Energy storage power station and energy storage operation method participating in power spot market

Abstract

The application discloses an energy storage power station and an energy storage operation method for participating in a power spot market. The method comprises the following steps: generating a day-ahead market settlement price prediction curve according to a day-ahead market price prediction curve and a day-ahead market settlement rule; generating a future day full charging and full discharging arbitrage sequence combination set of the energy storage power station according to the day-ahead market settlement price prediction curve; and selecting a full charging and full discharging arbitrage sequence combination with the highest arbitrage spread from the future day full charging and full discharging arbitrage sequence combination set as a target full charging and full discharging arbitrage sequence combination of the energy storage power station in a future day, and controlling the energy storage power station to operate according to the target full charging and full discharging arbitrage sequence combination. The method can comprehensively consider the energy storage life, market mechanism and other constraints, quickly give an optimal arbitrage operation strategy of the energy storage power station for one day according to the settlement price prediction curve, and control the energy storage power station to operate, thereby improving the control effect of the energy storage power station on peak load shifting and valley load filling of the power grid.

Description

Technical Field

[0001] This application relates to the field of energy storage operation technology, and in particular to an energy storage power station and an energy storage operation method for participating in the electricity spot market. Background Technology

[0002] Driven by dual-carbon goals, the proportion of new energy installed capacity in the power system continues to rise. However, the volatility and intermittency of photovoltaic and wind power pose significant challenges to the stability of the power system, necessitating a large amount of flexible adjustment resources. Electrochemical-based energy storage, as a rechargeable and rapidly responding flexible resource, plays a crucial role on the power generation, grid, and user sides. However, energy storage currently faces challenges such as high costs and difficulties in cost mitigation.

[0003] As a component of the electricity market system, the electricity spot market plays a crucial role in discovering real-time electricity prices, accurately reflecting supply and demand, and achieving peak shaving in the power system. However, current energy storage operation strategies only consider the impact of peak-valley electricity prices and cannot adapt to changes in the real-time electricity price curve in the electricity spot market. This results in poor control of peak shaving and valley filling of electricity consumption by energy storage power stations. Summary of the Invention

[0004] Based on the shortcomings of the existing technology, this application provides an energy storage power station and an energy storage operation method for participating in the electricity spot market. It can control the operation of the energy storage power station by considering various limiting factors such as the service life and charge / discharge rate of the energy storage battery and the constraints of the electricity spot market. This solves the problem that the existing energy storage operation strategy only considers the impact of peak and valley electricity prices and cannot follow the changes in the real-time electricity price curve in the electricity spot market, resulting in poor control effect of the energy storage power station on the peak shaving and valley filling of the power grid.

[0005] To achieve the above objectives, this application provides the following technical solution:

[0006] The first aspect of this application provides a method for operating energy storage to participate in the electricity spot market, including:

[0007] Based on the day-ahead market electricity price forecast curve and the day-ahead market settlement rules, generate the day-ahead market settlement electricity price forecast curve;

[0008] Based on the aforementioned day-ahead market settlement electricity price forecast curve, a set of future daily full-charge and discharge arbitrage sequences for energy storage power stations is generated;

[0009] The full-full-full-release arbitrage sequence combination with the highest arbitrage price difference is selected from the set of full-full-release arbitrage sequence combinations for the future date as the target full-full-release arbitrage sequence combination for the energy storage power station for the future date, and the energy storage power station is controlled to operate according to the target full-full-release arbitrage sequence combination.

[0010] Optionally, in the above-mentioned method for operating energy storage participating in the electricity spot market, generating a day-ahead market settlement price forecast curve based on the day-ahead market price forecast curve and the day-ahead market settlement rules includes:

[0011] Determine the minimum settlement time in the aforementioned day-ahead market settlement rules;

[0012] Using the minimum settlement time as the settlement electricity price unit time, the average electricity price corresponding to each settlement electricity price unit time of the day-ahead market electricity price forecast curve is calculated. The average electricity price corresponding to each settlement electricity price unit time is: the average value of each electricity price forecast point of the day-ahead market electricity price forecast curve within the corresponding settlement unit electricity price time.

[0013] The day-ahead market electricity price forecast curve is generated by taking the average electricity price of all the day-ahead market electricity price forecast curves at each settlement electricity price unit time as the settlement electricity price forecast sequence.

[0014] Optionally, in the above-described method for operating energy storage in the electricity spot market, based on the day-ahead market settlement price forecast curve, a set of future daily full-charge and release arbitrage sequences for the energy storage power station is generated, including:

[0015] Determine whether the energy consumption of the energy storage power station during a single venting operation is greater than the minimum settlement time in the day-ahead market calculation rules;

[0016] If it is determined that the energy consumption time of a single venting of the energy storage power station is not greater than the minimum settlement time in the day-ahead market calculation rules, then the future day full-full-venting arbitrage sequence combination set is generated based on the original concave points and original convex points on the day-ahead market settlement electricity price prediction curve.

[0017] If it is determined that the energy storage power station's single-stage venting time is greater than the minimum settlement time in the day-ahead market calculation rules, then the original concave points and original convex points on the day-ahead market settlement price prediction curve are expanded to obtain expanded concave points and expanded convex points on the day-ahead market settlement price prediction curve. Based on the original concave points, the original convex points, the expanded concave points, and the expanded convex points, the future day full-full-venting arbitrage sequence combination set is generated.

[0018] Optionally, in the above-described method for operating energy storage systems participating in the electricity spot market, the energy consumption of a single venting operation of the energy storage power station is inversely proportional to the battery charge / discharge rate of the energy storage power station.

[0019] Optionally, in the above-described method for operating energy storage participating in the electricity spot market, the original concave points and convex points on the day-ahead market settlement price forecast curve are expanded to obtain expanded concave points and expanded convex points on the day-ahead market settlement price forecast curve, including:

[0020] Determine the target expansion factor;

[0021] The original concave points and convex points on the day-ahead market settlement electricity price forecast curve are respectively expanded to the target expansion multiple according to the corresponding expansion principle to obtain the expanded concave points and expanded convex points on the day-ahead market settlement electricity price forecast curve;

[0022] The expansion principle corresponding to the original concave point includes: finding settlement price prediction points with adjacent time on both sides of the original concave point; the expansion principle corresponding to the original convex point includes: finding settlement price prediction points with adjacent time on both sides of the original convex point.

[0023] Optionally, in the above-described method for operating energy storage participating in the electricity spot market, determining the target expansion factor includes:

[0024] The target expansion factor is calculated based on the energy storage power station's single venting time and the minimum settlement time in the day-ahead market calculation rules.

[0025] Optionally, in the above-mentioned method for energy storage operation in the electricity spot market, the expansion principle corresponding to the original concave point also includes: finding the closest value on both sides of the original concave point without allowing jumps, and / or, the search range cannot skip adjacent convex points, corresponding to the settlement price prediction point;

[0026] The expansion principle corresponding to the original convex point also includes: finding the closest value on both sides of the original convex point without allowing jumps, and / or, the search range cannot skip adjacent concave points, corresponding to the settlement electricity price prediction point.

[0027] Optionally, in the above-described method for operating energy storage participating in the electricity spot market, generating the future full-fill-release arbitrage sequence combination set based on the original concave point, the original convex point, the extended concave point, and the extended convex point includes:

[0028] Each of the original concave points and each of the extended concave points are respectively regarded as each chargeable period of the energy storage power station, and each of the original convex points and each of the extended convex points are respectively regarded as each dischargeable period of the energy storage power station.

[0029] Based on the number of charging and discharging periods required for the target number of arbitrage opportunities in the future days, a corresponding number of periods are selected from all the rechargeable periods and all the discharging periods and arranged in combination to obtain the set of full charge and discharge arbitrage sequences for the future days; the number of charging and discharging periods required for the target number of arbitrage opportunities in the future days is calculated based on the target number of arbitrage opportunities in the future days, the time consumed by the energy storage power station in one empty discharge, and the minimum settlement time in the day-ahead market calculation rules;

[0030] Based on the existing concave and convex points on the day-ahead market settlement electricity price forecast curve, the set of future day full-full-lower arbitrage sequence combinations is generated, including:

[0031] Each of the original concave points on the day-ahead market settlement electricity price forecast curve is taken as a charging period of the energy storage power station, and each of the original convex points on the day-ahead market settlement electricity price forecast curve is taken as a discharging period of the energy storage power station.

[0032] Based on the number of charging and discharging periods required for the target number of arbitrage operations in the future day, a corresponding number of periods are selected from all the rechargeable periods and all the discharging periods and arranged in combination to obtain the set of full charge and discharge arbitrage sequences for the future day.

[0033] Optionally, in the above-described method for operating energy storage systems participating in the electricity spot market, the process for determining the target number of future daily arbitrage opportunities is as follows:

[0034] The upper limit of the number of full charge / discharge cycles and the upper limit of the number of arbitrage cycles in the future days are determined respectively;

[0035] Determine whether the upper limit of the number of full charge and discharge cycles in the future is less than the upper limit of the number of arbitrage cycles in the future;

[0036] If it is determined that the upper limit of the number of full charge and discharge cycles in the future is not less than the upper limit of the number of arbitrage cycles in the future, then the upper limit of the number of arbitrage cycles in the future will be used as the target number of arbitrage cycles in the future.

[0037] If it is determined that the upper limit of the number of full charge and discharge cycles in the future day is less than the upper limit of the number of arbitrage cycles in the future day, then the upper limit of the number of full charge and discharge cycles in the future day will be used as the target number of arbitrage cycles in the future day.

[0038] Optionally, in the above-described method for operating energy storage participating in the electricity spot market, determining the upper limit of the number of full charge and discharge cycles per future day includes:

[0039] The maximum daily cycle count and the maximum daily full charge / discharge count of the energy storage power station during the battery life cycle are determined respectively.

[0040] The minimum value between the maximum daily cycle count and the maximum daily full charge / discharge count is taken as the upper limit of the future daily full charge / discharge count.

[0041] Optionally, in the above-mentioned method for operating energy storage participating in the electricity spot market, determining the upper limit of the number of future daily arbitrage opportunities includes:

[0042] The number of original concave points and the number of original convex points are determined respectively;

[0043] The minimum value between the number of concave points and the number of convex points is taken as the upper limit of the number of future daily arbitrage opportunities.

[0044] Optionally, the above-described method for operating energy storage systems participating in the electricity spot market, after generating a set of future daily full-charge and release arbitrage sequences for the energy storage power station based on the day-ahead market settlement price forecast curve, further includes:

[0045] Determine the number of full-volume arbitrage sequence combinations in which the arbitrage spread of the future full-volume arbitrage sequence combination is less than the minimum arbitrage spread of each future full-volume arbitrage.

[0046] The fully leveraged arbitrage sequences that meet the preset price difference deletion condition in the future full leveraged arbitrage sequence combination set are deleted to obtain the remaining fully leveraged arbitrage sequences in the future full leveraged arbitrage sequence combination set; wherein, the preset price difference deletion condition is: among the price difference sorting sequences of the fully leveraged arbitrage sequences in the future full leveraged arbitrage sequence combination set with the minimum settlement time as the unit, the sequences whose price difference sorting order is lower than the preset sorting order.

[0047] Based on the number of charging and discharging periods required for the target number of future daily arbitrages, the remaining full-charge and full-discharge arbitrage sequences are recombined in chronological order to obtain the adjusted combination of the full-charge and full-discharge arbitrage series for future days.

[0048] The future full-charge-release arbitrage series adjustment combination is used as the target full-charge-release arbitrage sequence combination for the energy storage power station in the future, and the energy storage power station is controlled to operate according to the target full-charge-release arbitrage sequence combination.

[0049] Optionally, in the above-mentioned method for operating energy storage participating in the electricity spot market, the process for determining the minimum arbitrage spread for each full charge and discharge includes:

[0050] Determine the number of cycles within the battery lifecycle of the energy storage power station;

[0051] Based on the number of cycles within the battery's lifespan, a model is established to predict the target rate of return on investment for the energy storage power station and the day-ahead arbitrage profit of future daily electricity spot market.

[0052] Solve the model to obtain the minimum arbitrage spread for each future full-scale opening and closing.

[0053] Optionally, in the above-described method for operating energy storage systems participating in the electricity spot market, before selecting the full-load arbitrage sequence combination with the highest arbitrage price difference from the set of full-load arbitrage sequence combinations for future days as the target full-load arbitrage sequence combination for the energy storage power station for future days, and controlling the energy storage power station to operate according to the target full-load arbitrage sequence combination, the method further includes:

[0054] Delete the full-full-low arbitrage sequence combinations that meet the preset invalid arbitrage sequence combination conditions from the future day full-full-low arbitrage sequence combination set.

[0055] The condition for meeting the preset invalid arbitrage sequence combination is that the full charge and discharge arbitrage sequence combination has a continuous charging period after full charge or a continuous discharging period after discharge.

[0056] The second aspect of this application provides an energy storage power station, comprising: a controller for controlling the energy storage power station to operate at rated power in accordance with an energy storage operation method for participating in the electricity spot market as disclosed in any of the first aspects.

[0057] This application provides a method for operating energy storage systems participating in the electricity spot market. The method first generates a day-ahead market settlement price forecast curve based on the day-ahead market price forecast curve and the day-ahead market settlement rules. Then, based on the day-ahead market settlement price forecast curve, it generates a set of future full-load-release arbitrage sequence combinations for the energy storage power station. Finally, it selects the full-load-release arbitrage sequence combination with the highest arbitrage price difference from the future full-load-release arbitrage sequence combination as the target full-load-release arbitrage sequence combination for the energy storage power station in the future, and controls the energy storage power station to operate according to the target full-load-release arbitrage sequence combination. In other words, this application can comprehensively consider constraints such as energy storage lifespan and market mechanisms, and quickly provide the optimal arbitrage operation strategy for the energy storage power station for the next day based on the day-ahead market settlement price forecast curve to control the operation of the energy storage power station. This improves the control effect of the energy storage power station on peak shaving and valley filling of the power grid. While solving the problem that existing energy storage operation strategies only consider the impact of peak and valley prices and cannot follow changes in the real-time electricity price curve in the electricity spot market, resulting in poor control effect of the energy storage power station on peak shaving and valley filling of the power grid, it also ensures the maximization of the energy storage power station's revenue. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0059] Figure 1 A flowchart illustrating an energy storage operation method for participating in the electricity spot market, provided as an embodiment of this application;

[0060] Figure 2 A schematic diagram of a day-ahead market electricity price forecast curve provided for an embodiment of this application;

[0061] Figure 3 A flowchart illustrating the generation of a day-ahead market settlement electricity price forecast curve is provided for embodiments of this application.

[0062] Figure 4 A schematic diagram of a day-ahead market settlement electricity price forecast curve provided for an embodiment of this application;

[0063] Figure 5 A flowchart illustrating the generation of a future full-full-open arbitrage sequence combination set provided in this application embodiment;

[0064] Figure 6 An example diagram of the shape of a concave and convex dot provided in an embodiment of this application;

[0065] Figure 7 Another process for generating a future full-full-open arbitrage sequence combination set provided in this application embodiment;

[0066] Figure 8 This application provides a combination of all possible full-open arbitrage sequences for future days without point expansion;

[0067] Figure 9 A flowchart for determining the number of future daily arbitrage opportunities provided in this application embodiment;

[0068] Figure 10 An extended flowchart for increasing the number of concave and convex points is provided for an embodiment of this application;

[0069] Figure 11 This application provides an extended sequence of all possible charge / discharge periods as an embodiment of the present application.

[0070] Figure 12 Another process for generating a future full-full-open arbitrage sequence combination set provided in this application embodiment;

[0071] Figure 13 A flowchart illustrating another energy storage operation method for participating in the electricity spot market, provided as an embodiment of this application;

[0072] Figure 14 A flowchart for determining the minimum arbitrage spread for each full-scale opening and closing in the future, provided as an embodiment of this application;

[0073] Figure 15 A battery cycle life curve is provided as an embodiment of this application;

[0074] Figure 16 A flowchart illustrating another energy storage operation method for participating in the electricity spot market, provided as an embodiment of this application. Detailed Implementation

[0075] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0076] First, it's important to note that with the advancement of new power system construction, from the energy supply side, large-scale integration of new energy units, such as wind and solar power, into the grid will pose challenges to the grid's power balance due to the randomness and volatility of their output. From the energy consumption side, the continuous improvement in terminal electrification levels will lead to a sustained increase in peak loads during seasonal and daily peak hours, widening the peak-to-valley difference. To ensure the safe and stable operation of the system, the grid's demand for flexible peak-shaving resources will significantly increase.

[0077] Currently, power distribution systems typically employ peak shaving and valley filling strategies when allocating and controlling charging and discharging power. This involves introducing energy storage systems into the distribution system and controlling their charging and discharging based on peak and off-peak electricity demand periods. Electricity prices during peak hours are generally higher than those during off-peak hours. The energy storage system charges during off-peak hours to fill these gaps and discharges during peak hours to enhance the grid's power supply capacity, thereby improving the utilization rate of existing power equipment and potentially increasing revenue.

[0078] In response, this application provides an energy storage operation method for participating in the electricity spot market. This method can control the operation of the energy storage power station by considering various limiting factors such as the lifespan and charge / discharge rate of the energy storage battery and the constraints of the electricity spot market. This solves the problem that existing energy storage operation strategies only consider the impact of peak and valley electricity prices and cannot follow the changes in the real-time electricity price curve in the electricity spot market, resulting in poor control of peak shaving and valley filling of the power grid by the energy storage power station.

[0079] Please see Figure 1 The operation method of energy storage participating in the electricity spot market mainly includes the following steps:

[0080] S101. Generate the day-ahead market settlement price forecast curve based on the day-ahead market electricity price forecast curve and the day-ahead market settlement rules.

[0081] In practical applications, the day-ahead electricity price forecast curve can be output through the electricity price forecast module. If the electricity price forecast curve has points spaced 15 minutes apart, totaling 96 points over 24 hours, then... Figure 2 As shown. The 96-point electricity price prediction sequence sorted by time can be: {P1, P2, P3...P...} 96}

[0082] It should be noted that the specific process of executing step S101, generating the day-ahead market settlement price forecast curve based on the day-ahead market electricity price forecast curve and the day-ahead market settlement rules, can be described as follows: Figure 3 As shown, it mainly includes:

[0083] S201. Determine the minimum settlement time in the day-ahead market settlement rules.

[0084] In practical applications, the minimum settlement time in the day-ahead market settlement rules can be determined by arranging the various settlement times stipulated in the day-ahead market settlement rules in ascending order and then selecting the settlement time that ranks first.

[0085] Similarly, the minimum settlement time in the day-ahead market settlement rules can be determined by arranging the various settlement times stipulated in the day-ahead market settlement rules in descending order and then selecting the last settlement time.

[0086] Of course, it is not limited to the above. Depending on the application environment and user needs, other existing methods can be used to determine the minimum settlement time in the day-ahead market settlement rules, all of which are within the scope of protection of this application.

[0087] S202. Using the minimum settlement time as the settlement price unit time, calculate the average electricity price corresponding to each settlement price unit time of the day-ahead market electricity price forecast curve.

[0088] The average electricity price per unit time corresponding to the settlement electricity price can be: the average value of each electricity price prediction point of the day-ahead market electricity price prediction curve within the corresponding settlement unit electricity price time.

[0089] In practical applications, the time axis of the current market electricity price forecast curve can be divided according to the settlement price unit time. This determines each settlement price unit time on the time axis of the current market electricity price forecast curve and the electricity price forecast point falling within each settlement price unit time. Then, for each settlement price unit time, the arithmetic mean of each electricity price forecast point falling within that settlement price unit time is calculated to obtain the average electricity price of the day-ahead market electricity price forecast curve corresponding to each settlement price unit time.

[0090] S203. Take the average electricity price corresponding to each settlement price unit time of all day-ahead market electricity price forecast curves as the settlement price forecast sequence, and generate the day-ahead market settlement price forecast curve.

[0091] In practical applications, the average electricity price for each settlement unit of time on all day-ahead market electricity price forecast curves can be used to replace the corresponding electricity price forecast points on the day-ahead market electricity price forecast curves, thereby generating the day-ahead market settlement electricity price forecast curve.

[0092] It should be noted that in practice, the minimum settlement time t can be taken according to the day-ahead settlement rules in the spot market. j The predicted settlement price sequence is calculated by averaging the predicted point prices within the time frame. If the settlement price is calculated in one-hour increments, the hourly settlement price is equal to the arithmetic mean of the predicted prices for four 15-minute intervals within that time frame. Figure 4 As shown. The settlement price forecast sequence recalculated according to the day-ahead market settlement rules can be: {P j1 P j2 P j3 ...P j24}

[0093] S102. Based on the day-ahead market settlement electricity price forecast curve, generate a set of future daily full-charge and discharge arbitrage sequences for energy storage power stations.

[0094] In practical applications, the specific process of executing step S102, which involves generating a future full-charge-discharge arbitrage sequence combination set for energy storage power stations based on the day-ahead market settlement electricity price forecast curve, can be as follows: Figure 5 As shown, the main steps include S301 to S303:

[0095] S301. Determine whether the energy consumption time for a single venting of the energy storage power station is greater than the minimum settlement time in the day-ahead market calculation rules.

[0096] Among them, the energy consumption of a single venting operation of an energy storage power station can be inversely proportional to the battery charge / discharge rate of the energy storage power station.

[0097] In other words, it can be done through the formula Calculations are performed to obtain the energy consumption time for a single venting operation of the energy storage power station; T represents the energy consumption time for a single venting operation of the energy storage power station, and C represents the energy consumption time for a single venting operation. p This indicates the battery charge / discharge rate of the energy storage power station.

[0098] If it is determined that the energy storage power station's single-stage venting time is not greater than the minimum settlement time in the day-ahead market calculation rules, then step S302 can be executed; if it is determined that the energy storage power station's single-stage venting time is greater than the minimum settlement time in the day-ahead market calculation rules, then step S303 can be executed.

[0099] S302. Based on the existing concave and convex points on the current market settlement electricity price forecast curve, generate a set of future full-load arbitrage sequence combinations.

[0100] In practical applications, it is assumed that the charging and discharging power is the maximum rated power each time, and the battery is in a discharged state at the end of each day. The original convex points on the day-ahead market settlement price forecast curve can be defined as the maximum value point of each peak in the forecast curve, and the original concave points on the day-ahead market settlement price forecast curve can be defined as the minimum value point of each trough in the forecast curve. Generally, the number of original concave and convex points on the day-ahead market settlement price forecast curve is a positive integer greater than or equal to 1.

[0101] It should be noted that there are no restrictions on the methods for determining the original convex and concave points on the current market settlement electricity price forecast curve; methods such as curve differentiation or numerical comparison can be used.

[0102] It should also be noted that the shapes of all possible original concave and convex points on the prediction curve can be as follows: Figure 6 As shown. Among them, Figure 6 If multiple adjacent points with equal values ​​are located at the peaks of the morphological sequence numbers 2, 4, and 6, they are considered as a convex point, and any point can be chosen to represent it; if multiple adjacent points with equal values ​​are located at the troughs of the morphological sequence numbers 8, 10, and 12, they are considered as a concave point, and any point can be chosen to represent it.

[0103] In practical applications, the specific process of executing step S302, which involves generating a set of future full-load arbitrage sequences based on the existing concave and convex points on the day-ahead market settlement electricity price forecast curve, can be described as follows: Figure 7 As shown, it mainly includes steps S401 and S402:

[0104] S401. Each of the original concave points on the day-ahead market settlement electricity price forecast curve is taken as a charging period of the energy storage power station, and each of the original convex points on the day-ahead market settlement electricity price forecast curve is taken as a discharging period of the energy storage power station.

[0105] Assuming the current day-ahead market settlement electricity price forecast curve for this future day has x existing concave points and y existing convex points, then the maximum number of arbitrage opportunities for this future day is C. max =min(x,y). The first existing concave point can be considered as the rechargeable period, and the nearest existing convex point as the dischargeable period. Pairing these points in this order yields C. max For the initial arbitrage charge-discharge sequence combination, ordered chronologically, it can be: {(P j充1 P j放1 ), (P j充2 P j放2 )……(P j充Cmax P j放Cmax This sequence represents the granularity of the settlement electricity price unit, including all original concave points {P}. j充1 P j充2 ...P j充Cmax} are all within the rechargeable period, and all original bumps {P j放1 P j放2 ...P j放Cmax These are all periods when discharge is possible.

[0106] Combination Figure 8 C max =3, all rechargeable periods are: {P j24 P j11 P j17}, All dischargeable periods are: {P j8 P j16 P j21}. The three arbitrage charge-discharge combination sequences, ordered chronologically, can be: {(P j24 P j8 ), (P j11 P j16 ), (P j17 P j21 )}.

[0107] S402. Based on the number of charging and discharging periods required for the arbitrage target number of future days, select the corresponding number of periods from all charging periods and all discharging periods and arrange them in combination to obtain the set of full-charge and full-discharge arbitrage sequences for future days.

[0108] In practical applications, the process of determining the target number of future daily arbitrage opportunities can be as follows: Figure 9 As shown, the main steps include S501 to S504:

[0109] S501, determine the upper limit of the number of full charge and discharge cycles in the future and the upper limit of the number of arbitrage cycles in the future.

[0110] First, the maximum daily cycle count and the maximum daily full charge / discharge count of the energy storage power station during its battery life cycle can be determined separately. Then, the minimum value between the maximum daily cycle count and the maximum daily full charge / discharge count can be used as the upper limit of the future daily full charge / discharge count.

[0111] Specifically, the maximum daily cycle count of an energy storage power station's battery lifespan can be calculated using the maximum cycle count over its battery lifespan, the estimated minimum service life of the energy storage station, and the equivalent number of days of use per year. Let's assume the maximum cycle count over the battery lifespan is M, the estimated minimum service life is n, and the equivalent number of days of use per year is d. e It can be done by M÷n÷d e Calculate the maximum number of daily cycles during the battery lifecycle of the energy storage power station.

[0112] Since the time consumed by an energy storage power station during one empty discharge can be expressed as T, the corresponding time consumed by a full charge of the energy storage power station is also T. Therefore, the maximum number of full charge and discharge cycles of an energy storage power station in 24 hours can be 24 / 2T = 12 / T times.

[0113] Understandably, the future daily maximum number of full-charge and discharge cycles is limited by the estimated minimum service life of the energy storage power station and the battery charge / discharge rate. Specifically, the future daily maximum number of full-charge and discharge cycles, C... y It can be done through formula C y =min(M÷n÷d) e The result is obtained by calculation (12 / T).

[0114] In practice, we can first determine the number of original concave points and the number of original convex points respectively; then we can use the minimum value between the number of concave points and the number of convex points as the upper limit of the number of future daily arbitrage opportunities.

[0115] In other words, assuming the maximum number of arbitrage opportunities per day in the future is C. max If the number of original concave points is x, and the number of original convex points is y, then it can be determined through C. max =min(x,y), which gives the upper limit of the number of arbitrage opportunities in the future.

[0116] S502. Determine whether the upper limit of the number of full charge and discharge cycles in the future is less than the upper limit of the number of arbitrage cycles in the future.

[0117] In practical applications, the upper limit of the number of full-charge and discharge cycles in the future can be compared with the upper limit of the number of arbitrage cycles in the future to determine whether the upper limit of the number of full-charge and discharge cycles in the future is less than the upper limit of the number of arbitrage cycles in the future.

[0118] If it is determined that the upper limit of the number of full charge and discharge cycles in the future is not less than the upper limit of the number of arbitrage cycles in the future, then step S503 can be executed; if it is determined that the upper limit of the number of full charge and discharge cycles in the future is less than the upper limit of the number of arbitrage cycles in the future, then step S504 can be executed.

[0119] S503, Use the upper limit of the number of arbitrage opportunities in the future day as the target number of arbitrage opportunities in the future day.

[0120] In practical applications, if the upper limit of the number of full charge / discharge cycles in the future is greater than the upper limit of the number of arbitrage cycles in the future, then the upper limit of the number of arbitrage cycles in the future can be used as the target number of arbitrage cycles in the future. That is, if C y ≥C max Then C 目标 =C max C 目标 This indicates the number of arbitrage opportunities in the future.

[0121] S504. The upper limit of the number of full charge and discharge cycles in the future day shall be used as the target number of arbitrage cycles in the future day.

[0122] In practical applications, if the maximum number of full-charge / discharge cycles in the future is less than the maximum number of arbitrage cycles in the future, then the maximum number of full-charge / discharge cycles in the future can be used as the target number of arbitrage cycles in the future. That is, if C y <C max Then C 目标 =C y C 目标 This indicates the number of arbitrage opportunities in the future.

[0123] In practical applications, the number of charging and discharging periods required for the future daily arbitrage target can be calculated based on the future daily arbitrage target, the energy storage power station's single venting time, and the minimum settlement time in the day-ahead market calculation rules. Specifically, it can be calculated using the formula a = C. 目标 ×T÷t j The calculation is as follows. In the formula, 'a' represents the number of charging and discharging periods required for the future daily arbitrage target, and C... 目标 t represents the number of future daily arbitrage opportunities, T represents the energy consumption of a single venting operation of the energy storage power station, and t represents the total energy consumption per day. j This indicates the minimum settlement time in the day-ahead market calculation rules.

[0124] Of course, this is not the only possibility. Depending on the specific application environment and user needs, other methods can be used to determine the number of charging and discharging periods required for the future daily arbitrage target, all of which are within the scope of protection of this application.

[0125] Assuming the energy storage power station has m charging periods and n discharging periods, then the total number of permutations and combinations of charging periods is: There are [number] possible combinations of dischargeable time periods. There are [number] arbitrage sequences. By randomly selecting one set from all possible combinations of rechargeable time periods and another set from all possible combinations of discharging time periods, and then combining them again, we can generate a total of [number] arbitrage sequence combinations for the target number of arbitrage opportunities in the future. The seed, that is, the set of combinations of future full-full-full-open arbitrage sequences, includes Arbitrage sequence combinations.

[0126] Assume C 目标 =1,C p =0.5, t j = 1 hour, then T = 2 hours. The number of charging and discharging periods required for one arbitrage operation is a = 1 × 2 ÷ 1 = 2, which means 2 charging periods and 2 discharging periods are needed. Combined with... Figure 8 All possible combinations of charging time periods are: Similarly, all possible combinations of dischargeable time periods are: If there are 3 pairs of arbitrage sequences generated in the future full-scale arbitrage sequence combination set, then there are 3 × 3 = 9 possible arbitrage sequence combinations. Among them, there are 3 pairs of arbitrage sequence combinations with the minimum settlement time as the unit: {(Pj24 P j8 ), (P j11 P j16 ), (P j17 P j21 )}.

[0127] S303. Expand the original concave points and original convex points on the day-ahead market settlement electricity price forecast curve to obtain the expanded concave points and expanded convex points on the day-ahead market settlement electricity price forecast curve. Based on the original concave points, original convex points, expanded concave points and expanded convex points, generate a set of future day full-full-full-release arbitrage sequence combinations.

[0128] In practical applications, the specific process of expanding the original concave and convex points on the day-ahead market settlement electricity price forecast curve in step S303 to obtain the expanded concave and convex points on the day-ahead market settlement electricity price forecast curve can be described as follows: Figure 10 As shown, it mainly includes steps S601 and S602:

[0129] S601. Determine the target expansion factor.

[0130] The target expansion factor can be calculated based on the energy storage power station's single-pass venting time and the minimum settlement time in the day-ahead market calculation rules.

[0131] Specifically, assuming the time consumed by a single venting operation of an energy storage power station is T, and the minimum settlement time in the day-ahead market calculation rules is t. j Then it can be done by T÷t j -1 is used to calculate the target expansion factor.

[0132] In practical applications, the number of existing convex and concave points on the day-ahead market settlement electricity price forecast curve is generally expanded by the same multiple.

[0133] S602. The original concave points and convex points on the day-ahead market settlement electricity price forecast curve are expanded to the target expansion multiple according to the corresponding expansion principle, so as to obtain the expanded concave points and expanded convex points on the day-ahead market settlement electricity price forecast curve.

[0134] Among them, the expansion principle corresponding to the original concave point can only consider finding the settlement price prediction points that are adjacent in time on both sides of the original concave point; the expansion principle corresponding to the original convex point can only consider finding the settlement price prediction points that are adjacent in time on both sides of the original convex point.

[0135] In some embodiments, the extension principle corresponding to the original concave point can also consider finding the settlement price prediction points corresponding to adjacent times on both sides of the original concave point, while considering the closest value and not allowing jumps, and / or, the search range cannot skip the settlement price prediction points corresponding to adjacent convex points; similarly, the extension principle corresponding to the original convex point can also only consider: finding the settlement price prediction points corresponding to adjacent times on both sides of the original convex point, and further considering the closest value and not allowing jumps, and the search range cannot skip the settlement price prediction points corresponding to adjacent concave points; it can be determined according to the specific application environment and user needs, and all are within the protection scope of this application.

[0136] In practical applications, all rechargeable periods of the expanded energy storage power station can be represented as: {P j充1 P j充2 ... Pj充m There are m periods in total. All dischargeable periods of the extended energy storage power station can be represented as: {P} j放1 P j放2 ...P j放n There are n in total.

[0137] exist Figure 8 Based on this, assume C p =0.5, T=2 hours, t j = 1 hour, then the number of existing concave and convex points on the day-ahead market settlement electricity price forecast curve needs to be doubled, that is, find one more point next to the existing convex and concave points on the day-ahead market settlement electricity price forecast curve, such as Figure 11 As shown, the extended concave point can be: {P j1 P j12 P j18}, the extended convex point can be: {P j7 P j15 P j22}

[0138] For practical applications, please refer to Figure 12 The specific process of generating a set of future full-full-open arbitrage sequences based on the original concave points, original convex points, extended concave points, and extended convex points in step S303 mainly includes steps S701 to S702:

[0139] S701. Each original concave point and each extended concave point are respectively regarded as each chargeable period of the energy storage power station, and each original convex point and each extended convex point are respectively regarded as each dischargeable period of the energy storage power station.

[0140] Similarly combined Figure 11 After expansion, all available charging periods for the energy storage power station are: {P j24 P j1 P j11 Pj12 P j17 P j18 There are a total of 6. The expanded energy storage power station covers all available release points during the specified time periods {P}. j7 P j8 P j15 P j16 P j21 P j22 There are 6 in total.

[0141] S702. Based on the number of charging and discharging periods required for the target number of arbitrage opportunities in the future day, select the corresponding number of periods from all rechargeable periods and all discharging periods and arrange them in combination to obtain a set of full charge and discharge arbitrage sequences for the future day.

[0142] It should be noted that the process of determining the number of future daily arbitrage targets in step S702, and the number of charging and discharging periods required for the number of future daily arbitrage targets, are no different from those in step S402, and can be referred to each other. They will not be repeated here.

[0143] Assume C p =0.5, C 目标 =2,t j = 1 hour, then T = 2 hours. The number of charging and discharging periods required for two arbitrage operations is a = 2 × 2 ÷ 1 = 4. Therefore, 4 charging periods and 4 discharging periods are needed. Figure 11 All possible combinations of charging time periods are: Similarly, all possible combinations of dischargeable time periods are: If there are 15 pairs of arbitrage sequences generated in the future full-scale arbitrage sequence combination set, then there are 15 × 15 = 225 possible arbitrage sequence combinations. Among them, there are 4 pairs of arbitrage sequence combinations with the minimum settlement time as the unit: {(P j24 P j7 ), (P j11 P j15 ), (P j12 P j16 ), (P j17 P j21 )}.

[0144] S103. Select the full-full-full-release arbitrage sequence combination with the highest arbitrage price difference from the set of full-full-release arbitrage sequence combinations for the future date as the target full-full-release arbitrage sequence combination for the energy storage power station for the future date, and control the energy storage power station to operate according to the target full-full-release arbitrage sequence combination.

[0145] In practical applications, for each full-charge-discharge arbitrage sequence combination in the future daily full-charge-discharge arbitrage sequence combination set, the arbitrage price difference of the full-charge-discharge arbitrage sequence combination can be obtained by summing the settlement prediction point value corresponding to all discharge periods in the arbitrage sequence combination and subtracting the settlement prediction electricity price corresponding to all charging periods in the arbitrage sequence combination.

[0146] It should be noted that after obtaining the arbitrage difference of each full-full-release arbitrage sequence combination in the future full-full-release arbitrage sequence combination set through the above method, the full-full-release arbitrage sequence combination combination with the largest arbitrage difference can be selected from the energy storage power station's target full-full-release arbitrage sequence combination in the future, and the energy storage power station can be controlled to charge and discharge at rated power according to the chargeable and dischargeable periods in the target full-full-release arbitrage sequence combination.

[0147] Based on the above principles, the energy storage operation method for participating in the electricity spot market provided in this embodiment first generates a day-ahead market settlement price forecast curve based on the day-ahead market price forecast curve and the day-ahead market settlement rules; then, based on the day-ahead market settlement price forecast curve, it generates a set of future full-charge-release arbitrage sequence combinations for the energy storage power station; finally, it selects the full-charge-release arbitrage sequence combination with the highest arbitrage price difference from the set of future full-charge-release arbitrage sequence combinations as the target full-charge-release arbitrage sequence combination for the energy storage power station in the future, and controls the energy storage power station to operate according to the target full-charge-release arbitrage sequence combination. In other words, this application can comprehensively consider the lifespan constraints and market mechanism constraints of energy storage (especially electrochemical energy storage), and quickly provide the optimal arbitrage operation strategy for the energy storage power station for the next day based on the day-ahead market settlement price forecast curve to control the operation of the energy storage power station. This improves the control effect of the energy storage power station on the peak shaving and valley filling of the power grid. While solving the problem that the existing energy storage operation strategy only considers the impact of peak and valley electricity prices and cannot follow the changes in the real-time electricity price curve in the electricity spot market, resulting in poor control effect of the energy storage power station on the peak shaving and valley filling of the power grid, it can also ensure the maximization of the energy storage power station's revenue.

[0148] Furthermore, this application utilizes a graphical method to quickly eliminate interfering arbitrage combinations by identifying the peaks and troughs in the battery prediction curve of the energy storage power station. Moreover, this application can flexibly utilize various electricity spot market rules and energy storage power stations with different charge / discharge rate configurations to achieve refined control. Finally, it is also compatible with changes in parameters such as the battery lifespan of the energy storage power station, the annual equivalent number of days of use of the power station, and the estimated minimum service life of the energy storage power station, allowing for dynamic adjustment of the energy storage arbitrage operation strategy to ensure the expected returns for investors.

[0149] Alternatively, in another embodiment provided in this application, please refer to Figure 13After performing step S102 and generating a set of future daily full-charge-discharge arbitrage sequences for the energy storage power station based on the day-ahead market settlement price forecast curve, the energy storage operation method participating in the electricity spot market may further include:

[0150] S801. Determine the number of full-volume arbitrage sequence combinations in which the arbitrage spread of future full-volume arbitrage sequences is less than the minimum arbitrage spread of each future full-volume arbitrage.

[0151] In practical applications, the process of determining the minimum arbitrage spread for each full-scale release can be as follows: Figure 14 As shown, the main steps include S901 to S903:

[0152] S901. Determine the number of cycles within the battery lifecycle of the energy storage power station.

[0153] In practical applications, since the remaining effective capacity (EOL) and charge / discharge rate (C) of the battery at the end of the battery lifespan of the energy storage power station are known... p By consulting the battery characteristic table, the maximum number of cycles M within the battery lifecycle of the energy storage power station corresponding to EOL can be obtained.

[0154] Battery characteristic data sheets are generally provided by the battery manufacturer; details can be found in, for example... Figure 15 As shown.

[0155] S902. Based on the number of cycles within the battery's lifespan, a model is established to determine the target rate of return for energy storage power stations and the day-ahead arbitrage profit of future daily electricity spot market.

[0156] In practical applications, if we assume that the maximum number of battery cycles M over its lifespan is averaged over future years, and that the average number of cycles used each year can be fully utilized, then the number of battery cycles available each year in the future, m = M ÷ n; the annual spot arbitrage profit = ΔP × m; the annual profit of the energy storage power station = annual spot arbitrage profit + annual other profit I. i Annual net revenue of energy storage power station = Annual income of energy storage power station - Annual operating cost C i Let F be the net income in year i. i =ΔP×m+I i -C i —(1), then the annual net income sequence of the energy storage power station is as follows: {F1, F2, F3……F n Using the IRR calculation formula Substituting into equation (1), we get

[0157] Among them, IIR min C represents the estimated minimum internal rate of return for the energy storage power station, and C represents the initial investment cost.

[0158] In other words, the model for the target rate of return on investment of this energy storage power station and the future daily electricity spot market arbitrage profit is as follows:

[0159] S903. Solve the model to obtain the minimum arbitrage spread for each future full-scale opening and closing.

[0160] Since the model of the investment target rate of return of energy storage power station and the future daily electricity spot market arbitrage profit has a unique unknown, the minimum arbitrage difference ΔP for each full charge and discharge, it can be obtained by solving it.

[0161] It should be noted that, in addition to the specific methods shown above for determining the minimum arbitrage spread for each full charge and discharge in the future, in actual operation, changes in parameters such as power station revenue and operating costs, the expected life cycle of the energy storage power station, and the annual equivalent utilization days of the power station can be considered. The number of cycles within the actual battery life cycle can be counted, and the above steps can be repeated in stages to dynamically adjust the minimum arbitrage spread △P for each full charge and discharge in the future.

[0162] In practical applications, for each full-charge-discharge arbitrage sequence combination in the future daily full-charge-discharge arbitrage sequence combination set, the arbitrage spread for each full-charge-discharge arbitrage sequence combination can be obtained by summing the settlement forecast electricity prices corresponding to all discharge periods in the arbitrage sequence combination and subtracting the settlement forecast electricity prices corresponding to all charging periods in the arbitrage sequence combination. Then, the arbitrage spread of each full-charge-discharge arbitrage sequence combination is compared with the minimum arbitrage spread for each full-charge-discharge in the future to obtain the number of full-charge-discharge arbitrage sequence combination combinations in the future daily full-charge-discharge arbitrage sequence combination set whose arbitrage spread is less than the minimum arbitrage spread for each full-charge-discharge in the future.

[0163] It should be noted that after obtaining the arbitrage difference of each full-full-release arbitrage sequence combination in the future full-full-release arbitrage sequence combination set through the above method, the full-full-release arbitrage sequence combination combination with the largest arbitrage difference can be selected from the energy storage power station's target full-full-release arbitrage sequence combination in the future, and the energy storage power station can be controlled to charge and discharge at rated power according to the chargeable and dischargeable periods in the target full-full-release arbitrage sequence combination.

[0164] In other words, the number of future daily arbitrage opportunities C can be calculated. 目标 For each arbitrage spread, count the number of arbitrage spreads (b) that are less than ΔP.

[0165] S802. Delete the full-volume arbitrage sequences that meet the preset price difference deletion conditions from the full-volume arbitrage sequence combination set for the future day, and obtain the remaining full-volume arbitrage sequences from the full-volume arbitrage sequence combination set for the future day.

[0166] The preset price difference deletion condition is as follows: among the price difference sorting sequences of fully open arbitrage sequences in the future full open arbitrage sequence combination set with the minimum settlement time as the unit, the sequence whose price difference sorting order is lower than the preset sorting order, and the preset sorting order is b×T÷t. j 'b' represents the number of full-volume arbitrage sequences where the concentrated arbitrage spread is less than the minimum arbitrage spread for each full-volume arbitrage in the future, and 'T' represents the energy consumption of a single venting operation at the energy storage power station. j This indicates the minimum settlement time in the day-ahead market calculation rules.

[0167] In practice, we can calculate the price difference of arbitrage sequences 'a' in the future full-scale arbitrage sequence combination set, with the minimum settlement time as the unit, sort them from low to high, and remove b×T÷t. j For low-difference sequences, the remainder (C) 目标. -b)×T÷t j For arbitrage sequences.

[0168] S803. Based on the number of charging and discharging periods required for the target number of arbitrage opportunities in the future day, the remaining sequences of each full-charge-discharge arbitrage are recombined in chronological order to obtain the adjusted combination of the full-charge-discharge arbitrage series for the future day.

[0169] In practical applications, the remaining full-full-full arbitrage sequences can be recombined in chronological order based on the number of charging and discharging periods required for future arbitrage targets, thus obtaining adjusted combinations of future full-full-full arbitrage series.

[0170] Among them, the future full-day arbitrage series adjustment portfolio includes (C) 目标. -b) For full-charge-discharge arbitrage sequence combinations, each full-charge-discharge arbitrage combination defines the charge / discharge period and power magnitude.

[0171] It should be noted that power is generally defined as rated power, but it is not limited to this and can be determined according to the specific application environment and user needs. This application does not make specific limitations, and all of them are within the protection scope of this application.

[0172] S804. The future full-load arbitrage series adjustment combination is used as the target full-load arbitrage sequence combination for the energy storage power station in the future, and the energy storage power station is controlled to operate according to the target full-load arbitrage sequence combination.

[0173] In practical applications, the future full-charge-discharge arbitrage series adjustment combination can be directly used as the target full-charge-discharge arbitrage sequence combination for the energy storage power station in the future, and the energy storage power station can be controlled to charge and discharge at rated power according to the chargeable and discharge periods in the target full-charge-discharge arbitrage sequence combination.

[0174] Assume Cp =0.5, C 目标 =2,t j =1 hour, combined Figure 9 Then, the future daily fully-loaded arbitrage series adjustment combination can be {[(P j24 P j1 )charge, (P j7 P j8 ) release], [(P j11 P j12 )charge, (P j21 P j22 )put]}.

[0175] It should be noted that by recombining the remaining sequences of each full-load arbitrage series in chronological order to obtain the future full-load arbitrage series adjustment combination, the charging and discharging of the energy storage power station can be directly controlled according to the charging and discharging periods in each future full-load arbitrage series adjustment combination, thereby improving the control and execution convenience of the energy storage power station.

[0176] Based on the above, the energy storage operation method for participating in the electricity spot market provided in this embodiment can further, after generating a future full-load and release arbitrage sequence combination set of the energy storage power station based on the day-ahead market settlement price prediction curve, verify the future full-load and release arbitrage sequence combination set based on the minimum arbitrage difference for each future full-load and release, and obtain an adjustment combination of the future full-load and release arbitrage series to control the operation of the energy storage power station. This solves the problem that existing energy storage operation strategies only consider the impact of peak and valley electricity prices and cannot follow changes in the real-time electricity price curve in the electricity spot market, resulting in poor control effect of energy storage power stations on peak shaving and valley filling of the power grid. At the same time, it further achieves the goal of maximizing the revenue of the energy storage power station. From the investor's perspective, considering the actual return model, the strategy optimizes the day-ahead market arbitrage strategy for energy storage systems, aiming to achieve the minimum return on investment throughout the entire lifecycle of the energy storage power station. Furthermore, it establishes a model that correlates the long-term return on investment target with the daily arbitrage profit in the current electricity spot market, simplifying strategy generation complexity. In addition, while accommodating changes in parameters such as the battery lifecycle, the equivalent number of days of annual use of the power station, and the estimated minimum service life of the energy storage power station, it also dynamically adjusts the daily arbitrage target number and the minimum arbitrage spread for each full charge and release, thereby dynamically adjusting the daily day-ahead market arbitrage plan to ensure the investor's expected returns.

[0177] Alternatively, in another embodiment provided in this application, please refer to Figure 16Before executing step S103, selecting the full-full-full-release arbitrage sequence combination with the highest arbitrage spread from the set of full-full-release arbitrage sequence combinations for future days as the target full-full-release arbitrage sequence combination for the energy storage power station on future days, and controlling the energy storage power station to operate according to the target full-full-release arbitrage sequence combination, the following may also be included:

[0178] S1001. Delete the full-full-low arbitrage sequence combinations that meet the preset invalid arbitrage sequence combination conditions from the future full-full-low arbitrage sequence combination combination set.

[0179] Among them, the conditions for a preset invalid arbitrage sequence combination are: the full charge and discharge arbitrage sequence combination has a continuous charging period after full charge or a continuous discharging period after discharge.

[0180] In other words, if the battery is completely discharged and then immediately becomes available for discharge, the arbitrage sequence combination is invalid; or if the battery is fully charged and then immediately becomes available for recharging, the arbitrage sequence combination is invalid.

[0181] In practical applications, since the future full-charge-discharge arbitrage sequence combination set is obtained by selecting the corresponding number of charging and discharging periods from all charging periods and all discharging periods based on the number of charging and discharging periods required for the future arbitrage target number, without considering whether each full-charge-discharge arbitrage sequence combination in the future full-charge-discharge arbitrage sequence combination set can be realized in light of actual conditions, it is necessary to delete invalid arbitrage sequence combinations in the future full-charge-discharge arbitrage sequence combination set, which further improves the operational accuracy of the energy storage operation method participating in the electricity spot market.

[0182] In conclusion, it's worth noting that electricity market price data essentially reflects the off-peak and peak electricity consumption periods. Price data is not merely an economic indicator; it also reflects the timing of peak and off-peak electricity demand. Therefore, maximizing the charging and discharging benefits of energy storage power stations indicates that the energy stored during off-peak periods is roughly equivalent to the energy released during peak periods. In other words, the energy stored during off-peak periods is almost entirely consumed during peak periods, allowing energy storage power stations to maximize peak-valley electricity consumption regulation, improve energy utilization during off-peak periods, and reduce the power grid's supply pressure during peak periods. Thus, maximizing the charging and discharging benefits of energy storage power stations is not just an economic indicator; it also signifies maximizing the regulation of peak and off-peak electricity demand.

[0183] Optionally, another embodiment of this application also provides an energy storage power station, which may include: a controller for controlling the energy storage power station to operate at rated power in accordance with the energy storage operation method for participating in the electricity spot market as described in any of the above embodiments.

[0184] In practical applications, the controller can be a cloud server, a site server, or an edge layer application device; the specific application environment and user needs can be determined accordingly, and all of these are within the scope of protection of this application.

[0185] It should be noted that the relevant explanations regarding the operation methods of energy storage participating in the electricity spot market can be found in the corresponding embodiments described above, and will not be repeated here. The relevant explanations regarding energy storage power stations can be found in the prior art, and will also not be repeated here.

[0186] In this embodiment, since the energy storage operation method for electricity spot market price arbitrage includes a target charging and discharging time combination that maximizes the charging and discharging revenue of the energy storage power station by finding the optimal combination, the energy storage power station is controlled by the controller to operate at rated power in accordance with the energy storage operation method for participating in the electricity spot market as described in any of the above embodiments. This not only improves the control effect of the energy storage power station on the peak shaving and valley filling of the power grid, but also maximizes the revenue of the energy storage power station.

[0187] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0188] In this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0189] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for operating an energy storage participating in a power spot market, characterized in that, include: Based on the day-ahead market electricity price forecast curve and the day-ahead market settlement rules, generate the day-ahead market settlement electricity price forecast curve; Based on the day-ahead market settlement electricity price forecast curve, and combined with the battery charge / discharge rate and battery life constraints of the energy storage power station, a future daily full-charge-discharge arbitrage sequence combination set for the energy storage power station is generated; wherein, the battery life constraints include the maximum number of daily cycles within the battery's lifespan. From the set of full-charge-release arbitrage sequence combinations for the future day, select the full-charge-release arbitrage sequence combination with the highest arbitrage price as the target full-charge-release arbitrage sequence combination for the energy storage power station for the future day, and control the energy storage power station to charge and discharge at rated power according to the chargeable and dischargeable periods in the target full-charge-release arbitrage sequence combination. Based on the aforementioned day-ahead market settlement electricity price forecast curve, a set of future daily full-charge-release arbitrage sequence combinations for energy storage power stations is generated, including: Determine whether the energy consumption of the energy storage power station during a single venting operation is greater than the minimum settlement time in the day-ahead market settlement rules; If it is determined that the energy consumption time of a single venting of the energy storage power station is not greater than the minimum settlement time in the day-ahead market settlement rules, then the future day full-full-venting arbitrage sequence combination set is generated based on the original concave points and original convex points on the day-ahead market settlement electricity price prediction curve. If it is determined that the energy storage power station's single venting power consumption is greater than the minimum settlement time in the day-ahead market settlement rules, then the original concave points and original convex points on the day-ahead market settlement electricity price prediction curve are expanded to obtain expanded concave points and expanded convex points on the day-ahead market settlement electricity price prediction curve. Based on the original concave points, the original convex points, the expanded concave points, and the expanded convex points, the future day full-full-venting arbitrage sequence combination set is generated. The step of expanding the original concave and convex points on the day-ahead market settlement electricity price forecast curve to obtain expanded concave and convex points on the day-ahead market settlement electricity price forecast curve includes: Determine the target expansion factor; The original concave points and convex points on the day-ahead market settlement electricity price forecast curve are respectively expanded to the target expansion multiple according to the corresponding expansion principle to obtain the expanded concave points and expanded convex points on the day-ahead market settlement electricity price forecast curve; The expansion principle corresponding to the original concave point includes: finding settlement price prediction points with adjacent time on both sides of the original concave point; the expansion principle corresponding to the original convex point includes: finding settlement price prediction points with adjacent time on both sides of the original convex point.

2. The energy storage operation method for participating in the electricity spot market according to claim 1, characterized in that, Based on the day-ahead market electricity price forecast curve and the day-ahead market settlement rules, a day-ahead market settlement electricity price forecast curve is generated, including: Determine the minimum settlement time in the aforementioned day-ahead market settlement rules; Using the minimum settlement time as the settlement electricity price unit time, the average electricity price corresponding to each settlement electricity price unit time of the day-ahead market electricity price forecast curve is calculated. The average electricity price corresponding to each settlement electricity price unit time is: the average value of each electricity price forecast point of the day-ahead market electricity price forecast curve within the corresponding settlement unit electricity price time. The day-ahead market electricity price forecast curve is generated by taking the average electricity price of all the day-ahead market electricity price forecast curves at each settlement electricity price unit time as the settlement electricity price forecast sequence.

3. The energy storage operation method for participating in the electricity spot market according to claim 1, characterized in that, The energy consumption of a single venting operation of the energy storage power station is inversely proportional to the battery charge / discharge rate of the energy storage power station.

4. The energy storage operation method for participating in the electricity spot market according to claim 1, characterized in that, Determining the target expansion factor includes: The target expansion factor is calculated based on the energy storage power station's single venting time and the minimum settlement time in the day-ahead market settlement rules.

5. The energy storage operation method for participating in the electricity spot market according to claim 1, characterized in that, The expansion principle corresponding to the original concave point also includes: finding the closest value on both sides of the original concave point without allowing jumps, and / or, the search range cannot skip adjacent convex points, corresponding to the settlement electricity price prediction point; The expansion principle corresponding to the original convex point also includes: finding the closest value on both sides of the original convex point without allowing jumps, and / or, the search range cannot skip adjacent concave points, corresponding to the settlement electricity price prediction point.

6. The energy storage operation method for participating in the electricity spot market according to claim 1, characterized in that, Based on the original concave point, the original convex point, the extended concave point, and the extended convex point, the set of future day full-full-open arbitrage sequence combinations is generated, including: Each of the original concave points and each of the extended concave points are respectively regarded as each chargeable period of the energy storage power station, and each of the original convex points and each of the extended convex points are respectively regarded as each dischargeable period of the energy storage power station. Based on the number of charging and discharging periods required for the target number of arbitrage opportunities in the future days, a corresponding number of periods are selected from all the rechargeable periods and all the discharging periods and arranged in combination to obtain the set of full charge and discharge arbitrage sequences for the future days; the number of charging and discharging periods required for the target number of arbitrage opportunities in the future days is calculated based on the target number of arbitrage opportunities in the future days, the time consumed by the energy storage power station in one empty discharge, and the minimum settlement time in the day-ahead market settlement rules; Based on the existing concave and convex points on the day-ahead market settlement electricity price forecast curve, the set of future day full-load arbitrage sequence combinations is generated, including: Each of the original concave points on the day-ahead market settlement electricity price forecast curve is taken as a charging period of the energy storage power station, and each of the original convex points on the day-ahead market settlement electricity price forecast curve is taken as a discharging period of the energy storage power station. Based on the number of charging and discharging periods required for the target number of arbitrage operations in the future day, a corresponding number of periods are selected from all the rechargeable periods and all the discharging periods and arranged in combination to obtain the set of full charge and discharge arbitrage sequences for the future day.

7. The energy storage operation method for participating in the electricity spot market according to claim 6, characterized in that, The process for determining the target number of future daily arbitrage opportunities is as follows: The upper limit of the number of full charge / discharge cycles and the upper limit of the number of arbitrage cycles in the future days are determined respectively; Determine whether the upper limit of the number of full charge and discharge cycles in the future is less than the upper limit of the number of arbitrage cycles in the future; If it is determined that the upper limit of the number of full charge and discharge cycles in the future is not less than the upper limit of the number of arbitrage cycles in the future, then the upper limit of the number of arbitrage cycles in the future will be used as the target number of arbitrage cycles in the future. If it is determined that the upper limit of the number of full charge and discharge cycles in the future day is less than the upper limit of the number of arbitrage cycles in the future day, then the upper limit of the number of full charge and discharge cycles in the future day will be used as the target number of arbitrage cycles in the future day.

8. The energy storage operation method for participating in the electricity spot market according to claim 7, characterized in that, Determining the upper limit of the number of full charge and discharge cycles in the future includes: The maximum daily cycle count and the maximum daily full charge / discharge count of the energy storage power station during the battery life cycle are determined respectively. The minimum value between the maximum daily cycle count and the maximum daily full charge / discharge count is taken as the upper limit of the future daily full charge / discharge count.

9. The energy storage operation method for participating in the electricity spot market according to claim 7, characterized in that, Determine the upper limit of the number of future daily arbitrage opportunities, including: The number of original concave points and the number of original convex points are determined respectively; The minimum value between the number of concave points and the number of convex points is taken as the upper limit of the number of future daily arbitrage opportunities.

10. The energy storage operation method for participating in the electricity spot market according to claim 1, characterized in that, After generating a set of future daily full-charge and release arbitrage sequences for energy storage power stations based on the aforementioned day-ahead market settlement electricity price forecast curve, the process also includes: Determine the number of full-volume arbitrage sequence combinations in which the arbitrage spread of the future full-volume arbitrage sequence combination is less than the minimum arbitrage spread of each future full-volume arbitrage. The fully leveraged arbitrage sequences that meet the preset price difference deletion condition in the future full leveraged arbitrage sequence combination set are deleted to obtain the remaining fully leveraged arbitrage sequences in the future full leveraged arbitrage sequence combination set; wherein, the preset price difference deletion condition is: among the price difference sorting sequences of the fully leveraged arbitrage sequences in the future full leveraged arbitrage sequence combination set with the minimum settlement time as the unit, the sequences whose price difference sorting order is lower than the preset sorting order. Based on the number of charging and discharging periods required for the target number of future daily arbitrages, the remaining full-charge and full-discharge arbitrage sequences are recombined in chronological order to obtain the adjusted combination of the full-charge and full-discharge arbitrage series for future days. The future full-charge-release arbitrage series adjustment combination is used as the target full-charge-release arbitrage sequence combination for the energy storage power station in the future, and the energy storage power station is controlled to operate according to the target full-charge-release arbitrage sequence combination.

11. The energy storage operation method for participating in the electricity spot market according to claim 10, characterized in that, The process for determining the minimum arbitrage spread for each future full-scale release includes: Determine the number of cycles within the battery lifecycle of the energy storage power station; Based on the number of cycles within the battery's lifespan, a model is established to predict the target rate of return on investment for the energy storage power station and the future daily electricity spot market arbitrage profit. Solve the model to obtain the minimum arbitrage spread for each future full-scale opening and closing.

12. The energy storage operation method for participating in the electricity spot market according to claim 1, characterized in that, Before selecting the full-full-full-release arbitrage sequence combination with the highest arbitrage spread from the set of future full-full-release arbitrage sequence combinations as the target full-full-release arbitrage sequence combination for the energy storage power station on the future day, and before controlling the energy storage power station to operate according to the target full-full-release arbitrage sequence combination, the method further includes: Delete the full-full-low arbitrage sequence combinations that meet the preset invalid arbitrage sequence combination conditions from the future day full-full-low arbitrage sequence combination set. The condition for meeting the preset invalid arbitrage sequence combination is that the full charge and discharge arbitrage sequence combination has a continuous charging period after full charge or a continuous discharging period after discharge.

13. An energy storage power station, characterized in that, include: A controller for controlling the energy storage power station to operate at rated power in accordance with the energy storage operation method for participating in the electricity spot market as described in any one of claims 1-12.

Images