilities installed within the user.

[0181] The access layer supports user-side distributed energy storage facilities to access the aggregation management and control system through the public network or private network, and supports multiple access methods:

[0182] Method 1: System-level interconnection access

[0183] Applicable to energy storage facilities that have been connected to the user or energy enterprise's self-built management system. The aggregated management and control system provides a data interface, and the self-built management system communicates with the aggregated management and control system through the public network, enabling user-side distributed energy storage facility access.

[0184] Method 2: Intelligent integrated terminal access in the substation area

[0185] It is suitable for the access of various distributed energy storage facilities on the user side. The energy storage facilities are connected to the substation intelligent fusion terminal through various communication protocols such as 104 protocol, HTTP, Modbus, etc. The substation intelligent fusion terminal aggregates the information and communicates with the application layer through the power dedicated network.

[0186] Method 3: Dedicated collection terminal access

[0187] It is suitable for access to various types of distributed energy storage facilities on the user side. A dedicated acquisition terminal is installed on the distributed energy storage facilities on the user side. The dedicated acquisition terminal communicates with the application layer through the public network to achieve access to various types of distributed energy storage facilities on the user side.

[0188] The access layer, the user-side distributed energy storage facilities and the aggregated management and control system realize information communication through the access layer, including: uploading the state of charge (SOC), charging and discharging power, charging and discharging capacity, maximum allowed charging and discharging power, adjustable increase / decrease charging and discharging power, chargeable capacity, dischargeable capacity, etc. of the energy storage facilities, and receiving control instructions such as charging and discharging status and charging and discharging power issued by the aggregated management and control system.

[0189] The application layer monitors and analyzes the operation of connected distributed energy storage facilities based on the distributed energy storage data model, including but not limited to energy storage aggregation monitoring, operational statistical analysis, and active power coordinated control. Based on aggregation management and control methods, distributed energy storage facilities are clustered and, based on requirements such as frequency regulation, peak regulation, and demand response, power and electricity regulation targets are decomposed to enable distributed energy storage aggregation to participate in source-grid-load-storage interaction, power ancillary services, and demand response applications.

[0190] Energy storage aggregation monitoring: Real-time monitoring of the operating status of various distributed energy storage facilities, including facility operating status (charging / discharging / standby / shutdown / fault, etc.), charging / discharging power, charging and discharging amount, battery SOC, etc.

[0191] Operational statistical analysis: Statistical analysis of the operation status of various distributed energy storage facilities is realized, including energy storage charging and discharging power, charging and discharging capacity, charging and discharging cycle efficiency, facility utilization rate, equivalent cycle coefficient, etc.

[0192] Active power coordinated control: Based on the real-time operating status of the distribution network, new energy power forecasts, load forecasts, etc., and subject to the constraints of system operation, the active power output of distributed energy storage facilities is optimized and adjusted to achieve economical operation of the distribution network.

[0193] Interaction between source, grid, load and storage: responds to control instructions from the marketing / dispatching master station, interacts with distributed photovoltaics and various power loads in the region, and supports the safe and stable operation of the distribution network and the absorption of clean energy.

[0194] Power auxiliary services: Aggregate various types of distributed energy storage on the user side, analyze and evaluate the power regulation capabilities after aggregation, participate in power peak regulation services, and optimize and decompose the planned output curve to each energy storage facility.

[0195] Demand response: Aggregate various types of distributed energy storage on the user side to form a regulation resource library, carry out grid demand response invitations, analyze and evaluate response capabilities such as power and electricity, and participate in power demand response.

[0196] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0197] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0198] The present application is described with reference to the flowcharts and / or block diagrams of the methods, facilities (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing facility to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing facility generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0199] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing facility to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device that implements the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0200] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process described in the flowchart. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0201] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A method for aggregated management and control of distributed energy storage facilities on the user side, characterized in that: include: Obtain information on all connected distributed energy storage facilities and grid interaction targets for each application scenario; Analyze the characteristics of the information of each distributed energy storage facility to obtain the regulation status of each distributed energy storage facility in each application scenario; Based on the regulation status of all distributed energy storage facilities, all distributed energy storage facilities are aggregated to obtain the regulation capacity of each distributed energy storage category in each application scenario; Generate regulation instructions for controlling each energy storage facility category based on the grid interaction goals of each application scenario and the regulation capabilities of each distributed energy storage category; The regulation capability of each distributed energy storage category in each application scenario is obtained by aggregating all distributed energy storage facilities based on their regulation conditions, including: Constructing a clustering feature set based on all distributed energy storage facilities, information about the distributed energy storage facilities, and a clustering indicator set set for each application scenario; Based on the cluster feature set, the distance between any two distributed energy storage facilities in the cluster feature set is calculated to construct a proximity matrix: Based on the proximity matrix, clustering the distributed energy storage facilities using K-MEANS, and determining the regulation capacity of each distributed energy storage category; The regulation capability includes: power regulation capability, power regulation capability and regulation response time; The application scenarios include at least one or more of the following: participating in grid frequency regulation, participating in grid peak regulation, and participating in demand response; The clustering feature set is constructed based on all distributed energy storage facilities, information about the distributed energy storage facilities, and a clustering indicator set set for each application scenario, including: Build a facility collection based on all connected distributed energy storage facilities: Based on the information and regulation status of all connected distributed energy storage facilities, a set of energy storage facility clustering characteristic indicators is constructed: constructing an initial set based on the facility set and the indicator set; A clustering feature set is constructed based on the clustering indicator set and the initial set set for each application scenario.

2. The method according to claim 1, wherein The adjustment conditions of each distributed energy storage facility include: maximum adjustable power increase, maximum adjustable power decrease and adjustment time.

3. The method according to claim 2, wherein The maximum adjustable power increase is calculated as follows: ΔP adj,up =P d,max -P curr Where ΔP adj,up P is the maximum adjustable power increase of the energy storage facility; d,max is the maximum discharge power of the energy storage facility; P curr is the current power of the energy storage facility; The maximum adjustable power reduction is calculated as follows: ΔP adj,down =P c,max -P curr Where ΔP adj,down P is the maximum adjustable power reduction of the energy storage facility; c,max is the maximum discharge power of the energy storage facility; P curr is the current power of the energy storage facility; The adjustment time is calculated as follows: Where, T adj The adjustment time corresponding to the power ΔP of the energy storage facility; ΔP is the regulated power; Q spe is the rated capacity of energy storage; SOC is the state of charge; P curr is the current power of the energy storage facility; P d,max is the maximum allowable discharge power of the energy storage facility; P c,max The maximum allowable charging power of the energy storage facility.

4. The method according to claim 3, wherein The adjustment range of the adjustment power is determined by the following formula: ΔP adj,down ≤ΔP≤ΔP adj,up Where ΔP adj,down is the maximum adjustable power reduction of the energy storage facility; ΔP adj,up Increase the maximum adjustable power of energy storage facilities.

5. The method according to claim 1, wherein The clustering feature set is as follows: Where M is the clustering feature set; AS is the initial set; IN is the clustering feature index set; ST i is the i-th distributed energy storage facility, CT i is the i-th clustering feature index; M l is the characteristic value of the lth distributed energy storage facility; v ij is the value of the jth characteristic index of the i-th distributed energy storage facility; IN k is the parameter of the kth characteristic indicator; n is the number of aggregated energy storage facilities, and m is the number of clustering characteristic indicators.

6. The method according to claim 1, wherein The power regulation capacity of each distributed energy storage category is calculated as follows: Where ΔP ass,i is the power regulation capability of the i-th category; ΔP j is the adjustable power implemented by the jth distributed energy storage in this category; o is the number of distributed energy storage facilities in this category; The power regulation capability of each distributed energy storage category is calculated as follows: Where ΔQ ass,i is the power regulation capability of the i-th category; ΔQ j is the adjustable power of the jth distributed energy storage in this category; The regulation response time of each distributed energy storage type is calculated as follows: Where, t ass,i is the adjustment response time of the i-th category; t j is the regulation response time of the jth distributed energy storage implementation in this category.

7. The method according to claim 1, wherein The generation of regulation instructions for controlling each energy storage facility category based on the grid interaction goals of each application scenario and the regulation capabilities of each distributed energy storage category includes: Convert the grid interaction objectives of each application scenario into various regulation capabilities and set the maximum regulation response time; Determine an objective function with the goal of economic optimization, and set constraints for the objective function; Solving the objective function based on the respective regulation capabilities, maximum regulation response time and constraint conditions to obtain respective regulation capability values ​​of respective distributed energy storage categories; The adjustment capability values ​​of the distributed energy storage categories are used as control instructions for the distributed energy storage categories.

8. The method according to claim 7, wherein The objective function is as follows: f=min{c 1,i ×ΔP i +c 2,i ×ΔQ i } The constraints are as follows: Where c 1,i is the electricity regulation cost of the i-th category; c 2,i is the power regulation cost of the i-th category; ΔP i The regulation power provided for the i-th category; ΔQ i The amount of regulation provided for the i-th category; t i is the adjustment response time of the i-th category; n is the number of aggregated energy storage facilities; ΔP tar is the power regulation capacity requirement; ΔQ tar To meet the power regulation capability requirements.

9. The method according to claim 1, wherein The acquisition of information about all connected distributed energy storage facilities includes: Obtain information about each distributed energy storage facility based on a pre-built distributed energy storage data model; The distributed energy storage data model includes: basic information, control characteristics, operation information and regulation information; The basic information includes at least one or more of the following: facility type, energy storage medium, voltage level, rated capacity, rated power, commissioning date, owner and aggregator; The control characteristics include at least one or more of the following: whether controllable, charging response time, discharging response time, charging adjustment time, discharging adjustment time, charging to discharging conversion time and discharging to charging conversion time; The operation information includes at least one or more of the following: operation status, state of charge, charging power, discharging power, charging capacity and discharging capacity; The control information includes at least one or more of the following: a controlled state, a chargeable amount, a dischargeable amount, a maximum discharge power allowable value, a maximum charging power allowable value, a maximum discharge power available time, and a maximum charging power available time.

10. A user-side distributed energy storage facility aggregation management and control system, characterized in that: include: The access layer is used to obtain information about all connected distributed energy storage facilities and the grid interaction goals of each application scenario; The application layer is used to analyze the characteristics of the information of each distributed energy storage facility to obtain the regulation status of each distributed energy storage facility in each application scenario; based on the regulation status of all distributed energy storage facilities, all distributed energy storage facilities are aggregated to obtain the regulation capacity of each distributed energy storage category in each application scenario; Generate regulation instructions for controlling each energy storage facility category based on the grid interaction goals of each application scenario and the regulation capabilities of each distributed energy storage category; The regulation capability of each distributed energy storage category in each application scenario is obtained by aggregating all distributed energy storage facilities based on their regulation conditions, including: Constructing a clustering feature set based on all distributed energy storage facilities, information about the distributed energy storage facilities, and a clustering indicator set set for each application scenario; Based on the cluster feature set, the distance between any two distributed energy storage facilities in the cluster feature set is calculated to construct a proximity matrix: Based on the proximity matrix, clustering the distributed energy storage facilities using K-MEANS, and determining the regulation capacity of each distributed energy storage category; The regulation capability includes: power regulation capability, power regulation capability and regulation response time; The application scenarios include at least one or more of the following: participating in grid frequency regulation, participating in grid peak regulation, and participating in demand response; The clustering feature set is constructed based on all distributed energy storage facilities, information about the distributed energy storage facilities, and a clustering indicator set set for each application scenario, including: Build a facility collection based on all connected distributed energy storage facilities: Based on the information and regulation status of all connected distributed energy storage facilities, a set of energy storage facility clustering characteristic indicators is constructed: constructing an initial set based on the facility set and the indicator set; A clustering feature set is constructed based on the clustering indicator set and the initial set set for each application scenario.

11. The system according to claim 10, wherein: The system also includes a device layer; The equipment layer includes connected distributed energy storage facilities; The access layer is used to obtain information about all connected distributed energy storage facilities and grid interaction targets for each application scenario based on the device layer.

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