New energy power transaction method based on multi-demand scheduling collaborative optimization

Abstract

The invention relates to the field of power transaction, in particular to a new energy power transaction method based on multi-demand scheduling collaborative optimization, and the method comprises the steps: S1, obtaining charging basic information data which comprises the required charging power and the required charging amount, and obtaining the required charging duration; s2, forming a day-ahead scheduling model according to the operation cost of the conventional unit and the operation cost of the new energy unit; s3, forming an intra-day scheduling model according to the power balance constraint and the operation constraint of the conventional unit and the new energy unit; and S4, according to the day-ahead scheduling model and the intra-day scheduling model, orderly power supply is realized, differentiated value-added services are provided for the users, and the user stickiness of the demand side is increased. The method has the advantages that the regulation and control plan of the new energy demand side resources can be formulated with the optimal operation economy as the target, and the renewable energy consumption capacity and the power distribution active response capacity of the new energy main network are improved.

Description

[Technical field]

[0001] The present invention relates to the field of power trading, and in particular to a new energy power trading method based on multi-demand scheduling collaborative optimization. [Background technology]

[0002] With the rapid development of new energy, the demand for accurate power supply is increasing, such as the demand side flexible load resource problem of new energy electric vehicles, such as the temperature control load of the battery itself, and the driver's consideration of charging for the time-of-use electricity price difference. The battery will heat up after long-term use, resulting in changes in electricity consumption. At the same time, the electricity demand in the day-ahead stage and the intraday stage is also very different.

[0003] Therefore, a new energy power trading method based on multi-demand scheduling collaborative optimization is proposed, which meets the power load demand by operating and regulating the resource pool, thereby improving the stability of the power supply system and the economy of users' electricity use.

[0004] In addition, electricity is dispatched in a graded manner based on time factors. For example, in the day-ahead stage, the price difference between optimized charging of electric vehicles and energy storage charging piles is taken into consideration to establish a day-ahead dispatching model with the goal of optimizing operating economy. In the intraday stage, the power system backup cost and temperature control load constraints are taken into consideration to establish an intraday dispatching model with the goal of optimizing operating economy. [Summary of the invention]

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the existing technology and provide a new energy power trading method based on multi-demand scheduling collaborative optimization, which can formulate a regulation plan for new energy demand-side resources with the goal of optimizing operating economy, and improve the new energy main grid's ability to absorb renewable energy and the active response capability of distribution.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A new energy power trading method based on multi-demand scheduling collaborative optimization is used for a new energy vehicle power trading method, comprising the following steps:

[0008] S1: Obtain basic charging information data, which includes the required charging power and the required charging amount, and obtain the required charging time;

[0009] S2: Based on the operating costs of conventional units and new energy units, a day-ahead dispatch model is formed;

[0010] S3: Form an intraday dispatch model based on power balance constraints and the operating constraints of conventional units and new energy units;

[0011] S4: Based on the day-ahead dispatch model and the intraday dispatch model, orderly power supply is achieved, and differentiated value-added services are provided to users to increase user stickiness on the demand side.

[0012] As the preferred method, day-ahead scheduling is used to formulate a 24-hour scheduling plan based on the day-ahead forecast value of the baseline load, which requires determining the start-stop status and output of conventional units, the charging demand of new energy vehicles, and the scheduling capacity of energy storage equipment;

[0013] Intraday scheduling is used to adjust the cycle in a rolling manner according to load forecasts, which requires determining the operating strategies of conventional units, temperature control loads, and new energy units.

[0014] As a preferred option, the calculation formula of the day-ahead scheduling model is as follows:

[0015]

[0016] Where: T is the running time, is the operating cost of conventional units, is the operating cost of the new energy unit, is the operating cost per unit of processing of conventional units, is the operating power processed by the conventional unit g, z t,g Normal unit startup state, y t,g In the normal unit shutdown state, Sdc g For conventional units, Suc g is the shutdown cost of conventional unit g, P t desa is the startup cost of the new energy unit, P t eva is the shutdown cost of new energy units, is the impact factor.

[0017] As a preferred option, the intraday scheduling model calculation formula is as follows:

[0018]

[0019] Where: T is the running time, is the power balance constraint, is the unit operation constraint, λ DRAE,da is the operation impact factor, P t desa is the unit startup power, P t eva The shutdown power of the unit. is the average power of the unit during the period, P t desa is the power when the machine is turned on at time t, is the average shutdown power of the unit during the cycle, Pt eva is the average shutdown power at time t, is the power impact factor.

[0020] The new energy power trading platform mentioned above includes:

[0021] An acquisition module is used to acquire basic charging information data including the required charging power and the required charging amount, and obtain the required charging time;

[0022] The day-ahead dispatch module is used to dispatch electricity based on the operating costs of conventional units and new energy units;

[0023] Intraday dispatch module, used to dispatch electricity according to power balance constraints and operation constraints of conventional units and new energy units;

[0024] The energy efficiency optimization service module is used to achieve orderly power supply based on the day-ahead scheduling model and the intraday scheduling model, and to provide users with differentiated value-added services to increase user stickiness on the demand side.

[0025] As a preference, it also includes an incentive-type demand-side resource aggregation module, and the calculation formula of the incentive-type demand-side resource aggregation module is as follows:

[0026]

[0027] Where: is the actual load demand power of demand-side user j in response to the incentive-based demand response project during period t: J is the set of demand-side users who respond to the incentive-based demand response project.

[0028] As a preferred embodiment, a price-based demand-side resource aggregation model is also included, and the calculation formula of the price-based demand-side resource aggregation module is as follows:

[0029]

[0030] Where: is the actual load demand power of the demand-side user j who responds to the price-based demand response project during the period; I is the set of demand-side users who respond to the price-based demand response.

[0031] As a preferred option, an energy efficiency optimization service contract is also included, and the energy efficiency optimization service contract includes:

[0032] The power consumption monitoring contract is used to monitor whether the daily scheduling module needs to perform energy efficiency optimization services based on the equipment quantity and power generation of the daily scheduling module;

[0033] Energy efficiency optimization vendor matching contract, used to match the energy efficiency optimization service module that issues a transaction request with the equipment manufacturer of the intraday scheduling module that needs energy efficiency optimization service;

[0034] The energy efficiency optimization equipment quantity matching contract is used to match the energy efficiency optimization service module that issues a transaction request with the energy efficiency optimization equipment quantity of the intraday scheduling module that needs to perform equipment energy efficiency optimization services;

[0035] The energy efficiency optimization price matching contract is used to select the energy efficiency optimization service module with the lowest price as the transaction object that successfully matches the intraday scheduling module among the energy efficiency optimization service modules that successfully match the equipment manufacturers and energy efficiency optimization equipment quantities of the intraday scheduling module.

[0036] The beneficial effects of the present invention are as follows:

[0037] 1. Since it takes a long time to start and stop conventional units and the release of the day-ahead time-of-use electricity price will affect the operating status of the intraday load, the start and stop status of conventional units is determined in the day-ahead dispatch and cannot be changed in the intraday dispatch. Under the same load demand, the more dispatch output of new energy units, the less output of conventional units, and the optimal system operation economy.

[0038] 2. Load resources that respond to the market price signals issued by the demand-side resource aggregation response subject also refer to load resources that respond to price-based demand response projects. The goal of the energy market-based demand response mechanism is to use market prices that reflect the potential power operation and production costs to guide end-users on the demand side to change their electricity consumption behavior, so that end users bear the corresponding price costs, in order to achieve effective allocation of demand-side resources.

[0039] 3. During the operation of the resource aggregation response subject, the present invention will collect massive flexible load electricity consumption data and equipment operation data, and at the same time collect demand information data from power grid dispatching and the power market. Through data mining, this information can establish the sensitivity of demand-side users to electricity prices, the responsiveness of flexible loads to power grid dispatching, and the attractiveness of users to response subsidy rewards.

[0040] These features and advantages of the present invention will be disclosed in detail in the following specific embodiments and drawings.

Brief Description of the Drawings

[0041] The present invention will be further described below in conjunction with the accompanying drawings:

[0042] Figure 1 This is a flow chart of Embodiment 1 of the present invention. [Specific implementation method]

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] The following first describes the concepts involved in this application in conjunction with the accompanying drawings. It should be noted that the following description of each concept is only to make the content of this application easier to understand and does not limit the scope of protection of this application.

[0045] Embodiment 1:

[0046] A new energy power trading method based on multi-demand scheduling collaborative optimization is used for the power trading method of new energy vehicles, such as Figure 1 As shown, the following steps are included:

[0047] S1: Obtain basic charging information data, which includes the required charging power and the required charging amount, and obtain the required charging time;

[0048] S2: Based on the operating costs of conventional units and new energy units, a day-ahead dispatch model is formed;

[0049] S3: Form an intraday dispatch model based on power balance constraints and the operating constraints of conventional units and new energy units;

[0050] S4: Based on the day-ahead dispatch model and the intraday dispatch model, orderly power supply is achieved, and differentiated value-added services are provided to users to increase user stickiness on the demand side.

[0051] Day-ahead scheduling is used to formulate a 24-hour scheduling plan based on the day-ahead forecast value of the baseline load. It is necessary to determine the start and stop status and output of conventional units, the charging demand power of new energy vehicles, and the scheduling capacity of energy storage equipment. For example, to formulate a 24-hour scheduling plan, confirm that T is 24.

[0052] The calculation formula of the day-ahead scheduling model is as follows:

[0053]

[0054] Where: T is the running time, is the operating cost of conventional units, is the operating cost of the new energy unit, is the operating cost per unit of processing of conventional units, is the operating power processed by the conventional unit g, z t,g Normal unit startup state, y t,gIn the normal unit shutdown state, Sdc g For conventional units, Suc g is the shutdown cost of conventional unit g, P t desa is the startup cost of the new energy unit, P t eva is the shutdown cost of new energy units, is the unit influencing factor.

[0055] Since it takes a long time to start and stop conventional units and the day-ahead time-of-use electricity price will affect the operating status of the daily load after it is released, the start and stop status of conventional units is determined in the day-ahead scheduling and cannot be changed in the day-ahead scheduling. The power generation cost of new energy units is relatively small compared to conventional units, and its cost is ignored in this invention.

[0056] Under the condition of the same load demand, the more the dispatched output of new energy units is, the less the output of conventional units is, and the system operation economy is optimal.

[0057] The reserve capacity required for system operation is determined by the error in the load forecast value, and plans are made separately for day-ahead and day-intraday dispatching.

[0058] Day-ahead dispatch is to formulate a dispatch plan for the next 24 hours based on the day-ahead forecast value of the baseline load, which requires determining the start and stop status and output of conventional units, the charging strategy of electric vehicles, and the dispatch capacity of distributed energy storage.

[0059] Since conventional units have a long start-up and shutdown time, they cannot be modified in the intraday rolling plan after being determined in the day-ahead plan. Distributed energy storage has the characteristics of fast response, flexible control, and bidirectional charging and discharging power. In the day-ahead scheduling, in addition to determining the charging and discharging power, a certain amount of spare capacity needs to be reserved to participate in the intraday rolling scheduling to undertake rotating reserve and earn income.

[0060] Intraday scheduling is used to adjust the cycle in a rolling manner according to load forecasts, which requires determining the operating strategies of conventional units, temperature control loads, and new energy units.

[0061] The calculation formula of the intraday scheduling model is as follows. The intraday rolling scheduling cycle can be 4 hours, with rolling updates every 1 hour, and each scheduling period is 15 minutes, so T = 4 hours / 15 minutes = 16:

[0062]

[0063] Where: T is the running time, is the power balance constraint, is the unit operation constraint, λ DRAE,da is the operation impact factor, P t desa is the unit startup power, Pt eva The shutdown power of the unit. is the average power of the unit during the period, P t desa is the power when the machine is turned on at time t, is the average shutdown power of the unit during the cycle, P t eva is the average shutdown power at time t, is the power impact factor.

[0064] In daily operation, most electric vehicles are in a parked state. Through orderly management of electric vehicle charging, an optimized charging strategy can be formulated under the constraints of operating conditions.

[0065] Intraday scheduling is based on ultra-short-term output forecasts and load forecasts with a rolling adjustment cycle of 4 hours to determine the output of conventional units, the interruption strategy of temperature-controlled loads, the operation strategy of distributed energy storage, and the output plan of new energy units.

[0066] Since the temperature control load has a quick response and recovery time, and in consideration of the user experience, in the collaborative scheduling strategy proposed in the present invention, the temperature control load only participates in intraday scheduling, and the system backup constraint is guaranteed by the last level of scheduling of the system.

[0067] The above-mentioned new energy power trading platform includes:

[0068] An acquisition module is used to acquire basic charging information data including the required charging power and the required charging amount, and obtain the required charging time;

[0069] The day-ahead dispatch module is used to dispatch electricity based on the operating costs of conventional units and new energy units;

[0070] Intraday dispatch module, used to dispatch electricity according to power balance constraints and operation constraints of conventional units and new energy units;

[0071] The energy efficiency optimization service module is used to achieve orderly power supply based on the day-ahead scheduling model and the intraday scheduling model, and to provide users with differentiated value-added services to increase user stickiness on the demand side.

[0072] It also includes an incentive-type demand-side resource aggregation module, and the calculation formula of the incentive-type demand-side resource aggregation module is as follows:

[0073]

[0074] Where: is the actual load demand power of demand-side user j in response to the incentive-based demand response project during period t: J is the set of demand-side users who respond to the incentive-based demand response project.

[0075] When the stability of the power system is threatened, the power system operator uses subsidy measures to send incentive signals to demand-side users. Demand-side users who are qualified and willing to accept this signal respond and actively change their own electricity demand behavior.

[0076] It also includes a price-based demand-side resource aggregation module, and the calculation formula of the price-based demand-side resource aggregation module is as follows:

[0077]

[0078] Where: is the actual load demand power of the demand-side user j who responds to the price-based demand response project during the period; I is the set of demand-side users who respond to the price-based demand response.

[0079] The load resources that respond to the market price signals issued by the demand-side resource aggregation response subject also refer to the load resources that respond to the price-based demand response project. The goal of the electric energy market-based demand response mechanism is to use the market price that reflects the potential power operation and production costs to guide the end-users on the demand side to change their electricity consumption behavior, so that the end-users bear the corresponding price costs, so as to achieve the effective allocation of demand-side resources.

[0080] During the operation of the resource aggregation response subject, the present invention will collect massive flexible load electricity consumption data and equipment operation data, and at the same time collect demand information data from power grid dispatching and the power market. Through data mining, this information can establish the sensitivity of demand-side users to electricity prices, the responsiveness of flexible loads to power grid dispatching, and the attractiveness of users to response subsidy rewards.

[0081] Through continuous trajectory correction, it will provide strong support for grid dispatching decisions and power market transactions;

[0082] The present invention realizes the dynamic construction of an adjustable resource pool of a resource aggregation response subject. While providing services for power grid regulation and the electricity market, it should also use its own energy attributes to carry out auxiliary services, improve its own operating model, and expand its user base.

[0083] By providing personalized electricity services and practical reward mechanisms, users' electricity usage habits are changed, thereby achieving orderly electricity usage, and differentiated value-added services are provided to users to increase user stickiness on the demand side;

[0084] Preferably, it also includes an energy efficiency optimization service contract, which includes:

[0085] The power consumption monitoring contract is used to monitor whether the daily scheduling module needs to perform energy efficiency optimization services based on the equipment quantity and power generation of the daily scheduling module;

[0086] Energy efficiency optimization vendor matching contract, used to match the energy efficiency optimization service module that issues a transaction request with the equipment manufacturer of the intraday scheduling module that needs energy efficiency optimization service;

[0087] The energy efficiency optimization equipment quantity matching contract is used to match the energy efficiency optimization service module that issues a transaction request with the energy efficiency optimization equipment quantity of the intraday scheduling module that needs to perform equipment energy efficiency optimization services;

[0088] The energy efficiency optimization price matching contract is used to select the energy efficiency optimization service module with the lowest price as the transaction object that successfully matches the intraday scheduling module among the energy efficiency optimization service modules that successfully match the equipment manufacturers and energy efficiency optimization equipment quantities of the intraday scheduling module.

[0089] The power consumption monitoring contract is used to monitor whether the intraday scheduling module needs energy efficiency optimization services based on the equipment quantity and power generation of the intraday scheduling module. When the intraday scheduling module works with a fixed amount of equipment and reaches a certain power consumption, it is necessary to maintain and service the equipment in the intraday scheduling module to ensure its performance and usage time. Next, it is necessary to match it with a suitable energy efficiency optimization service module.

[0090] The manufacturer matching contract is used to match the energy efficiency optimization service module that issues a transaction request with the equipment manufacturer of the intraday scheduling module that needs energy efficiency optimization services. Since the energy efficiency optimization service module may not be able to provide energy efficiency optimization services for all equipment produced by all manufacturers, in order to ensure the effectiveness of the energy efficiency optimization service, manufacturer matching is required. When applying, the ability of the energy efficiency optimization service module needs to be verified.

[0091] The energy efficiency optimization equipment quantity matching contract is used to match the energy efficiency optimization service module that issues the transaction request with the energy efficiency optimization equipment quantity of the power generation module that needs the equipment energy efficiency optimization service; even if the manufacturer is matched, it is necessary to determine whether the energy efficiency optimization service module is capable of completing the energy efficiency optimization service of all equipment quantities within the set time, so as to improve work efficiency and avoid affecting the work of the intraday scheduling module;

[0092] The price matching contract is used to select the equipment operation and maintenance service module with the lowest price from the equipment operation and maintenance service modules that have successfully matched the equipment manufacturer and the quantity of energy efficiency optimization equipment in a certain intraday scheduling module as the transaction object that has successfully matched the intraday scheduling module. After the manufacturer and the quantity of equipment are matched, the price is used as the final selection condition to ensure the interests of the intraday scheduling module.

[0093] Those of ordinary skill in the art will appreciate that the units (or modules, steps, etc., the same below) of the examples described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0094] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0095] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0096] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nly Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc., which can store program code.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A new energy power trading method based on multi-demand scheduling collaborative optimization, used for a new energy vehicle power trading method, characterized in that: The following steps are involved: S1: Obtain basic charging information data, wherein the basic charging information data includes the required charging power and the required charging amount, and obtain the required charging time; S2: Based on the operating costs of conventional units and new energy units, a day-ahead dispatch model is formed; S3: Form an intraday dispatch model based on power balance constraints and the operating constraints of conventional units and new energy units; S4: Based on the day-ahead dispatch model and the intraday dispatch model, orderly power supply is achieved, and differentiated value-added services are provided to users to increase user stickiness on the demand side.

2. The new energy power trading method based on multi-demand scheduling collaborative optimization according to claim 1 is characterized in that: The day-ahead dispatch model is used to formulate a 24-hour dispatch plan based on the day-ahead forecast value of the baseline load, which requires determining the start / stop status and output of conventional units, the charging demand power of new energy vehicles, and the dispatch capacity of energy storage equipment; The intraday scheduling model is used to adjust the cycle in a rolling manner according to load forecast, which requires determining the conventional unit operation strategy, temperature control load, and new energy unit operation strategy.

3. The new energy power trading method based on multi-demand scheduling collaborative optimization according to claim 1 is characterized in that: The calculation formula of the day-ahead scheduling model is as follows: Where: T is the running time, is the operating cost of conventional units, is the operating cost of the new energy unit, is the operating cost per unit of processing of conventional units, is the operating power processed by the conventional unit g, z t,g Normal unit startup state, y t,g In the normal unit shutdown state, Sdc g For conventional units, Suc g is the shutdown cost of conventional unit g, P t desa is the startup cost of the new energy unit, P t eva is the shutdown cost of new energy units, is the impact factor.

4. The new energy power trading method based on multi-demand scheduling collaborative optimization according to claim 1 is characterized in that: The intraday scheduling model calculation formula is as follows: Where: T is the running time, is the power balance constraint, is the unit operation constraint, DRAE,da is the operation impact factor, P t desa is the unit startup power, P t eva The shutdown power of the unit. is the average power of the unit during the period, P t desa is the power when the machine is turned on at time t, is the average shutdown power of the unit during the cycle, P t eva is the average shutdown power at time t, is the power impact factor.

5. The new energy power trading platform according to claim 1, characterized in that: include: An acquisition module is used to acquire basic charging information data including the required charging power and the required charging amount, and obtain the required charging time; The day-ahead dispatch module is used to dispatch electricity based on the operating costs of conventional units and new energy units; Intraday dispatch module, used to dispatch electricity according to power balance constraints and operation constraints of conventional units and new energy units; The energy efficiency optimization service module is used to achieve orderly power supply based on the day-ahead scheduling model and the intraday scheduling model, and to provide users with differentiated value-added services to increase user stickiness on the demand side.

6. The new energy power trading method based on multi-demand scheduling collaborative optimization as claimed in claim 5 is characterized in that: It also includes an incentive-type demand-side resource aggregation module, and the calculation formula of the incentive-type demand-side resource aggregation module is as follows: Where: is the actual load demand power of demand-side user j in response to the incentive-based demand response project during period t: J is the set of demand-side users who respond to the incentive-based demand response project.

7. The new energy power trading method based on multi-demand scheduling collaborative optimization as claimed in claim 5 is characterized in that: It also includes a price-based demand-side resource aggregation module, and the calculation formula of the price-based demand-side resource aggregation module is as follows: Where: is the actual load demand power of the demand-side user j who responds to the price-based demand response project during the period; I is the set of demand-side users who respond to the price-based demand response.

8. The new energy power trading method based on multi-demand scheduling collaborative optimization as claimed in claim 5 is characterized in that: It also includes an energy efficiency optimization service contract, which includes: The power consumption monitoring contract is used to monitor whether the daily scheduling module needs to perform energy efficiency optimization services based on the equipment quantity and power generation of the daily scheduling module; Energy efficiency optimization vendor matching contract, used to match the energy efficiency optimization service module that issues a transaction request with the equipment manufacturer of the intraday scheduling module that needs energy efficiency optimization service; The energy efficiency optimization equipment quantity matching contract is used to match the energy efficiency optimization service module that issues a transaction request with the energy efficiency optimization equipment quantity of the intraday scheduling module that needs to perform equipment energy efficiency optimization services; The energy efficiency optimization price matching contract is used to select the energy efficiency optimization service module with the lowest price as the transaction object that successfully matches the intraday scheduling module among the energy efficiency optimization service modules that successfully match the equipment manufacturers and energy efficiency optimization equipment quantities of the intraday scheduling module.

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