Method for evaluating capability of energy storage participating in frequency modulation auxiliary service of power system

Abstract

The invention provides a capability assessment method for participation of energy storage in power system frequency modulation auxiliary service, and belongs to the technical field of power system control. The problem of distributed resource frequency modulation capability evaluation in the existing electricity market is solved; comprising the following steps that an optimization model is constructed, and the optimization model comprises an objective function, uncertainty, constraint conditions and cost performance analysis; wherein the objective function is composed of two parts, the first part is frequency modulation income of a day-ahead maximized energy storage market subject in a time period t; the second part is intra-day scheduling; the uncertainty is used for declaring the price and capacity of the frequency modulation service based on the predicted frequency modulation demand and the bid winning price; the cost analysis is used for judging whether the expected revenue of the energy storage frequency modulation equipment participating in the frequency modulation service is cost-effective; solving the model; the method is applied to an electric power system containing energy storage.

Description

Technical Field

[0001] The present invention provides a method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services, belonging to the technical field of power system control. Background Art

[0002] In traditional power systems, frequency regulation services mainly rely on centralized generators, especially thermal power. These generators are able to adjust their output power according to the needs of the power grid to maintain the frequency stability of the power grid. However, with the large-scale access of renewable energy and the continuous development of the power market, the demand and challenges for frequency regulation services are also increasing. The intermittent and unpredictable nature of renewable energy such as wind and solar energy increases the complexity of power grid operation and places higher demands on frequency regulation services. In addition, the market-oriented reform of the power industry has made the providers of frequency regulation services no longer limited to traditional power generation companies, but expanded to market entities including virtual power plants and third-party independent operators.

[0003] The development of energy storage technology has provided new frequency regulation resources for power systems. Energy storage systems have become an indispensable frequency regulation resource in power systems due to their fast response and flexible regulation characteristics, helping the power grid to balance supply and demand and maintain stable and safe operation of the power grid. With the development of energy storage technology, its role in the power market has become increasingly important. However, it still faces a series of challenges in practical applications: (1) Frequency regulation capability assessment: Accurate assessment of the frequency regulation capability of energy storage systems is a prerequisite for their effective scheduling and control. At present, there is a lack of accurate methods to evaluate the frequency regulation performance of energy storage equipment, including its response speed, regulation depth and duration. (2) Real-time scheduling and control: Energy storage systems need to be scheduled and controlled according to real-time grid demand, which requires efficient algorithms and models to process real-time data and make quick decisions. (3) Cost-benefit analysis: The economic feasibility of energy storage frequency regulation services is the key to their commercialization. A detailed analysis of the operating costs and benefits of energy storage equipment is required to ensure their economic feasibility. (4) Market mechanism and policy support: The effective operation of energy storage frequency regulation services requires corresponding market mechanisms and policy support. At present, the electricity markets in many parts of the country have not yet been fully opened, and there is a lack of clear pricing mechanisms and incentive policies for energy storage and frequency regulation services. Summary of the invention

[0004] In order to solve the problem of evaluating the frequency regulation capability of distributed resources in the existing power market, the present invention proposes a method for evaluating the capability of energy storage to participate in the auxiliary frequency regulation service of the power system, and realizes the effective management and cost-effectiveness maximization of the frequency regulation service by constructing an optimization model.

[0005] The technical solution adopted by the present invention is: a method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services, comprising the following steps: Step 1: Construction of an optimization model, which includes an objective function, uncertainty, constraints, and cost-effectiveness analysis; The objective function consists of two parts. The first part is to maximize the energy storage market players in the period t The FM revenue during the period is t The second part is the intraday dispatch, which calculates the weighted value of the frequency regulation power cost under all possible values ​​according to the randomness of the AGC instructions, and minimizes the frequency regulation auxiliary service cost; The uncertainty is used to declare the price and capacity of frequency regulation services based on the predicted frequency regulation demand and the winning bid price; The constraints include frequency regulation instruction related constraints, declared capacity constraints, energy storage frequency regulation equipment power constraints, power balance constraints of electric energy storage frequency regulation equipment, and power correlation constraints between frequency regulation mileage and energy storage frequency regulation equipment; The cost-effectiveness analysis is used to determine whether the expected benefits of the energy storage frequency regulation equipment participating in the frequency regulation service are cost-effective; Step 2: Model solution: After obtaining the required parameters, the optimization method is used to solve the optimization model to obtain the final declaration decision of the energy storage market entity.

[0006] The expression of the objective function is as follows: ; Where: x is the set of decision variables, ; b t For energy storage market players in the period t The winning bid price for frequency regulation ancillary services; For energy storage market players in the period t The expected value of the total frequency regulation mileage, that is, the cumulative frequency regulation mileage of the energy storage market players based on the AGC instructions during this period; is the probability of the unit AGC command power value, in different time periods t The probability distribution of is also different; k Indicates time period t Sub-moment t’ Down No. k A value, Indicates during the period t Sub-moment t’ The AGC command value of the unit declared capacity; Q t For energy storage market players in the period t The declared capacity of frequency regulation auxiliary services; For energy storage frequency regulation equipment in the periodt Sub-moment t’ The operating power of t’ for duration; t’ is the AGC instruction dispatching time on the frequency modulation operation day, ; For the period t Sub-moment t’ Real-time electricity prices; T It is a collection of multiple FM time periods.

[0007] The uncertainty is expressed as the probability distribution of the FM power Describe, Indicates that during intraday dispatch, the power grid will allocate the energy storage market entities that have won the bid in the time period t Frequency regulation ancillary service capacity Q t Send AGC dispatch instructions, and the energy storage frequency modulation equipment needs to dynamically adjust the frequency modulation power To follow the AGC instructions.

[0008] The expressions of frequency modulation instruction related constraints are as follows: ; ; Δ is the maximum allowable deviation.

[0009] The expression for declaring capacity constraints is as follows: ; Q max The maximum capacity of energy storage frequency regulation equipment participating in frequency regulation auxiliary services.

[0010] The expression of power constraint of energy storage frequency regulation equipment is as follows: ; ; For energy storage frequency regulation equipment in the period t Sub-moment t’ Basic operating power; p max The maximum power allowed for energy storage and frequency regulation equipment.

[0011] The expression of the power balance constraint of the electric energy storage frequency regulation equipment is as follows: ; ; Where: For energy storage frequency regulation equipment in the period t The remaining energy, Et-1 is the residual energy of the previous period, Δ t’ for duration; E min , E max They are respectively the minimum and maximum capacity ranges allowed for energy storage and frequency regulation equipment.

[0012] The expression for the constraint of the relationship between frequency regulation mileage and the power of energy storage frequency regulation equipment is as follows: .

[0013] The expression of cost-effectiveness analysis is as follows: ; The sum on the left side of the formula represents the expected revenue of the energy storage frequency regulation equipment in all time periods, and the sum on the right side represents the charging and discharging operation costs calculated based on the real-time electricity price in all time periods; if the above inequality holds, the participation of the energy storage frequency regulation equipment in the frequency regulation service is economically viable.

[0014] In step 2, the mixed integer linear programming method is used to solve the objective function and constraints to obtain the optimal winning bid price and capacity as the final declaration decision of the energy storage market player.

[0015] The beneficial effects of the present invention compared to the prior art are as follows: through the method of the present invention, the participation strategies of market entities can be effectively evaluated and optimized, the frequency regulation efficiency and economy of the power system can be improved, while greater economic benefits can be brought to market entities, and a flexible declaration decision-making tool that complies with market operation rules can be provided for market entities. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below in conjunction with the accompanying drawings: Figure 1 is a flow chart of the method of the present invention; Figure 2 The figure is a flow chart for solving the optimization model of the present invention. DETAILED DESCRIPTION

[0017] like Figure 1-2 As shown, the present invention provides a method for evaluating the ability of energy storage to participate in the auxiliary frequency regulation service of the power system. By constructing an optimization model of energy storage market entities applicable to policy rules and frequency regulation auxiliary service market conditions in different regions, it is used to evaluate the frequency regulation capability of energy storage market entities in each frequency regulation period, and solve the frequency regulation quotation strategy for the corresponding period to maximize the benefits of energy storage market entities such as virtual power plants participating in the frequency regulation auxiliary service. The constructed optimization model can optimize the declaration of day-ahead frequency regulation services and the specific energy storage charging and discharging scheduling within the day.

[0018] The method specifically comprises the following steps: Step 1: Construction of the optimization model, which includes objective function, uncertainty, constraints and cost-effectiveness analysis, where: 1) Construct the objective function, which consists of two parts. The first part is to maximize the energy storage market players in the period t The first part is the frequency regulation revenue within a period, where the frequency regulation revenue is determined by the product of the winning bid price and the frequency regulation mileage (also known as the frequency regulation depth) during the period; the second part is the intraday scheduling, which calculates the weighted value of the frequency regulation power cost under all possible values ​​according to the randomness of the AGC instructions, and minimizes the frequency regulation ancillary service cost; the specific expression is as follows: (1); Where: x is the set of decision variables, ; b t For energy storage market players in the period t The winning bid price of the frequency regulation auxiliary service; according to the frequency regulation auxiliary service policy rules in different regions, if the unit wins the bid, the frequency regulation winning bid clearing price is calculated according to its declared price; in the present invention b t As a known variable, it is given by the energy storage market players based on historical clearing data and their own historical frequency regulation performance; For energy storage market players in the period t The expected value of the total frequency regulation mileage, that is, the cumulative frequency regulation mileage (also known as regulation depth) of the energy storage market players based on AGC instructions during this period; is the probability of the unit AGC command power value, in different time periods t The probability distribution of is also different; k Indicates time period t Sub-moment t’ Down No. k A value, Indicates time period t Sub-moment t’ The AGC command value of the unit declared capacity; For energy storage frequency regulation equipment in the period t Sub-moment t’ The operating power of t’ is the duration, which may be minutes or seconds; t’ The AGC command scheduling time of the frequency modulation operation day, in minutes or seconds. ; For the period t Sub-momentt’ The real-time electricity price is the real-time peak, flat and valley electricity price of the electricity market on that day; T It is a collection of multiple frequency modulation time periods, which can be specifically divided into five, six or other frequency modulation time periods according to the frequency modulation auxiliary service policy rules in different regions.

[0019] The energy storage market entity refers to an operator, which may be an independent energy storage power station, a virtual power plant operator, a power sales company, etc.; the energy storage frequency regulation equipment is a specific energy storage entity equipment. When participating in the electricity market, the declaration and clearing process is based on the entity as the unit; in actual dispatch, it is based on the equipment as the unit.

[0020] 2) Uncertainty Construction The energy storage system needs to declare the price and capacity of frequency regulation services based on the predicted frequency regulation demand and the winning bid price. Given the uncertainty of AGC instructions, probability distribution is used to describe them.

[0021] set up AGC t,t’ For the period t Sub-moment t’ The AGC instruction, For the period t Sub-moment t’ The AGC instruction value of the unit declared capacity is the value of the AGC instruction that the energy storage market entity needs to follow for each unit declared capacity. In other words, the power grid will follow the capacity declared by the energy storage market entity. Q t To determine the amount of AGC instructions that each unit capacity needs to respond to. is a random variable with a probability distribution During the day's dispatch, the power grid will allocate the capacity based on the capacity declared by the energy storage market entity that won the bid. Q t Issue AGC (Automatic Generation Control) dispatch instructions, and the winning energy storage frequency modulation equipment needs to dynamically adjust the frequency modulation power To follow the AGC instruction, it is expressed as .

[0022] 3) Constraints: including frequency regulation instruction-related constraints, declared capacity constraints, energy storage frequency regulation equipment power constraints, power balance constraints of electric energy storage frequency regulation equipment, and constraints on the relationship between frequency regulation mileage and power of energy storage frequency regulation equipment. Specifically: The expressions of frequency modulation instruction related constraints are as follows: (2-1); (2-2); Formula (2-1) represents the frequency modulation instruction AGC t,t’Dependency on the optimization variable of the timeframe Q t ; Formula (2-2) indicates that the frequency modulation power of the energy storage device is ensured at any time are as close to the AGC instructions as possible. is the corresponding frequency modulation power; Δ is the maximum allowable deviation value.

[0023] The expression for declaring capacity constraints is as follows: (3); Formula (3) indicates that energy storage frequency regulation equipment must declare the frequency regulation capacity it is willing to provide in each period of the day-ahead market; Q t For energy storage market players in the period t The declared capacity of frequency regulation ancillary services (in MW); Q max The maximum capacity of energy storage frequency regulation equipment that can participate in frequency regulation ancillary services.

[0024] The expression of power constraint of energy storage frequency regulation equipment is as follows: (4-1); (4-2); Formula (4-1) indicates that the energy storage operating power consists of two parts: frequency regulation power and basic power (power reserved for energy storage); (4-2) indicates that the energy storage operating power needs to be within the equipment operating regulations. For energy storage frequency regulation equipment in the period t Sub-moment t’ The operating power, For energy storage frequency regulation equipment in the period t Sub-moment t’ FM power; For energy storage frequency regulation equipment in the period t Sub-moment t’ Basic operating power; p max The maximum power allowed for energy storage and frequency regulation equipment.

[0025] The expression of the power balance constraint of the electric energy storage frequency regulation equipment is as follows: (5-1); (5-2); Where: For energy storage frequency regulation equipment in the period t The remaining energy, E t-1 is the residual energy of the previous period, Δ t’ for duration; Emin , E max They are respectively the minimum and maximum capacity ranges allowed for energy storage and frequency modulation equipment, to avoid excessive charging and discharging that may affect the service life of the equipment.

[0026] The expression for the constraint of the relationship between frequency regulation mileage and the power of energy storage frequency regulation equipment is as follows: (6-1); Formula (6-1) is the power correlation constraint between frequency regulation mileage and energy storage frequency regulation equipment, ensuring the period t Total FM mileage expectation R t Equal to the cumulative amount of frequency modulation power at all sub-times in this period. Linearize equation (6-1) and introduce auxiliary variables p + , p - , so that: (6-2); Then there are constraints: (6-3); (6-4); (6-5); The original formula (6-1) is transformed into: (6-6); in: p + Indicates time period t Sub-moment t’ Under, positive deviation of FM power; p - Indicates time period t Sub-moment t’ Under, the negative deviation of FM power; z t,t’ is a binary variable, indicating the t Sub-moment t’ Whether to select positive deviation ( z t,t’ =1 indicates positive deviation, z t,t’ =0 for negative deviation); M is a large enough positive number to ensure that z t,t’ =1 p + Can take any non-negative value. z t,t’ =0 p +=0; Formula (6-3) and Formula (6-4) ensure that at any time p + and p - cannot be non-zero at the same time; constraint (6-5) means p + and p - The sum is equal to the FM power The absolute value of .

[0027] 4) The expression for cost-effectiveness analysis is as follows: (7); If the expected revenue is greater than or equal to the cost, then participating in the frequency regulation service is economical; the sum on the left side of formula (7) represents the expected revenue of the energy storage frequency regulation equipment in all time periods, and the sum on the right side represents the charging and discharging operation cost calculated according to the real-time electricity price in all time periods. If formula (7) holds, then participating in the frequency regulation service of the energy storage frequency regulation equipment is economically viable.

[0028] Step 2: Model solving, including parameter acquisition and optimization methods.

[0029] 1. Parameter acquisition instructions: b t It is derived by energy storage market players based on historical clearing data and their own historical frequency regulation performance; The day-ahead stage is obtained through prediction and other methods; T Obtained according to the frequency modulation auxiliary service policy rules in different regions; Q max Parameters of energy storage frequency modulation equipment; Δ t’ The actual time may be minutes or seconds; t’ is minutes or seconds; p max Obtained from the operating parameter plate of the energy storage frequency regulation equipment; Issued by the power grid; Obtained by fitting and statistics of historical data.

[0030] 2. Optimization method Based on the actual rules of the frequency regulation auxiliary service market in different regions, each energy storage market player completes the declaration and clearance on the day before, and must strictly follow the AGC instructions during the day. The optimization model of the present invention uses an expected value model-based method for optimization. Ensure that the frequency regulation capability is retained at all times through equipment constraints to ensure that there is sufficient frequency regulation power and SOC backup space outside the equipment power baseline. SOC (State of Charge) refers to the state of charge of the battery, also known as the remaining power.

[0031] like Figure 2 As shown, the specific solution process is as follows: Start; parameter acquisition: collect all necessary parameters, including frequency regulation period, quotation range, electricity price, equipment power limit, etc.; initialization: determine the initial winning bid price and declared capacity of the energy storage market entity; the optimization goal is to maximize the expected return; mixed integer linear programming solution: use the mixed integer linear programming method to solve the objective function and constraints to obtain the optimal winning bid price and capacity; output the optimal winning bid price and capacity: obtain the optimal winning bid price and capacity as the final declaration decision of the energy storage market entity; end.

[0032] The present invention aims to effectively evaluate and optimize the frequency regulation capability of energy storage market players by constructing an optimization model, and improve the frequency regulation efficiency and economy of the power system. Through the method of the present invention, a flexible and market-compliant declaration decision-making tool is provided for energy storage market players, while providing technical support for the development of the power market.

[0033] 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 with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services, characterized by: The following steps are involved: Step 1: Construction of an optimization model, which includes an objective function, uncertainty, constraints, and cost-effectiveness analysis; The objective function consists of two parts. The first part is to maximize the energy storage market players in the period t The FM revenue during the period is t The second part is the intraday dispatch, which calculates the weighted value of the frequency regulation power cost under all possible values ​​according to the randomness of the AGC instructions, and minimizes the frequency regulation auxiliary service cost; The uncertainty is used to declare the price and capacity of frequency regulation services based on the predicted frequency regulation demand and the winning bid price; The constraints include frequency regulation instruction related constraints, declared capacity constraints, energy storage frequency regulation equipment power constraints, power balance constraints of electric energy storage frequency regulation equipment, and power correlation constraints between frequency regulation mileage and energy storage frequency regulation equipment; The cost-effectiveness analysis is used to determine whether the expected benefits of the energy storage frequency regulation equipment participating in the frequency regulation service are cost-effective; Step 2: Model solution: After obtaining the required parameters, the optimization method is used to solve the optimization model to obtain the final declaration decision of the energy storage market entity.

2. A method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 1, characterized in that: The expression of the objective function is as follows: ； Where: x is the set of decision variables, ; b t For energy storage market players in the period t The winning bid price for frequency regulation ancillary services; For energy storage market players in the period t The expected value of the total frequency regulation mileage, that is, the cumulative frequency regulation mileage of the energy storage market players based on the AGC instructions during this period; is the probability of the unit AGC command power value, in different time periods t The probability distribution of is also different; k Indicates time period t Sub-moment t’ Down No. k A value, Indicates during the period t Sub-moment t’ The AGC command value of the unit declared capacity; Q t For energy storage market players in the period t The declared capacity of frequency regulation auxiliary services; For energy storage frequency regulation equipment in the period t Sub-moment t’ The operating power of t’ for duration; t’ is the AGC instruction dispatching time on the frequency modulation operation day, ; For the period t Sub-moment t’ Real-time electricity prices; T It is a collection of multiple FM time periods.

3. The method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 2, characterized in that: The uncertainty is expressed as the probability distribution of the FM power Describe, Indicates that during intraday dispatch, the power grid will allocate energy storage market entities in the time period according to the winning bid. t Frequency regulation ancillary service capacity Q t Send AGC dispatch instructions, and the energy storage frequency modulation equipment needs to dynamically adjust the frequency modulation power To follow the AGC instructions.

4. The method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 3, characterized in that: The expressions of frequency modulation instruction related constraints are as follows: ； ； Δ is the maximum allowable deviation.

5. The method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 3 is characterized by: The expression for declaring capacity constraints is as follows: ； Q max The maximum capacity of energy storage frequency regulation equipment participating in frequency regulation auxiliary services.

6. The method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 3, characterized in that: The expression of the power constraint of energy storage frequency regulation equipment is as follows: ； ； For energy storage frequency regulation equipment in the period t Sub-moment t’ Basic operating power; p max The maximum power allowed for energy storage and frequency regulation equipment.

7. The method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 3, characterized in that: The expression of the power balance constraint of the electric energy storage frequency regulation equipment is as follows: ； ； Where: For energy storage frequency regulation equipment in the period t The remaining energy, E t-1 is the residual energy of the previous period, Δ t’ for duration; E min , E max They are respectively the minimum and maximum capacity ranges allowed for energy storage and frequency regulation equipment.

8. The method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 3, characterized in that: The expression for the constraint of the relationship between frequency regulation mileage and the power of energy storage frequency regulation equipment is as follows: 。 9. A method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to any one of claims 4 to 8, characterized in that: The expression of cost-effectiveness analysis is as follows: ； The sum on the left side of the formula represents the expected revenue of the energy storage frequency regulation equipment in all time periods, and the sum on the right side represents the charging and discharging operation costs calculated based on the real-time electricity price in all time periods; if the above inequality holds, the participation of the energy storage frequency regulation equipment in the frequency regulation service is economically viable.

10. A method for evaluating the ability of energy storage to participate in power system frequency regulation auxiliary services according to claim 9, characterized in that: In step 2, the mixed integer linear programming method is used to solve the objective function and constraints to obtain the optimal bidding price and capacity as the final declaration decision of the energy storage market player.

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