Peak regulation and frequency modulation transaction decision-making method and system

Abstract

The invention discloses a peak regulation and frequency modulation transaction decision-making method and system, and relates to the technical field of peak regulation and frequency modulation application. S2, secondary frequency modulation; s3, constructing a state variable of battery energy storage; s4, the optimal frequency modulation price of battery energy storage is obtained; s5, constructing a decision variable of battery energy storage; s6, determining an objective function with maximized total revenue obtained by battery energy storage peak regulation and frequency modulation; and S7, calculating battery energy storage peak-load and frequency-modulation output. According to the method, the system frequency deviation is improved to a certain extent through primary frequency modulation, then zero-difference adjustment is achieved through secondary frequency modulation, namely, the system frequency is recovered and adjusted to a rated value, modeling is conducted on battery energy storage participating in power grid peak regulation and frequency modulation through a dynamic programming algorithm, and battery energy storage peak regulation and frequency modulation income maximization serves as the target. And the battery energy storage peak-load and frequency-modulation output is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of peak-shaving and frequency-modulation applications, and in particular to a peak-shaving and frequency-modulation transaction decision-making method and system. Background Art

[0002] In recent years, with the rapid growth of power load, the peak-to-valley difference of power grid load has gradually increased. At the same time, the large-scale grid connection of random, volatile and non-dispatchable renewable energy has made the peak-shaving problem of power grid more prominent, and also caused a series of difficulties for power dispatching. The power supply and transmission and distribution equipment in the power system are planned and constructed according to the peak load of the power grid, but the peak load of the power grid lasts for a short time, resulting in a low asset utilization rate of power equipment planned and constructed to meet the peak load demand. With the continuous expansion of the scale and capacity of power generation access in my country, it directly affects the peak-shaving capacity, frequency stability and economic and reliable operation of the power grid;

[0003] Battery energy storage is a good choice for participating in grid peak and frequency regulation due to its fast response speed and high control accuracy. However, due to the different time scales of peak and frequency regulation, in order to accurately allocate the output of battery energy storage participating in peak and frequency regulation, it is necessary to consider the optimization of different time scales of battery energy storage peak and frequency regulation. It is difficult to ensure the accuracy of battery energy storage tracking frequency regulation signals. If the system frequency stability cannot be maintained and the output of battery energy storage peak and frequency regulation cannot be reasonably allocated, the total benefits of battery energy storage peak and frequency regulation will be affected. Summary of the invention

[0004] The purpose of the present invention is to provide a peak-shaving and frequency-regulating transaction decision-making method and system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a peak-shaving and frequency-modulation transaction decision method, comprising the following steps:

[0006] S1. Primary frequency modulation: The frequency of the entire interconnected system is kept consistent through primary frequency modulation. A signal with a sampling period of 2 seconds is input to continuously monitor the system frequency. The frequency modulation signal source is selected according to the power generation control area, the regional control error is calculated, and multiple areas are controlled according to the regional control error. The regional control error is an indicator to measure the imbalance between load and power generation in the power system control area;

[0007] S2, secondary frequency regulation: When the power grid cannot restore the system frequency to the rated value after the primary frequency regulation, the secondary frequency regulation is carried out. By controlling the frequency regulator, the generator output is increased. When the load change is still greater than the output mechanical power of the generator, the generator output is continued to be increased so that the increase in the mechanical power output of the generator is just equal to the initial load change, reaching a new balance point, and realizing the error-free regulation of the secondary frequency regulation;

[0008] S3. Constructing the state variables of battery energy storage: Modeling the battery energy storage participating in the peak load and frequency regulation of the power grid through the dynamic programming algorithm, obtaining the basic parameters of the battery energy storage and the frequency regulation pricing of the power market, determining the initial and final charge states of the battery energy storage, and the basic parameters including the power of the battery energy storage in response to the frequency regulation signal, and constructing the battery energy storage state variable set together;

[0009] S4. Obtaining the optimal frequency regulation pricing for battery energy storage: Obtain the penetration rate of new energy in the power grid during the frequency regulation period to determine the target accuracy, and obtain the tracking accuracy based on the basic information of the battery energy storage obtained. By comparing the tracking accuracy with the target accuracy, the optimal frequency regulation pricing for battery energy storage is obtained;

[0010] S5. Constructing decision variables for battery energy storage: constructing a set of decision variables for battery energy storage according to the charging and discharging power of the battery energy storage, which includes the frequency modulation base value of the battery energy storage, i.e., the output of the battery energy storage participating in peak regulation, and the power of the battery energy storage responding to the frequency modulation signal. The output of the battery energy storage participating in peak regulation changes every 5 minutes following the electricity price in the power market, and the power of the battery energy storage responding to the frequency modulation signal is decided every 4 seconds following the change of the frequency modulation signal.

[0011] S6. Determine the objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation: express the relationship of battery energy storage capacity according to the state variables of battery energy storage, and then determine the objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation;

[0012] S7. Calculate the peak-shaving and frequency-regulating output of battery energy storage: The two decision variables of battery energy storage have different time scales, namely the base frequency value that changes every 5 minutes and the frequency output that changes every 4 seconds. Therefore, three time-scale models are established to calculate the peak-shaving and frequency-regulating output of battery energy storage in turn. The three time-scale models are the capacity model with a time scale of 1 hour, the base frequency value model with a time scale of 5 minutes, and the frequency modulation model with a time scale of 4 seconds.

[0013] Preferably, in step S1, the primary frequency modulation is to connect the real-time device based on GPS positioning to the energy management system of the dispatching center. If the power generation and load of the current control area are unbalanced, other control areas exchange power through the change of power on the tie line, so as to keep the frequency of the entire interconnected system consistent;

[0014] In step S3, the battery energy storage state variable set includes the battery energy storage capacity, the RegD frequency modulation signal, the electricity market price, and the battery energy storage tracking accuracy reflecting the strength of the battery energy storage response to the frequency modulation signal. The RegD frequency modulation signal changes every 4 seconds, the electricity market price changes every 5 minutes, and the battery energy storage tracking accuracy is evaluated once every hour. RegD is a signal generated by the regional control error through a high-pass filter, which is used for a dynamic frequency modulation power supply with a fast response speed.

[0015] Preferably, step S4 comprises the following steps:

[0016] S401. Determine the target accuracy of the battery energy storage tracking frequency modulation signal according to the new energy penetration rate of the power grid during the frequency modulation period;

[0017] S402, setting the initial value of the battery energy storage frequency regulation pricing, and solving the tracking decision of the battery energy storage for the frequency regulation signal with the goal of maximizing the total benefit of the battery energy storage participating in the peak regulation and frequency regulation according to the acquired basic information of the battery energy storage;

[0018] S403, calculating the tracking accuracy of the battery energy storage tracking frequency modulation signal according to the tracking decision;

[0019] S404. By comparing the tracking accuracy with the target accuracy, the frequency modulation pricing is continuously updated to affect the frequency modulation output of the battery energy storage, until the tracking accuracy of the battery energy storage reaches the target accuracy of the battery energy storage tracking frequency modulation signal, thereby obtaining the optimal frequency modulation pricing of the battery energy storage.

[0020] Preferably, step S5 comprises the following steps:

[0021] S501, Indicates battery energy storage charging;

[0022] S502, Indicates battery energy storage discharge;

[0023] S503, It means that the battery energy storage completely tracks the frequency modulation signal. Indicates the base value of battery energy storage frequency regulation, Indicates the power of the battery energy storage in response to the FM signal, D t Indicates RegD frequency modulation signal.

[0024] Preferably, in step S6, the total revenue includes two parts, one part of the revenue is generated by the charging and discharging of the battery energy storage, which is affected by the electricity price in the electricity market, and the other part of the revenue is the battery energy storage frequency regulation performance compensation revenue, which is determined by the frequency regulation pricing and the battery energy storage tracking accuracy;

[0025] The objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation is:

[0026]

[0027] Among them, V t E represents the electricity market price at time t, x t represents the set of decision variables for battery energy storage, t represents the time, T represents the entire period, Δt represents a part of the period, V t FRG represents the performance compensation income of battery energy storage participating in frequency regulation at time t, T It represents the average value of the deviation of the battery energy storage response to the frequency modulation signal during the T period. represents the frequency regulation pricing of the power market during the T period, η d represents the battery energy storage discharge efficiency, K represents the bid power in the T period, V T It means that the total benefits of peak and frequency regulation by battery energy storage are maximized;

[0028] Preferably, step S7 comprises the following steps:

[0029] S701. The state variable of the battery energy storage is composed of the battery energy storage capacity and the electricity market price. The decision variable is the charge and discharge power of the battery energy storage that changes every 5 minutes. The Bellman optimal equation is used to express the maximum value of the revenue of the energy storage participating in the grid service from the middle moment to the last moment. Therefore, the battery energy storage capacity value is settled once every hour as the initial value of the frequency modulation base value model.

[0030] S702. Under the frequency modulation base value model with a time scale of 5 minutes, a preset value is added for the accuracy of the battery energy storage responding to the frequency modulation signal during the frequency modulation moment, and it remains unchanged within each 5 minutes. When the preset value is equal to 0, it means that the battery energy storage does not track the frequency modulation signal at all during the frequency modulation moment. When the preset value is equal to 1, it means that the battery energy storage completely tracks the signal. The frequency modulation base value is used as a decision variable, and a recursive algorithm is used to obtain the maximum value of the battery energy storage benefit in the entire time period and at each moment, thereby determining the frequency modulation base value of the battery energy storage and the battery energy storage tracking accuracy within each 5 minutes.

[0031] Preferably, the step S7 further comprises the following steps:

[0032] S703. Under the frequency modulation model with a time scale of 4 seconds, within each 5-minute period, the battery energy storage frequency modulation base value and the power market electricity price remain unchanged, the power of the battery energy storage in response to the frequency modulation signal is taken as the only variable, and the decision variables of the battery energy storage in response to the frequency modulation signal are solved. According to the decision variables, the maximum tracking accuracy of the battery energy storage in response to the frequency modulation signal is obtained.

[0033] A peak-shaving and frequency-regulating transaction decision system comprises a primary frequency-regulating unit, a secondary frequency-regulating unit, a state variable construction unit, an optimal frequency-regulating pricing obtaining unit, a decision variable construction unit, an objective function determining unit and a peak-shaving and frequency-regulating output obtaining unit;

[0034] The primary frequency modulation unit makes the frequency of the entire interconnected system consistent through primary frequency modulation, inputs a signal with a sampling period of 2 seconds to continuously monitor the system frequency, selects the frequency modulation signal source according to the power generation control area, calculates the regional control error, and controls multiple areas according to the regional control error. The regional control error is an indicator to measure the load and power generation imbalance in the power system control area;

[0035] When the power grid cannot restore the system frequency to the rated value after the primary frequency regulation, the secondary frequency regulation unit performs secondary frequency regulation, increases the generator output by controlling the frequency regulator, and continues to increase the generator output when the load change is still greater than the output mechanical power of the generator, so that the increase in the mechanical power output of the generator is just equal to the initial load change, reaches a new balance point, and realizes the error-free regulation of the secondary frequency regulation;

[0036] The state variable construction unit models the battery energy storage participating in the peak load and frequency regulation of the power grid through a dynamic programming algorithm, obtains the basic parameters of the battery energy storage and the frequency regulation pricing of the power market, determines the initial and final charge states of the battery energy storage, and the basic parameters include the power of the battery energy storage in response to the frequency regulation signal, and together constructs a battery energy storage state variable set;

[0037] The optimal frequency regulation pricing obtaining unit obtains the new energy penetration rate of the power grid during the frequency regulation period to determine the target accuracy, and obtains the tracking accuracy according to the obtained basic information of the battery energy storage, and obtains the optimal frequency regulation pricing of the battery energy storage by comparing the tracking accuracy with the target accuracy;

[0038] The decision variable construction unit constructs a decision variable set of the battery energy storage according to the charging and discharging power of the battery energy storage, the set including the battery energy storage frequency modulation base value, i.e., the output of the battery energy storage participating in the peak regulation, and the power of the battery energy storage responding to the frequency modulation signal. The output of the battery energy storage participating in the peak regulation changes every 5 minutes following the electricity price in the power market, and the power of the battery energy storage responding to the frequency modulation signal is decided every 4 seconds following the change of the frequency modulation signal.

[0039] The objective function determination unit represents the relationship of the battery energy storage capacity according to the state variables of the battery energy storage, and then determines the objective function for maximizing the total benefits obtained by peak and frequency regulation of the battery energy storage;

[0040] The peak-shaving and frequency-regulating output obtaining unit establishes three time-scale models for the time scales of the two decision variables of the battery energy storage, and calculates the peak-shaving and frequency-regulating output of the battery energy storage in sequence. The three time-scale models are respectively a capacity model with a time scale of 1 hour, a frequency modulation base value model with a time scale of 5 minutes, and a frequency modulation model with a time scale of 4 seconds.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention improves the system frequency deviation to a certain extent through primary frequency modulation, and then realizes zero-difference regulation through secondary frequency modulation, that is, restores the system frequency to the rated value, models the battery energy storage participating in the peak-shaving and frequency modulation of the power grid through a dynamic programming algorithm, and obtains the battery energy storage peak-shaving and frequency modulation output with the goal of maximizing the battery energy storage peak-shaving and frequency modulation benefits. This can ensure that the total benefits of the battery energy storage peak-shaving and frequency modulation are maximized while reasonably allocating the output of the battery energy storage peak-shaving and frequency modulation, thereby realizing the optimization of different time scales of the battery energy storage peak-shaving and frequency modulation. In addition, by comparing the target accuracy determined by the new energy penetration rate and the tracking accuracy of the battery energy storage tracking frequency modulation signal with maximized benefits, the optimal frequency modulation pricing of the battery energy storage is obtained, which can ensure that the battery energy storage completes the peak-shaving service while participating in the frequency modulation to the maximum extent, so as to ensure the accuracy of the battery energy storage tracking frequency modulation signal and maintain the stability of the system frequency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of the overall process provided by an embodiment of the present invention;

[0044] Figure 2 A schematic diagram of a process for obtaining optimal frequency regulation pricing for battery energy storage provided by an embodiment of the present invention;

[0045] Figure 3 A schematic diagram of a process for calculating the peak and frequency regulation output of battery energy storage provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] See also Figure 1-3 The present invention provides a technical solution: a peak-shaving and frequency-modulating transaction decision method, comprising the following steps:

[0048] S1. Primary frequency modulation: The frequency of the entire interconnected system is kept consistent through primary frequency modulation. A signal with a sampling period of 2 seconds is input to continuously monitor the system frequency. The frequency modulation signal source is selected according to the power generation control area, the regional control error is calculated, and multiple areas are controlled according to the regional control error. The regional control error is an indicator to measure the imbalance between load and power generation in the power system control area;

[0049] S2, secondary frequency regulation: When the power grid cannot restore the system frequency to the rated value after the primary frequency regulation, the secondary frequency regulation is carried out. By controlling the frequency regulator, the generator output is increased. When the load change is still greater than the output mechanical power of the generator, the generator output is continued to be increased so that the increase in the mechanical power output of the generator is just equal to the initial load change, reaching a new balance point, and realizing the error-free regulation of the secondary frequency regulation;

[0050] S3. Constructing the state variables of battery energy storage: Modeling the battery energy storage participating in the peak load and frequency regulation of the power grid through the dynamic programming algorithm, obtaining the basic parameters of the battery energy storage and the frequency regulation pricing of the power market, determining the initial and final charge states of the battery energy storage, and the basic parameters including the power of the battery energy storage in response to the frequency regulation signal, and constructing the battery energy storage state variable set together;

[0051] S4. Obtaining the optimal frequency regulation pricing for battery energy storage: Obtain the penetration rate of new energy in the power grid during the frequency regulation period to determine the target accuracy, and obtain the tracking accuracy based on the basic information of the battery energy storage obtained. By comparing the tracking accuracy with the target accuracy, the optimal frequency regulation pricing for battery energy storage is obtained;

[0052] S5. Constructing decision variables for battery energy storage: constructing a set of decision variables for battery energy storage according to the charging and discharging power of the battery energy storage, which includes the frequency modulation base value of the battery energy storage, i.e., the output of the battery energy storage participating in peak regulation, and the power of the battery energy storage responding to the frequency modulation signal. The output of the battery energy storage participating in peak regulation changes every 5 minutes following the electricity price in the power market, and the power of the battery energy storage responding to the frequency modulation signal is decided every 4 seconds following the change of the frequency modulation signal.

[0053] S6. Determine the objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation: express the relationship of battery energy storage capacity according to the state variables of battery energy storage, and then determine the objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation;

[0054] S7. Calculate the peak-shaving and frequency-regulating output of battery energy storage: The two decision variables of battery energy storage have different time scales, namely the base frequency value that changes every 5 minutes and the frequency output that changes every 4 seconds. Therefore, three time-scale models are established to calculate the peak-shaving and frequency-regulating output of battery energy storage in turn. The three time-scale models are the capacity model with a time scale of 1 hour, the base frequency value model with a time scale of 5 minutes, and the frequency modulation model with a time scale of 4 seconds.

[0055] In step S1, the primary frequency regulation is to connect the real-time equipment based on GPS positioning to the energy management system of the dispatching center. If the power generation and load of the current control area are unbalanced, other control areas exchange power through the power change on the interconnection line, so as to keep the frequency of the entire interconnected system consistent;

[0056] The regional control error calculation formula is:

[0057] ACE=(NI A -NI S )-10B(f A -f S )-I ME

[0058] Among them, NI A Represents the sum of the actual power of all tie lines in the control area, NI S represents the sum of the power of all tie lines in the control area, B represents the frequency response coefficient of the control area, f A Indicates the actual value of the system frequency, f S Indicates the system frequency rating, I ME It represents the time difference correction caused by frequency offset, and ACE represents the area control error;

[0059] In step S3, the battery energy storage state variable set includes the battery energy storage capacity, the RegD frequency modulation signal, the electricity market price, and the battery energy storage tracking accuracy reflecting the intensity of the battery energy storage response to the frequency modulation signal. The RegD frequency modulation signal changes every 4 seconds, the electricity market price changes every 5 minutes, and the battery energy storage tracking accuracy is evaluated once every hour. RegD is a signal generated by the regional control error after a high-pass filter, which is used for a dynamic frequency modulation power supply with a fast response speed.

[0060] Step S4 includes the following steps:

[0061] S401. Determine the target accuracy of the battery energy storage tracking frequency modulation signal according to the new energy penetration rate of the power grid during the frequency modulation period;

[0062] S402, setting the initial value of the battery energy storage frequency regulation pricing, and solving the tracking decision of the battery energy storage for the frequency regulation signal with the goal of maximizing the total benefit of the battery energy storage participating in the peak regulation and frequency regulation according to the acquired basic information of the battery energy storage;

[0063] S403, calculating the tracking accuracy of the battery energy storage tracking frequency modulation signal according to the tracking decision;

[0064] S404, by comparing the tracking accuracy with the target accuracy, the frequency modulation pricing is continuously updated to affect the frequency modulation output of the battery energy storage, until the tracking accuracy of the battery energy storage reaches the target accuracy of the battery energy storage tracking frequency modulation signal, thereby obtaining the optimal frequency modulation pricing of the battery energy storage, improving the system frequency stability and realizing the total benefits of the battery energy storage peak modulation and frequency modulation;

[0065] Step S5 includes the following steps:

[0066] S501, Indicates battery energy storage charging;

[0067] S502, Indicates battery energy storage discharge;

[0068] S503, It means that the battery energy storage completely tracks the frequency modulation signal. Indicates the base value of battery energy storage frequency regulation, Indicates the power of the battery energy storage in response to the FM signal, D t Indicates RegD frequency modulation signal;

[0069] In step S6, the total revenue includes two parts. One part of the revenue is generated by the charging and discharging of the battery energy storage, which is affected by the electricity price in the power market. The other part of the revenue is the frequency regulation performance compensation revenue of the battery energy storage, which is determined by the frequency regulation pricing and the tracking accuracy of the battery energy storage.

[0070] The objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation is:

[0071]

[0072] Among them, V t E represents the electricity market price at time t, x t represents the set of decision variables for battery energy storage, t represents the time, T represents the entire period, Δt represents a part of the period, V t FR G represents the performance compensation income of battery energy storage participating in frequency regulation at time t, T It represents the average value of the deviation of the battery energy storage response to the frequency modulation signal during the T period. represents the frequency regulation pricing of the power market during the T period, η d represents the battery energy storage discharge efficiency, K represents the bid power in the T period, V T It means that the total benefits of peak and frequency regulation by battery energy storage are maximized;

[0073] Step S7 includes the following steps:

[0074] S701. The state variable of the battery energy storage is composed of the battery energy storage capacity and the electricity market price. The decision variable is the charge and discharge power of the battery energy storage that changes every 5 minutes. The Bellman optimal equation is used to represent the maximum benefit of the energy storage participating in the grid service from the middle moment to the last moment. Therefore, the battery energy storage capacity value is settled once every hour as the initial value of the frequency modulation base value model. The Bellman optimal equation is used as part of the dynamic programming algorithm.

[0075] Decision variable constraints:

[0076]

[0077] Among them, C trepresents the battery energy storage capacity at time t, represents the decision variable, C rated Indicates the rated capacity of battery energy storage, P rated represents the rated power of the battery energy storage, and Δt represents a partial period;

[0078] S702. Under the frequency modulation base value model with a time scale of 5 minutes, a preset value is added for the accuracy of the battery energy storage responding to the frequency modulation signal during the frequency modulation moment, and it remains unchanged within every 5 minutes. When the preset value is equal to 0, it means that the battery energy storage does not track the frequency modulation signal at all during the frequency modulation moment. When the preset value is equal to 1, it means that the battery energy storage completely tracks the signal. The frequency modulation base value is used as a decision variable. The maximum value of the battery energy storage benefit in the entire time period and at each moment is obtained through a recursive algorithm, thereby determining the frequency modulation base value of the battery energy storage and the tracking accuracy of the battery energy storage within each 5 minutes.

[0079] The recursive algorithm is:

[0080]

[0081] in, It represents the maximum benefit of battery energy storage participating in grid activities from time t to time T, V represents the maximum benefit of battery energy storage participating in grid activities from time t+τ to time T. t RB It represents the benefits of single-stage battery energy storage participating in the peak load and frequency regulation of the power grid at time t, It represents the state variable of battery energy storage under the frequency modulation base value model with a time scale of 5 minutes;

[0082] Step S7 also includes the following steps:

[0083] S703. Under the frequency modulation model with a time scale of 4 seconds, within each 5-minute period, the battery energy storage frequency modulation base value and the power market electricity price remain unchanged, the power of the battery energy storage in response to the frequency modulation signal is used as the only variable, and the decision variables of the battery energy storage in response to the frequency modulation signal are solved, and the maximum tracking accuracy of the battery energy storage in response to the frequency modulation signal is obtained according to the decision variables;

[0084] A peak-shaving and frequency-regulating transaction decision system comprises a primary frequency-regulating unit 1, a secondary frequency-regulating unit 2, a state variable construction unit 3, an optimal frequency-regulating pricing obtaining unit 4, a decision variable construction unit 5, an objective function determining unit 6 and a peak-shaving and frequency-regulating output obtaining unit 7;

[0085] The primary frequency modulation unit 1 makes the frequency of the entire interconnected system consistent through primary frequency modulation, inputs a signal with a sampling period of 2 seconds to continuously monitor the system frequency, selects the frequency modulation signal source according to the power generation control area, calculates the regional control error, and controls multiple areas according to the regional control error. The regional control error is an indicator to measure the load and power generation imbalance in the power system control area;

[0086] Secondary frequency regulation unit 2 When the power grid cannot restore the system frequency to the rated value after the primary frequency regulation, the secondary frequency regulation is performed. By controlling the frequency regulator, the generator output is increased. When the load change is still greater than the output mechanical power of the generator, the generator output is continued to be increased so that the increase in the mechanical power output of the generator is just equal to the initial load change, reaching a new balance point, and realizing the error-free regulation of the secondary frequency regulation;

[0087] The state variable construction unit 3 models the battery energy storage participating in the peak load and frequency regulation of the power grid through a dynamic programming algorithm, obtains the basic parameters of the battery energy storage and the frequency regulation pricing of the power market, determines the initial and final charge states of the battery energy storage, and the basic parameters include the power of the battery energy storage in response to the frequency regulation signal, and together constructs a battery energy storage state variable set;

[0088] The optimal frequency regulation pricing obtaining unit 4 obtains the penetration rate of new energy sources in the power grid during the frequency regulation period to determine the target accuracy, and obtains the tracking accuracy based on the obtained basic information of the battery energy storage, and obtains the optimal frequency regulation pricing of the battery energy storage by comparing the tracking accuracy with the target accuracy;

[0089] The decision variable construction unit 5 constructs a decision variable set of the battery energy storage according to the charging and discharging power of the battery energy storage, which includes the frequency modulation base value of the battery energy storage, that is, the output of the battery energy storage participating in the peak regulation, and the power of the battery energy storage responding to the frequency modulation signal. The output of the battery energy storage participating in the peak regulation changes every 5 minutes following the electricity price in the power market, and the power of the battery energy storage responding to the frequency modulation signal is decided every 4 seconds following the change of the frequency modulation signal.

[0090] The objective function determination unit 6 represents the relationship of the battery energy storage capacity according to the state variables of the battery energy storage, and further determines the objective function for maximizing the total benefits obtained by the battery energy storage peak load regulation and frequency regulation;

[0091] The peak-shaving and frequency-regulating output obtaining unit 7 establishes three time-scale models for the time scales of the two decision variables of the battery energy storage, and calculates the peak-shaving and frequency-regulating output of the battery energy storage in turn. The three time-scale models are respectively a capacity model with a time scale of 1 hour, a frequency modulation base value model with a time scale of 5 minutes, and a frequency modulation model with a time scale of 4 seconds.

[0092] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0093] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A peak-shaving and frequency-modulation transaction decision-making method, characterized in that The following steps are involved: S1. Primary frequency modulation: The frequency of the entire interconnected system is kept consistent through primary frequency modulation. A signal with a sampling period of 2 seconds is input to continuously monitor the system frequency. The frequency modulation signal source is selected according to the power generation control area, the regional control error is calculated, and multiple areas are controlled according to the regional control error. The regional control error is an indicator to measure the imbalance between load and power generation in the power system control area; S2, secondary frequency regulation: When the power grid cannot restore the system frequency to the rated value after the primary frequency regulation, the secondary frequency regulation is carried out. By controlling the frequency regulator, the generator output is increased. When the load change is still greater than the output mechanical power of the generator, the generator output is continued to be increased so that the increase in the mechanical power output of the generator is just equal to the initial load change, reaching a new balance point, and realizing the error-free regulation of the secondary frequency regulation; S3. Constructing the state variables of battery energy storage: Modeling the battery energy storage participating in the peak load and frequency regulation of the power grid through the dynamic programming algorithm, obtaining the basic parameters of the battery energy storage and the frequency regulation pricing of the power market, determining the initial and final charge states of the battery energy storage, and the basic parameters including the power of the battery energy storage in response to the frequency regulation signal, and constructing the battery energy storage state variable set together; S4. Obtaining the optimal frequency regulation pricing for battery energy storage: Obtain the penetration rate of new energy in the power grid during the frequency regulation period to determine the target accuracy, and obtain the tracking accuracy based on the basic information of the battery energy storage obtained. By comparing the tracking accuracy with the target accuracy, the optimal frequency regulation pricing for battery energy storage is obtained; S5. Constructing decision variables for battery energy storage: constructing a set of decision variables for battery energy storage according to the charging and discharging power of the battery energy storage, which includes the frequency modulation base value of the battery energy storage, i.e., the output of the battery energy storage participating in peak regulation, and the power of the battery energy storage responding to the frequency modulation signal. The output of the battery energy storage participating in peak regulation changes every 5 minutes following the electricity price in the power market, and the power of the battery energy storage responding to the frequency modulation signal is decided every 4 seconds following the change of the frequency modulation signal. S6. Determine the objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation: express the relationship of battery energy storage capacity according to the state variables of battery energy storage, and then determine the objective function for maximizing the total benefits of battery energy storage peak load regulation and frequency regulation; S7. Calculate the peak-shaving and frequency-regulating output of battery energy storage: The two decision variables of battery energy storage have different time scales, namely the base frequency value that changes every 5 minutes and the frequency output that changes every 4 seconds. Therefore, three time-scale models are established to calculate the peak-shaving and frequency-regulating output of battery energy storage in turn. The three time-scale models are the capacity model with a time scale of 1 hour, the base frequency value model with a time scale of 5 minutes, and the frequency modulation model with a time scale of 4 seconds.

2. A peak-shaving and frequency-modulation transaction decision-making method according to claim 1, characterized in that: In step S1, the primary frequency modulation is to connect the real-time equipment based on GPS positioning to the energy management system of the dispatching center. If the power generation and load of the current control area are unbalanced, other control areas exchange power through the power change on the interconnection line, so as to keep the frequency of the entire interconnected system consistent; In step S3, the battery energy storage state variable set includes the battery energy storage capacity, the RegD frequency modulation signal, the electricity market price, and the battery energy storage tracking accuracy reflecting the strength of the battery energy storage response to the frequency modulation signal. The RegD frequency modulation signal changes every 4 seconds, the electricity market price changes every 5 minutes, and the battery energy storage tracking accuracy is evaluated once every hour. RegD is a signal generated by the regional control error through a high-pass filter, which is used for a dynamic frequency modulation power supply with a fast response speed.

3. A peak-shaving and frequency-modulation transaction decision-making method according to claim 1, characterized in that: The step S4 comprises the following steps: S401. Determine the target accuracy of the battery energy storage tracking frequency modulation signal according to the new energy penetration rate of the power grid during the frequency modulation period; S402, setting the initial value of the battery energy storage frequency regulation pricing, and solving the tracking decision of the battery energy storage for the frequency regulation signal with the goal of maximizing the total benefit of the battery energy storage participating in the peak regulation and frequency regulation according to the acquired basic information of the battery energy storage; S403, calculating the tracking accuracy of the battery energy storage tracking frequency modulation signal according to the tracking decision; S404. By comparing the tracking accuracy with the target accuracy, the frequency modulation pricing is continuously updated to affect the frequency modulation output of the battery energy storage, until the tracking accuracy of the battery energy storage reaches the target accuracy of the battery energy storage tracking frequency modulation signal, thereby obtaining the optimal frequency modulation pricing of the battery energy storage.

4. A peak-shaving and frequency-modulation transaction decision-making method according to claim 1, characterized in that: The step S5 comprises the following steps: S501, Indicates battery energy storage charging; S502, Indicates battery energy storage discharge; S503, It means that the battery energy storage completely tracks the frequency modulation signal. Indicates the base value of battery energy storage frequency regulation, Indicates the power of the battery energy storage in response to the FM signal, D t Indicates RegD frequency modulation signal.

5. A peak-shaving and frequency-modulation transaction decision-making method according to claim 1, characterized in that: In step S6, the total revenue includes two parts. One part of the revenue is generated by the charging and discharging of the battery energy storage, which is affected by the electricity price in the power market. The other part of the revenue is the battery energy storage frequency regulation performance compensation revenue, which is determined by the frequency regulation pricing and the battery energy storage tracking accuracy.

6. A peak-shaving and frequency-modulation transaction decision-making method according to claim 1, characterized in that: The step S7 comprises the following steps: S701. The state variable of the battery energy storage is composed of the battery energy storage capacity and the electricity market price. The decision variable is the charge and discharge power of the battery energy storage that changes every 5 minutes. The Bellman optimal equation is used to express the maximum value of the revenue of the energy storage participating in the grid service from the middle moment to the last moment. Therefore, the battery energy storage capacity value is settled once every hour as the initial value of the frequency modulation base value model. S702. Under the frequency modulation base value model with a time scale of 5 minutes, a preset value is added for the accuracy of the battery energy storage responding to the frequency modulation signal during the frequency modulation moment, and it remains unchanged within each 5 minutes. When the preset value is equal to 0, it means that the battery energy storage does not track the frequency modulation signal at all during the frequency modulation moment. When the preset value is equal to 1, it means that the battery energy storage completely tracks the signal. The frequency modulation base value is used as a decision variable, and a recursive algorithm is used to obtain the maximum value of the battery energy storage benefit in the entire time period and at each moment, thereby determining the frequency modulation base value of the battery energy storage and the battery energy storage tracking accuracy within each 5 minutes.

7. A peak-shaving and frequency-modulation transaction decision-making method according to claim 6, characterized in that: The step S7 further comprises the following steps: S703. Under the frequency modulation model with a time scale of 4 seconds, within each 5-minute period, the battery energy storage frequency modulation base value and the power market electricity price remain unchanged, the power of the battery energy storage in response to the frequency modulation signal is taken as the only variable, and the decision variables of the battery energy storage in response to the frequency modulation signal are solved. According to the decision variables, the maximum tracking accuracy of the battery energy storage in response to the frequency modulation signal is obtained.

8. A peak-shaving and frequency-modulation trading decision-making system, characterized in that: The peak frequency modulation transaction decision system has the peak frequency modulation transaction decision method described in any one of 1 to 7, including a primary frequency modulation unit (1), a secondary frequency modulation unit (2), a state variable construction unit (3), an optimal frequency modulation pricing acquisition unit (4), a decision variable construction unit (5), an objective function determination unit (6) and a peak frequency modulation output acquisition unit (7); The primary frequency modulation unit (1) maintains the frequency of the entire interconnected system consistent through primary frequency modulation, inputs a signal with a sampling period of 2 seconds to continuously monitor the system frequency, selects a frequency modulation signal source according to a power generation control area, calculates a regional control error, and controls multiple areas according to the regional control error, wherein the regional control error is an indicator for measuring the imbalance between load and power generation in the power system control area; The secondary frequency regulation unit (2) performs secondary frequency regulation when the power grid cannot restore the system frequency to the rated value after the primary frequency regulation, and increases the generator output by controlling the frequency regulator. When the load change is still greater than the output mechanical power of the generator, the generator output is further increased to make the increase in the mechanical power output of the generator just equal to the initial load change, so as to reach a new balance point and realize the error-free regulation of the secondary frequency regulation. The state variable construction unit (3) models the battery energy storage participating in the peak load and frequency regulation of the power grid through a dynamic programming algorithm, obtains the basic parameters of the battery energy storage and the frequency regulation pricing of the power market, determines the initial and final charge states of the battery energy storage, the basic parameters include the power of the battery energy storage in response to the frequency regulation signal, and together constructs a battery energy storage state variable set; The optimal frequency regulation pricing obtaining unit (4) obtains the new energy penetration rate of the power grid during the frequency regulation period to determine the target accuracy, and obtains the tracking accuracy based on the obtained basic information of the battery energy storage, and obtains the optimal frequency regulation pricing of the battery energy storage by comparing the tracking accuracy with the target accuracy; The decision variable construction unit (5) constructs a decision variable set for the battery energy storage according to the charging and discharging power of the battery energy storage, the set including the battery energy storage frequency modulation base value, i.e., the output of the battery energy storage participating in peak regulation, and the power of the battery energy storage responding to the frequency modulation signal, the output of the battery energy storage participating in peak regulation changes every 5 minutes following the electricity price in the power market, and the power of the battery energy storage responding to the frequency modulation signal is decided every 4 seconds following the change of the frequency modulation signal; The objective function determination unit (6) represents the relationship between the battery energy storage capacity according to the state variables of the battery energy storage, and then determines the objective function for maximizing the total benefits obtained by peak and frequency regulation of the battery energy storage; The peak-shaving and frequency-regulating output obtaining unit (7) establishes three time-scale models for the time scales of the two decision variables of the battery energy storage, and calculates the peak-shaving and frequency-regulating output of the battery energy storage in sequence. The three time-scale models are respectively a capacity model with a time scale of 1 hour, a frequency-regulating base value model with a time scale of 5 minutes, and a frequency-regulating model with a time scale of 4 seconds.

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