Coordinated control method and system for peak regulation and frequency modulation market considering energy storage benefit

Abstract

The application discloses a peak regulation and frequency modulation market coordination control method considering energy storage benefits, and has the characteristics that the method comprises the following steps: according to the quotation and intended transaction power of a new energy station, a stand-alone energy storage power station carries out simulated power constraint and simulated market clearing to obtain expected peak regulation benefits; according to a power frequency modulation demand curve issued by a power dispatching institution, the stand-alone energy storage calculates expected frequency modulation benefits; according to the expected peak regulation benefits and the expected frequency modulation benefits, the expected benefit difference is calculated; according to the benefit difference of each period and the energy storage SOC condition, a frequency modulation quotation scheme is formulated; according to the frequency modulation quotation scheme of each frequency modulation subject, frequency modulation market bidding and clearing are carried out, and according to the frequency modulation results of the target stand-alone energy storage power station and the power constraint and capacity constraint, peak regulation market clearing is carried out; and according to the peak regulation and frequency modulation market conditions, peak regulation and frequency modulation are carried out. The method has the advantages of scientific rationality, strong applicability and good effect. The application also discloses a system.

Description

Technical Field

[0001] This invention relates to the field of energy storage participation in peak shaving in power systems, and is a method and system for coordinated control of peak shaving and frequency regulation markets that takes into account the revenue of energy storage. Background Technology

[0002] Currently, there is active promotion in this field for independent energy storage power stations to participate in the ancillary services market, but there is still no coordination involving multiple ancillary service tasks. Moreover, the current ancillary services market is cleared by dispatching agencies through bidding by multiple entities, making it difficult to simply coordinate multiple markets.

[0003] Due to current limitations in the development of energy storage battery technology, the cost of energy storage power stations remains high. At the same time, because the current subsidies for ancillary service tasks are low, it is difficult for energy storage power stations to achieve profitability by participating in only a single ancillary service task, and their battery utilization rate is also low. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a peak-shaving and frequency regulation market trading method and system that includes a peak-shaving and frequency regulation market model and a control system for energy storage power stations. This method enables energy storage power stations to coordinate their participation in the peak-shaving and frequency regulation ancillary service market, thereby increasing the economic efficiency and battery utilization of energy storage power stations. It is scientific, reasonable, highly applicable, and effective, taking into account the revenue of energy storage.

[0005] One of the technical solutions adopted to achieve the objective of this invention is: a peak-shaving and frequency regulation market coordination and control method considering energy storage revenue, characterized in that the method includes establishing an expected revenue calculation model, a pricing model, and a peak-shaving power setting model, coordinating two ancillary service markets, and generating frequency regulation and peak-shaving task curves with the goal of optimal economic efficiency. Specific details include:

[0006] Based on the quotations and intended trading power of new energy power plants, independent energy storage power plants conduct simulated power constraints and simulated market clearing to obtain expected peak-shaving benefits;

[0007] Based on the power frequency regulation demand curve released by the power dispatching agency, the expected frequency regulation revenue of independent energy storage is calculated.

[0008] The expected return difference is calculated based on the expected peak-shaving revenue and the expected frequency regulation revenue.

[0009] A frequency regulation pricing scheme is formulated based on the revenue difference in each time period and the SOC of energy storage.

[0010] The frequency regulation market will be cleared through competitive bidding based on the bidding schemes of each frequency regulation entity, and the peak shaving market will be cleared based on the frequency regulation results of the target independent energy storage power station, as well as power and capacity constraints.

[0011] Peak shaving and frequency regulation are carried out according to the situation of the peak shaving and frequency regulation market.

[0012] Furthermore, the simulated power constraint and simulated market clearing stipulate that the transaction power of an independent energy storage power station at any given time should not exceed its rated charging power, and the clearing should be based on the bidding prices of the peak-shaving applicants.

[0013] During the initial trading session of the trading day, wind power and photovoltaic new energy power plants submit bid curve C to independent energy storage power stations. new,ini,i,t And the power curve of intended transactions P new,ini,i,t At this point, the internal control system of the independent energy storage power station performs power constraints and simulates clearing processes based on the peak-shaving application situation, obtaining the winning bid price curve C after the simulated peak-shaving market ends. 1new,cle,i,t and the power curve P 1new,cle,i,t .

[0014] Furthermore, the expression for the expected peak-shaving return is as follows:

[0015] Regarding the revenue Q of the energy storage power station undertaking peak shaving tasks per hour tf,i The solution formula is:

[0016]

[0017] In the formula, n is the number of new energy power stations;

[0018] The hourly revenue Q for charging during peak hours c,t for:

[0019]

[0020] The hourly revenue Q for discharge during peak shaving periods f,d for:

[0021]

[0022] In the formula, N cd C represents the total number of successful bids for charging during the peak shaving phase; f P is the unit price of electricity sales; n This refers to the rated power of the energy storage power station.

[0023] Furthermore, independent energy storage power stations obtain the highest expected winning bid based on the power frequency regulation demand curve published by the power dispatching agency:

[0024] Based on the lowest winning bid price C for each frequency regulation demand derived from the simulated frequency regulation market of independent energy storage power stations. zb,j,min,t and the pre-selected winning bid capacity P m,t Based on the lowest winning bid price and the expected winning bid capacity, the highest bid C required for the target independent energy storage to win the bid is calculated. zb,max,t :

[0025]

[0026] In the formula: K is the comprehensive frequency regulation performance index of the target energy storage power station, K j This refers to the comprehensive frequency regulation performance indicators of critically selected energy storage power stations.

[0027] Furthermore, the expression for the expected revenue from frequency modulation is as follows:

[0028] Regarding the revenue Q of the energy storage power station undertaking frequency regulation tasks per hour bj,i The solution formula is:

[0029] Q bj,t =C bj，max,t P m,t N m,t (5)

[0030] Where: N m,t This represents the equivalent number of actions taken by the energy storage power station to participate in frequency regulation tasks for each time period.

[0031] Furthermore, the expression for calculating the expected peak-shaving and frequency-modulation revenue difference is as follows:

[0032] The difference between the hourly peak-shaving revenue and the frequency regulation revenue calculated based on the highest winning bid during peak-shaving charging periods:

[0033] Q cc,t =Q c,t -Q bj,t (6)

[0034] The difference between the hourly peak-shaving revenue and the frequency regulation revenue calculated based on the highest winning bid during the peak-shaving discharge period:

[0035] Q fc,t =Q f,t -Q bj,t (7).

[0036] Furthermore, the aforementioned method for formulating frequency regulation pricing should first select the execution period for the frequency regulation task based on the energy storage SOC and the expected return difference, including:

[0037] The revenue difference is calculated during the charging period, and the maximum rechargeable time T when the battery has the lowest capacity is calculated based on the battery's rated charging power and rated capacity. max Based on the previous peak shaving and frequency regulation phase, determine the number of charging hours T at the start of the peak shaving and frequency regulation phase, and calculate the T hours with the greatest benefit during the peak shaving and charging period:

[0038] [t1,t2......t T ] = maxQ cc,t (8) During the discharge period, the maximum profit difference T is calculated. N Hours:

[0039]

[0040] [t1,t2......t TN ] = maxQ fc,t (10)

[0041] In the formula, Q max For independent energy storage power stations, a maximum capacity beyond frequency regulation capacity is reserved, Q max A minimum capacity beyond frequency regulation capacity is reserved for independent energy storage power stations.

[0042] Furthermore, the formulation of the aforementioned frequency modulation price includes:

[0043] Benefit Q from historical average peak-shaving discharge time f,y,u T at the moment of maximum difference max By comparing the frequency modulation gains at time points T, we find that T1 is less than or greater than Q. f,y,u At time T1, after obtaining time T1, peak-shaving discharge will be arranged at time T1. In the frequency regulation market quotation, the quotation will be the unit price after peak-shaving revenue is converted.

[0044] For T charging periods and T discharging periods, the frequency regulation and peak shaving scheme with the greatest benefit is calculated by using the difference in their benefits: peak shaving tasks are arranged for the 2-hour charging period, and the remaining time is arranged for frequency regulation tasks; peak shaving tasks are arranged for the 3-hour discharging period, and the remaining time is arranged for frequency regulation tasks.

[0045] Furthermore, the peak-shaving market clearing, which is determined by power constraints, includes:

[0046] Based on the clearing results of the frequency regulation market, the peak-shaving power of the energy storage power station for each time period and the maximum rechargeable capacity during the peak-shaving charging phase are determined and constrained, and finally the peak-shaving market clearing is implemented.

[0047] The second technical solution for achieving the objective of this invention is a peak-shaving and frequency regulation market coordination control system that considers energy storage revenue, characterized in that the system includes:

[0048] The acquisition module is used to acquire the peak-shaving demand of new energy power plants and the frequency regulation demand of the power grid;

[0049] The market module is used to conduct market bidding and clearing to obtain the winning power and price;

[0050] The revenue calculation module is used to calculate the expected peak-shaving revenue and the expected frequency regulation revenue, and provides the revenue basis for subsequent modules based on the revenue difference;

[0051] The frequency regulation pricing module determines whether to perform peak shaving or frequency regulation tasks for each time period based on the revenue difference, and sets the frequency regulation price according to the set task.

[0052] The peak-shaving power optimization module determines the scalable peak power for each time period based on the clearing results of the frequency regulation market, and then performs constraints and clearing of the peak-shaving market.

[0053] The execution module performs ancillary service tasks based on the results of the peak shaving and frequency regulation markets.

[0054] Furthermore, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method when executing the computer program.

[0055] This invention proposes a coordinated control method and system for the peak-shaving and frequency regulation market, considering the revenue of energy storage. The method divides the peak-shaving and frequency regulation markets into a simulated market stage and an actual market stage. Through the simulated market stage, the expected revenue of independent energy storage power stations participating in different ancillary services can be calculated initially. Based on the calculated expected revenue, bidding can be conducted in the frequency regulation market. After obtaining the clearing results of the frequency regulation market, the peak-shaving market is cleared through a competitive bidding process, taking into account the rated power and capacity of energy storage and the bidding prices of new energy power stations. The final execution is based on the results of both markets. Furthermore, the effectiveness of this method is verified using the predicted output of new energy power stations and regional frequency regulation demand as case studies. By coordinating participation in the two ancillary services, the economics of independent energy storage participating in the ancillary service market are improved. The method has the advantages of being scientifically sound, highly applicable, and effective. Attached Figure Description

[0056] Figure 1 This is a block diagram of a peak-shaving and frequency regulation market coordination control method that takes into account energy storage revenue, according to the present invention.

[0057] Figure 2 This is a diagram of a regional power grid system containing multiple power sources in an example of the present invention;

[0058] Figure 3 This is an example of an energy storage power station participating only in the peak-shaving market, shown in the SOC diagram.

[0059] Figure 4 This is the SOC diagram of the energy storage power station participating only in the frequency regulation market in this embodiment of the invention;

[0060] Figure 5 This is a diagram of the SOC (State of Charge) of an energy storage power station coordinating its participation in two energy storage markets in an example of this invention.

[0061] Figure 6 This is a block diagram of a peak-shaving and frequency regulation market coordination and control system that takes into account energy storage revenue in an embodiment of the present invention;

[0062] Figure 7 This is a block diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0063] refer to Figure 1 This invention provides a method for coordinated control of the peak-shaving and frequency regulation market, considering energy storage revenue. The method includes establishing an expected revenue calculation model, a pricing model, and a peak-shaving power setting model; coordinating two ancillary service markets; and generating frequency regulation and peak-shaving task curves with the goal of optimal economic efficiency. Specific details include:

[0064] Based on the quotations and intended trading power of new energy power plants, independent energy storage power plants conduct simulated power constraints and simulated market clearing to obtain expected peak-shaving benefits;

[0065] Based on the power frequency regulation demand curve released by the power dispatching agency, the expected frequency regulation revenue of independent energy storage is calculated.

[0066] The expected return difference is calculated based on the expected peak-shaving revenue and the expected frequency regulation revenue.

[0067] A frequency regulation pricing scheme is formulated based on the revenue difference in each time period and the SOC of energy storage.

[0068] The frequency regulation market will be cleared through competitive bidding based on the bidding schemes of each frequency regulation entity, and the peak shaving market will be cleared based on the frequency regulation results of the target independent energy storage power station, as well as power and capacity constraints.

[0069] Peak shaving and frequency regulation are carried out according to the situation of the peak shaving and frequency regulation market.

[0070] The simulated power constraint and simulated market clearing stipulate that the transaction power of an independent energy storage power station at any given time should not exceed its rated charging power, and the clearing should be based on the bidding prices of the peak-shaving applicants.

[0071] During the initial trading session of the trading day, wind power and photovoltaic new energy power plants submit bid curve C to independent energy storage power stations. new,ini,i,t And the power curve of intended transactions P new,ini,i,t At this point, the internal control system of the independent energy storage power station performs power constraints and simulates clearing processes based on the peak-shaving application situation, obtaining the winning bid price curve C after the simulated peak-shaving market ends. 1new,cle,i,t and the power curve P 1new,cle,i,t .

[0072] The expression for the expected peak-shaving return is as follows:

[0073] Regarding the revenue Q of the energy storage power station undertaking peak shaving tasks per hour tf,i The solution formula is:

[0074]

[0075] In the formula, n is the number of new energy power stations;

[0076] The hourly revenue Q for charging during peak hours c,t for:

[0077]

[0078] The hourly revenue Q for discharge during peak shaving periods f,d for:

[0079]

[0080] In the formula, N cd C represents the total number of successful bids for charging during the peak shaving phase; f P is the unit price of electricity sales; n This refers to the rated power of the energy storage power station.

[0081] The highest expected winning bid was obtained by the independent energy storage power station based on the power frequency regulation demand curve published by the power dispatching agency.

[0082] Based on the lowest winning bid price C for each frequency regulation demand derived from the simulated frequency regulation market of independent energy storage power stations. zb,j,min,t and the pre-selected winning bid capacity P m,t Based on the lowest winning bid price and the expected winning bid capacity, the highest bid C required for the target independent energy storage to win the bid is calculated. zb,max,t :

[0083]

[0084] In the formula: K is the comprehensive frequency regulation performance index of the target energy storage power station, K j This refers to the comprehensive frequency regulation performance indicators of critically selected energy storage power stations.

[0085] The expression for the expected revenue of frequency modulation is as follows:

[0086] Regarding the revenue Q of the energy storage power station undertaking frequency regulation tasks per hour bj,i The solution formula is:

[0087] Q bj,t =C bj，max,t P m,t N m,t (15)

[0088] Where: N m,t This represents the equivalent number of actions taken by the energy storage power station to participate in frequency regulation tasks for each time period.

[0089] The expression for calculating the expected peak-shaving and frequency-modulation revenue difference is as follows:

[0090] The difference between the hourly peak-shaving revenue and the frequency regulation revenue calculated based on the highest winning bid during peak-shaving charging periods:

[0091] Q cc,t =Q c,t -Q bj,t (16)

[0092] The difference between the hourly peak-shaving revenue and the frequency regulation revenue calculated based on the highest winning bid during the peak-shaving discharge period:

[0093] Q fc,t =Q f,t -Q bj,t (17).

[0094] The aforementioned method for formulating frequency regulation pricing should first select the execution period for the frequency regulation task based on the energy storage SOC and the expected return difference, including:

[0095] The revenue difference is calculated during the charging period, and the maximum rechargeable time T when the battery has the lowest capacity is calculated based on the battery's rated charging power and rated capacity. max Based on the previous peak shaving and frequency regulation phase, determine the number of charging hours T at the start of the peak shaving and frequency regulation phase, and calculate the T hours with the greatest benefit during the peak shaving and charging period:

[0096] [t1,t2......t T ] = maxQ cc,t (18) During the discharge period, the maximum profit difference T is calculated. N Hours:

[0097]

[0098] [t1,t2......t TN ] = maxQ fc,t (20)

[0099] In the formula, Q max For independent energy storage power stations, a maximum capacity beyond frequency regulation capacity is reserved, Q max To reserve a minimum capacity beyond frequency regulation capacity for independent energy storage power stations, P n This refers to the rated power of the energy storage power station.

[0100] The formulation of the aforementioned frequency modulation price includes:

[0101] Benefit Q from historical average peak-shaving discharge time f,y,u T at the moment of maximum difference max By comparing the frequency modulation gains at time points T, we find that T1 is less than or greater than Q. f,y,uAt time T1, after obtaining time T1, peak-shaving discharge will be arranged at time T1. In the frequency regulation market quotation, the quotation will be the unit price after peak-shaving revenue is converted.

[0102] For T charging periods and T discharging periods, the frequency regulation and peak shaving scheme with the greatest benefit is calculated by using the difference in their benefits: peak shaving tasks are arranged for the 2-hour charging period, and the remaining time is arranged for frequency regulation tasks; peak shaving tasks are arranged for the 3-hour discharging period, and the remaining time is arranged for frequency regulation tasks.

[0103] For the remaining unplanned peak-shaving periods, normal frequency regulation pricing will be conducted based on the frequency regulation pricing model.

[0104] After the bids are submitted, a competitive bidding process is conducted in the frequency regulation market to determine the winning frequency regulation power P of the energy storage power station for each time period. tp,t and clearing price C tp,t .

[0105] The aforementioned peak-shaving market clearing, wherein the clearing result is determined through power constraints, includes:

[0106] Based on the clearing results of the frequency regulation market, the peak-shaving power of the energy storage power station for each time period and the maximum rechargeable capacity during the peak-shaving charging phase are determined and constrained, and finally the peak-shaving market clearing is implemented.

[0107] Peak shaving power setting

[0108] When multiple renewable energy power plants participate in independent energy storage bilateral transactions, bidding is required, and the final subsidy bids are cleared according to a unified marginal price.

[0109]

[0110] Where F V Total subsidy revenue for independent energy storage; T cha For bilateral trading sessions; s t P is the unit price for the subsidy during time period t; i,t Let Δt be the winning bid power of the i-th renewable energy power station during time period t; Δt is the time interval.

[0111] When formulating peak-shaving transactions for independent energy storage, the following constraints should be met:

[0112] i) Energy storage participation in peak shaving power constraints

[0113] P tp，t -P n ≤P tf,t ≤P n -P tp，t (twenty two)

[0114] Among them, P tf,t The charging power for independent energy storage during period t;

[0115] ii) Energy storage capacity constraints

[0116] Q tf ≤Q tf,max (twenty three)

[0117] Among them, Q tf Charging amount during peak shaving phase of independent energy storage; Q tf,max This represents the maximum rechargeable capacity during the independent energy storage peak-shaving phase.

[0118] iii) Bidding power constraints in bilateral transactions

[0119]

[0120] Model Solving

[0121] a) Wind power, photovoltaic, and other new energy power plants participating in the peak-shaving market submit their bid curves (C) to independent energy storage power stations. new,ini,i,t And the power curve of intended transactions P new,ini,i,t ;

[0122] b) The internal control system of the independent energy storage power station performs power constraints and simulated clearing processes for peak shaving applications, resulting in the winning bid price curve C after the simulated peak shaving market ends. 1new,cle,i,t and the power curve P 1new,cle,i,t ;

[0123] c) Calculate the hourly peak-shaving charging revenue Q of the energy storage power station. c,t The revenue Q per hour from peak-shaving charging provided by the energy storage power station f,d ;

[0124] d) The power dispatching agency releases frequency regulation demand, and energy storage power stations conduct simulated frequency regulation market bidding. Solve for the highest bid C required for each time period to win the bid for the energy storage power station. bj,max,t And solve for the expected revenue Q per hour from frequency modulation. bj,i ;

[0125] e) Calculate and solve for the expected revenue difference during peak-shaving charging period and the expected revenue difference during peak-shaving discharging period for independent energy storage power stations;

[0126] f) Calculate the maximum rechargeable time T when the battery has the lowest charge capacity, based on the battery's rated charging power and rated capacity. max And determine the number of chargeable hours T at the start of the peak shaving and frequency regulation phase based on the previous peak shaving and frequency regulation phase;

[0127] g) Calculate the hour with the greatest benefit during peak-shaving charging and the hour with the greatest benefit during discharging. N Hourly intervals are allocated for frequency adjustment, and frequency adjustment quotes are provided based on the different tasks scheduled for different time periods.

[0128] h) The power dispatching agency conducted a competitive bidding process for frequency regulation tasks, and obtained the winning bid C for frequency regulation. tp,t and the winning frequency modulation power P tp,t Based on power and capacity constraints, peak-shaving tasks are cleared out to obtain the final winning bid price C. tft and the winning frequency modulation power P tf,t And perform peak shaving and frequency adjustment tasks;

[0129] Optimization scheme evaluation indicators

[0130] a) Revenue from energy storage power stations

[0131] W income =W tp +W tf (25)

[0132] The total revenue of an energy storage power station mainly includes the revenue W from its participation in frequency regulation tasks. tp And the rewards W for participating in peak shaving tasks tf .

[0133] b) Power utilization rate

[0134]

[0135] In the formula: η P This refers to the power utilization rate of the batteries in an energy storage power station; a higher value indicates a higher power utilization rate. tf The number of times the energy storage power station undertook peak-shaving tasks; N tf ,i is the power output of the energy storage power station during each peak shaving; t tf N represents the unit price period in the peak-shaving market; tp N represents the number of times a bid has been won in the frequency regulation market for energy storage power stations. tp,i The power output of the energy storage power station in each frequency regulation bid; t tp For unit quotation periods in the FM market; t total This represents the total time.

[0136] Reference Figure 6 A peak-shaving and frequency regulation market coordination and control system that considers energy storage revenue includes:

[0137] The acquisition module is used to acquire the expected peak-shaving demand curve, peak-shaving price curve, and expected frequency regulation demand curve of the power grid for renewable energy power plants.

[0138] The market module is used for the first time to simulate market bidding and clearing based on the data obtained from the acquisition module, resulting in the expected hourly power curves and winning bid price curves for individual participation in peak shaving and frequency regulation; the market module is used for the second time to simulate actual market bidding and clearing after the bid is finalized, resulting in the actual final execution curve.

[0139] The revenue calculation module is used to calculate the expected peak shaving revenue and expected frequency regulation revenue for participating in only a single auxiliary service task, and provides the revenue basis for subsequent modules based on the revenue difference;

[0140] The frequency regulation pricing module determines the power allocation for different tasks in each time period based on the profit difference, and determines the price of frequency regulation tasks in each time period and the maximum allowable trading power of peak shaving tasks in each time period. The peak shaving power optimization module determines the shaving power for each time period based on the frequency regulation market clearing results, and then performs peak shaving market constraints and clearing.

[0141] The execution module performs ancillary service tasks based on the results of the peak shaving and frequency regulation markets.

[0142] Reference Figure 7 A computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method.

[0143] The following description, using accompanying drawings and embodiments, further illustrates a peak-shaving and frequency regulation market coordination control method that considers energy storage revenue.

[0144] like Figure 2 As shown in the figure, the regional power grid system diagram in this invention includes multiple power sources, and the example system is constructed using data from a week selected from a certain region.

[0145] The total installed capacity of the region is 5000MW, with new energy installed capacity at 1200MW and energy storage installed capacity at 300MW, accounting for 25% of the new energy installed capacity. This simulates a scenario where energy storage is heavily involved in the frequency regulation market and is in a saturated phase. The target for independent energy storage power stations is to use 40MW / 160MWh vanadium redox flow batteries.

[0146] The participants in the peak-shaving auxiliary market in the simulation system are three new energy power plants: wind farm 1 with an installed capacity of 300MW, wind farm 2 with an installed capacity of 350MW, and photovoltaic power plant 1 with an installed capacity of 150MW.

[0147] The simulation system includes 12 frequency regulation entities participating in the frequency regulation auxiliary market: 5 energy storage power stations, 5 thermal power plants, and 2 hydropower plants. The historical frequency regulation performance indicators of each entity are shown in Table 2, and the installed capacity and adjustable frequency capacity of each entity are shown in Table 3.

[0148] Table 1 Frequency modulation performance indicators of frequency modulation resources

[0149]

[0150] Table 2 Adjustable Capacity of Frequency Modulation Resources

[0151]

[0152]

[0153] The table below shows the economics of the three methods:

[0154] Table 3 Economic feasibility of the target energy storage power station

[0155]

[0156] As shown in the table above, the revenue of an independent energy storage power station participating only in peak shaving tasks is 2.3511 million yuan, the revenue of participating only in peak shaving tasks is 2.8494 million yuan, while the revenue of the comprehensive control strategy for one week is 4.3943 million yuan, which is 186.90% of that of frequency regulation only and 154.22% of that of frequency regulation only, far exceeding the revenue of participating in only one ancillary service.

[0157] The table below shows the battery power utilization rates for the three methods:

[0158] Table 4 Battery Utilization Rate of Target Energy Storage Power Station

[0159]

[0160] As shown in the table above, the battery power utilization rate of an independent energy storage power station participating only in peak shaving tasks is 54.46%, and the battery power utilization rate of a station participating only in peak shaving tasks is 48.65%. However, the battery power utilization rate of a comprehensive control strategy is 70.61% for one week, which is 129.65% of that of frequency regulation only and 145.14% of that of frequency regulation only. This is far higher than the battery power utilization rate of a station participating only in one ancillary service.

[0161] Depend on Figure 3 , Figure 4 , Figure 5 It can be seen that when an energy storage power station participates only in the peak shaving market, the energy storage SOC remains unchanged for 7 hours, meaning that the energy storage has no scheduled charging or discharging tasks for 7 hours. When an energy storage power station participates only in the frequency regulation market, the energy storage SOC remains unchanged for 8 hours, meaning that the energy storage has no scheduled charging or discharging tasks for 8 hours. However, when an energy storage power station coordinates participation in both markets, the energy storage SOC remains unchanged for only 5 hours. This means that the energy storage utilization rate of an energy storage power station using coordinated control is better than that of an energy storage power station participating in only one ancillary service market.

[0162] It is evident that this scheme, by coordinating the participation of energy storage power stations in two markets, enables energy storage power stations to coordinate peak shaving and frequency regulation ancillary services, thereby increasing the economic efficiency of energy storage power stations and significantly increasing the battery utilization rate of energy storage systems.

[0163] The calculation conditions, illustrations, etc. in the embodiments of this invention are only used to further illustrate the invention and are not exhaustive. They do not constitute a limitation on the scope of protection of the claims. Those skilled in the art, based on the inspiration gained from the embodiments of this invention, can conceive of other substantially equivalent alternatives without inventive effort, all of which are within the scope of protection of this invention.

Claims

1. A method for coordinated control of the peak-shaving and frequency regulation market that considers energy storage revenue, characterized in that, The method includes establishing an expected revenue calculation model, a pricing model, and a peak-shaving power setting model; coordinating the two ancillary service markets; and generating frequency regulation and peak-shaving task curves with the goal of optimal economic efficiency. Specific details include: Based on the quotations and intended trading power of new energy power plants, independent energy storage power plants conduct simulated power constraints and simulated market clearing to obtain expected peak-shaving benefits; Based on the power frequency regulation demand curve released by the power dispatching agency, the expected frequency regulation revenue of independent energy storage is calculated. Based on the expected peak-shaving revenue and the expected frequency regulation revenue, the difference between the expected peak-shaving and frequency regulation revenues is calculated. The expression for calculating the difference between the expected peak-shaving and frequency regulation revenues is as follows: The difference between the hourly peak-shaving revenue and the frequency regulation revenue calculated based on the highest winning bid during peak-shaving charging periods: ，（1） The difference between the hourly peak-shaving revenue and the frequency regulation revenue calculated based on the highest winning bid during the peak-shaving discharge period: ，（2） in, Peak-shaving revenue per hour for charging during peak hours. To achieve the expected benefits of frequency modulation, The hourly revenue from discharge during peak shaving periods; Based on the revenue difference for each time period and the energy storage SOC, a frequency regulation pricing scheme is formulated. The formulation of this scheme first requires selecting the execution period for the frequency regulation task based on the energy storage SOC and the expected revenue difference, including: The revenue difference is calculated during the charging period, and the maximum rechargeable time when the battery has the lowest capacity is calculated based on the battery's rated charging power and rated capacity. And determine the number of chargeable hours at the start of the peak shaving and frequency regulation phase based on the previous peak shaving and frequency regulation phase. T Calculate the period with the greatest benefit during peak-shaving charging. T Hour: ，（3） The difference in returns is maximized during the discharge period. Hours: ，（4） ，（5） In the formula, The maximum capacity beyond the frequency regulation capacity is reserved for independent energy storage power stations. A minimum capacity beyond frequency regulation capacity is reserved for independent energy storage power stations; The frequency regulation market will be cleared through competitive bidding based on the bidding proposals of various frequency regulation entities. The peak shaving market will be cleared based on the frequency regulation results of the target independent energy storage power stations, as well as power and capacity constraints. The simulated power constraint and simulated market clearing stipulate that the transaction power of an independent energy storage power station at any given time should not exceed its rated charging power, and the clearing should be based on the bidding prices of the peak-shaving applicants. During the initial trading session of the trading day, wind power and photovoltaic new energy power plants submit bid curves to independent energy storage power plants. and Intended Transaction Power Curve At this point, the internal control system of the independent energy storage power station performs power constraints and simulates clearing processes based on the peak-shaving application situation, and obtains the winning bid price curve after the simulated peak-shaving market ends. and the winning power curve ; The formulation of the aforementioned frequency modulation price includes: Benefits from historical average peak-shaving discharge time The moment with the largest difference The frequency modulation revenue at each time point is compared to obtain... Less than At the moment, when After that moment, The peak-shaving discharge is scheduled at a certain time. In the frequency regulation market quotation, the quotation is the unit price after the peak-shaving revenue is converted. for T Each charging period and T During each discharge period, the profit difference is used to calculate the frequency modulation and peak shaving scheme with the highest profit: charging phase. The first hour is allocated for peak shaving tasks, and the remaining hours are allocated for frequency regulation tasks, during the discharge phase. One hour is allocated for peak shaving tasks, and the remaining hours are allocated for frequency regulation tasks; Peak shaving and frequency regulation are carried out according to the situation of the peak shaving and frequency regulation market.

2. The peak-shaving and frequency regulation market coordination control method considering energy storage revenue as described in claim 1, characterized in that, The expected peak-shaving benefits are as follows: Regarding the revenue of energy storage power stations undertaking peak shaving tasks per hour The solution formula is: ，（6） In the formula, n It refers to the number of new energy power stations; hourly revenue from charging during peak hours for: ，（7） hourly revenue from discharge during peak shaving periods for: ，（8） In the formula, This refers to the total number of successful bids for charging during the peak shaving phase. This refers to the unit price of electricity sales; This refers to the rated power of the energy storage power station.

3. The peak-shaving and frequency regulation market coordination control method considering energy storage revenue as described in claim 1, characterized in that, The highest expected winning bid was obtained by the independent energy storage power station based on the power frequency regulation demand curve published by the power dispatching agency. The lowest winning bid price for each frequency regulation demand derived from a simulated frequency regulation market for independent energy storage power stations. and expected winning bid capacity The highest bid required for a target independent energy storage system to win a bid is calculated based on the lowest winning bid price and the expected winning bid capacity. : ，（9） In the formula: K The comprehensive frequency regulation performance index of the target energy storage power station, This refers to the comprehensive frequency regulation performance indicators of critically selected energy storage power stations.

4. The peak-shaving and frequency regulation market coordination control method considering energy storage revenue as described in claim 1, characterized in that, The expression for the expected revenue from frequency modulation is: Regarding the revenue of energy storage power stations undertaking frequency regulation tasks per hour The solution formula is: ，（10） In the formula: This represents the equivalent number of actions taken by the energy storage power station to participate in frequency regulation tasks for each time period.

5. The peak-shaving and frequency regulation market coordination control method considering energy storage revenue as described in claim 1, characterized in that, The aforementioned peak-shaving market clearing is determined through power constraints, including: Based on the clearing results of the frequency regulation market, the peak-shaving power of the energy storage power station for each time period and the maximum rechargeable capacity during the peak-shaving charging phase are determined and constrained, and finally the peak-shaving market clearing is implemented.

6. A peak-shaving and frequency regulation market coordination control system considering energy storage revenue, employing the peak-shaving and frequency regulation market coordination control method considering energy storage revenue as described in any one of claims 1 to 5, characterized in that, The system includes: The acquisition module is used to acquire the peak-shaving demand of new energy power plants and the frequency regulation demand of the power grid; The market module is used to conduct market bidding and clearing to obtain the winning power and price; The revenue calculation module is used to calculate the expected peak-shaving revenue and the expected frequency regulation revenue, and provides the revenue basis for subsequent modules based on the revenue difference; The frequency regulation pricing module determines whether to perform peak shaving or frequency regulation tasks for each time period based on the revenue difference, and sets the frequency regulation price according to the set task. The peak-shaving power optimization module determines the scalable peak power for each time period based on the clearing results of the frequency regulation market, and then performs constraints and clearing of the peak-shaving market. The execution module performs ancillary service tasks based on the results of the peak shaving and frequency regulation markets.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the peak shaving and frequency regulation market coordination control method as described in any one of claims 1 to 5, which takes into account energy storage revenue.

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