Quotation and quantity reporting decision-making method and device for participation of energy storage power station in spot market

Abstract

The invention provides a quotation and quantity report decision-making method and device for an energy storage power station participating in a spot market, and relates to the technical field of energy storage. The electricity price prediction curve corresponding to the electricity market in the first time period in the future is obtained through prediction; based on the energy storage constraint condition of the energy storage power station, combining the electricity price prediction curve, and taking the maximum value of the first profit objective function of the energy storage power station in the first time period as a target, fitting to obtain a charging and discharging power curve corresponding to the energy storage power station in the first time period; on the basis of the charging and discharging power curve, combined with the electricity price prediction curve, constructing a quotation constraint condition corresponding to the energy storage power station; and based on a quotation constraint condition, combining with the charging and discharging power curve, and by taking the maximum value of the second profit objective function of the energy storage power station in the first time period as a target, fitting to obtain a charging quotation corresponding to each preset charging power section and a discharging quotation corresponding to each preset discharging power section of the energy storage power station so as to generate a quotation quantity reporting strategy.

Description

Technical Field

[0001] This application relates to the technical field of energy storage, and particularly to a method and device for making quotation and quantity decision for an energy storage power station to participate in the spot market. Background Art

[0002] With the advancement of the power market reform, the power market has gradually shifted from the traditional quantity reporting mechanism to the quantity reporting and quotation mechanism, and the participation mode of the energy storage power station in the power market has also changed accordingly. In the traditional power spot market, the energy storage power station mainly participates in transactions by reporting quantities, charging during low-price periods and discharging during high-price periods according to the power price fluctuations, so as to obtain the arbitrage income of the price difference. However, the traditional quantity reporting mode cannot fully cope with the complexity of the market price and its dynamic changes, nor can it meet the diverse requirements of the competitive environment.

[0003] With the continuous improvement of the power market mechanism, the electricity energy market has gradually transitioned to the quantity reporting and quotation mode. The energy storage power station not only needs to declare the available electricity quantity, but also needs to provide the corresponding electricity price quotation. This change requires the energy storage power station to be able to formulate more accurate quotation and quantity strategies in a changing market environment to maximize its economic benefits. Therefore, how to optimize the market decision of the energy storage power station through intelligent strategies under the new market mechanism has become an important research topic in the current power market. Summary of the Invention

[0004] The present disclosure provides a method and device for making quotation and quantity decision for an energy storage power station to participate in the spot market, so as to at least solve the problem of how to formulate more accurate quotation and quantity strategies in the related art.

[0005] A method for making quotation and quantity decision for an energy storage power station to participate in the spot market according to an embodiment of the first aspect of the present application includes: predicting a corresponding electricity price prediction curve for a first time period in the future in the power market; based on the energy storage constraint conditions of the energy storage power station, combining with the electricity price prediction curve, and aiming at maximizing the value of the first profit objective function of the energy storage power station in the first time period, fitting to obtain a corresponding charge-discharge power curve of the energy storage power station in the first time period; based on the charge-discharge power curve, combining with the electricity price prediction curve, constructing a corresponding quotation constraint condition for the energy storage power station; based on the quotation constraint condition, combining with the charge-discharge power curve, and aiming at maximizing the value of the second profit objective function of the energy storage power station in the first time period, fitting to obtain a charging quotation corresponding to each preset charging power segment and a discharging quotation corresponding to each preset discharging power segment of the energy storage power station; generating a quotation and quantity strategy based on the charging quotation corresponding to each preset charging power segment and the discharging quotation corresponding to each preset discharging power segment.

[0006] According to an embodiment of the present application, the electricity price prediction curve represents the predicted electricity price for each second time period included in the first time period in the electricity market, and the charge-discharge power curve represents the charging power or discharging power of the energy storage power station for each second time period included in the first time period. Based on the charge-discharge power curve and in combination with the electricity price prediction curve, the corresponding quotation constraint conditions for the energy storage power station are constructed, including: based on the charge-discharge power curve and in combination with each second time period included in the first time period, a plurality of charge-discharge second time period pairs are formed, where each charge-discharge second time period pair includes a second time period in a charging state and a second time period in a discharging state; based on the charge-discharge second time period pairs and in combination with the electricity price prediction curve, the predicted electricity price difference corresponding to each charge-discharge second time period pair is determined; a plurality of charging power segments and a plurality of discharging power segments corresponding to the energy storage power station are determined, and the first quotation constraint conditions are generated in combination with the predicted electricity price difference.

[0007] According to an embodiment of the present application, generating the first quotation constraint conditions in combination with the predicted electricity price difference includes: determining the predicted electricity price difference with the smallest value from the predicted electricity price differences corresponding to each charge-discharge second time period pair as the target predicted electricity price difference; generating the first quotation constraint conditions based on the target predicted electricity price difference.

[0008] According to an embodiment of the present application, based on the charge-discharge second time period pairs and in combination with the electricity price prediction curve, determining the predicted electricity price difference corresponding to each charge-discharge second time period pair includes: obtaining the first electricity price corresponding to the second time period in the discharging state in the charge-discharge second time period pair on the electricity price prediction curve; obtaining the second electricity price corresponding to the second time period in the charging state in the charge-discharge second time period pair on the electricity price prediction curve; for each charge-discharge second time period pair, obtaining the difference between the first electricity price and the second electricity price, and using the difference as the predicted electricity price difference corresponding to the charge-discharge second time period pair.

[0009] According to an embodiment of the present application, the formula for the first profit objective function of the energy storage power station is:

[0010]

[0011] In the above formula, profit 1 represents the first profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, LMP(t) represents the electricity price corresponding to the t-th second time period on the electricity price prediction curve, η represents the charge-discharge efficiency of the energy storage power station, P d (t) represents the discharging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the discharging state in the t-th second time period, P d (t) is a positive value. If the energy storage power station is in the charging state in the t-th second time period, P d (t) is 0, Pc (t) represents the charging power corresponding to the energy storage power station in the t-th second time period. If the energy storage power station is in the charging state in the t-th second time period, P c (t) is negative, and the negative value represents charging. If the energy storage power station is in the discharging state in the t-th second time period, P c (t) is 0, price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price gov (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0012] According to an embodiment of the present application, the formula of the second profit objective function is:

[0013]

[0014] In the above formula, profit 2 represents the second profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, price d (t) represents the discharging bid price corresponding to the t-th second time period, price c (t) represents the charging bid price corresponding to the t-th second time period, η represents the charge-discharge efficiency of the energy storage power station, P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period. If the energy storage power station is in the discharging state in the t-th second time period, P d (t) is positive. If the energy storage power station is in the charging state in the t-th second time period, P d (t) is 0, P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period. If the energy storage power station is in the charging state in the t-th second time period, P c (t) is negative, and the negative value represents charging. If the energy storage power station is in the discharging state in the t-th second time period, P c (t) is 0, price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price gov (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0015] According to an embodiment of the present application, the energy storage constraint conditions of the energy storage power station at least include the following energy storage constraint conditions:

[0016] Weather parameter constraint conditions;

[0017] Capacity constraint conditions of the energy storage power station;

[0018] Constraints on the upper and lower limits of charge and discharge power;

[0019] Power station efficiency constraint conditions;

[0020] Constraints on the upper and lower limits of state of charge;

[0021] Constraints on the continuous charge and discharge duration;

[0022] Constraints on the state of charge at the expected end.

[0023] According to an embodiment of the present application, the formula for the constraints on the upper and lower limits of charge and discharge power is:

[0024]

[0025] 0 ≤ α + β ≤ 1

[0026] P c (t) ≤ 0, P d (t) ≥ 0

[0027] α, β ∈ {0, 1}

[0028] In the above formula, represents the upper limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the upper limit of the discharging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the discharging power corresponding to the energy storage power station in the t-th second time period; P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period; α and β respectively represent the 0-1 variables of the charge and discharge states of the energy storage power station in the t-th second time period, α = 1 indicates that the energy storage power station is in the charging state in the t-th second time period, and β = 1 indicates that the energy storage power station is in the discharging state in the t-th second time period.

[0029] According to an embodiment of the present application, the formula for the constraints on the upper and lower limits of the state of charge is:

[0030]

[0031] In the above formula, SOC(t + 1) represents the state of charge of the energy storage power station in the (t + 1)-th second time period; SOC(t) represents the state of charge of the energy storage power station in the t-th second time period; P c(t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period; η d represents the grid connection efficiency of the energy storage power station; η c represents the off-grid efficiency of the energy storage power station.

[0032] According to an embodiment of the present application, after generating a bid volume strategy based on the charging bids corresponding to each preset charging power segment and the discharging bids corresponding to each preset discharging power segment, it further includes: according to the bid volume strategy, combining the bidding data of market participants, the market supply and demand relationship, and other market information, predicting the winning bid time period of the energy storage power station and the winning bid information for each winning bid time period; calculating the predicted winning bid profit value of the energy storage power station based on the winning bid information for each winning bid time period.

[0033] An embodiment of the second aspect of the present application provides a bid volume decision-making device for an energy storage power station to participate in the spot market, including: a electricity price prediction module for predicting the electricity price prediction curve corresponding to the first time period in the future in the electricity market; a first fitting module for, based on the energy storage constraint conditions of the energy storage power station, combining the electricity price prediction curve, and aiming at maximizing the value of the first profit objective function of the energy storage power station in the first time period, fitting the charging and discharging power curve corresponding to the energy storage power station in the first time period; a constraint construction module for, based on the charging and discharging power curve, combining the electricity price prediction curve, constructing the bid constraint conditions corresponding to the energy storage power station; a second fitting module for, based on the bid constraint conditions, combining the charging and discharging power curve, and aiming at maximizing the value of the second profit objective function of the energy storage power station in the first time period, fitting the charging bids corresponding to each preset charging power segment and the discharging bids corresponding to each preset discharging power segment of the energy storage power station; a strategy generation module for generating a bid volume strategy based on the charging bids corresponding to each preset charging power segment and the discharging bids corresponding to each preset discharging power segment.

[0034] According to an embodiment of the present application, the electricity price prediction curve represents the predicted electricity price for each second time period included in the first time period in the electricity market, the charging and discharging power curve represents the charging power or discharging power of the energy storage power station for each second time period included in the first time period, and the constraint construction module is further configured to: based on the charging and discharging power curve, combining each second time period included in the first time period, form a plurality of charging and discharging second time period pairs, where the charging and discharging second time period pair includes a second time period in a charging state and a second time period in a discharging state; based on the charging and discharging second time period pair and combining the electricity price prediction curve, determine the predicted electricity price spread corresponding to each charging and discharging second time period pair; determine a plurality of charging power segments and a plurality of discharging power segments corresponding to the energy storage power station, and generate the first bid constraint conditions in combination with the predicted electricity price spread.

[0035] According to an embodiment of the present application, the constraint construction module is further configured to: determine the predicted electricity price spread with the smallest value from the predicted electricity price spreads corresponding to each charge-discharge second time period as the target predicted electricity price spread; generate a first bid constraint condition based on the target predicted electricity price spread.

[0036] According to an embodiment of the present application, the constraint construction module is further configured to: obtain the first electricity price corresponding to the second time period in the charge-discharge second time period pair that is in the discharging state on the electricity price prediction curve; obtain the second electricity price corresponding to the second time period in the charge-discharge second time period pair that is in the charging state on the electricity price prediction curve; for each charge-discharge second time period pair, obtain the difference between the first electricity price and the second electricity price, and use the difference as the predicted electricity price spread corresponding to the charge-discharge second time period pair.

[0037] According to an embodiment of the present application, the formula of the first profit objective function in the first fitting module is:

[0038]

[0039] In the above formula, profit 1 represents the first profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, LMP(t) represents the electricity price corresponding to the t-th second time period on the electricity price prediction curve, η represents the charge-discharge efficiency of the energy storage power station, P d (t) represents the discharging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the discharging state in the t-th second time period, P d (t) is a positive value. If the energy storage power station is in the charging state in the t-th second time period, P d (t) is 0. P c (t) represents the charging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the charging state in the t-th second time period, P c (t) is a negative value, and the negative value represents charging. If the energy storage power station is in the discharging state in the t-th second time period, P c (t) is 0. price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price gov (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0040] According to an embodiment of the present application, the formula of the second profit objective function in the second fitting module is:

[0041]

[0042] In the above formula, profit 2 represents the second profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, price d (t) represents the discharge quotation corresponding to the t-th second time period, price c (t) represents the charge quotation corresponding to the t-th second time period, η represents the charge-discharge efficiency of the energy storage power station, P d (t) represents the discharge power corresponding to the energy storage power station in the t-th second time period. If the energy storage power station is in the discharge state in the t-th second time period, P d (t) is a positive value. If the energy storage power station is in the charge state in the t-th second time period, P d (t) is 0, P c (t) represents the charge power corresponding to the energy storage power station in the t-th second time period. If the energy storage power station is in the charge state in the t-th second time period, P c (t) is a negative value, and the negative value represents charging. If the energy storage power station is in the discharge state in the t-th second time period, P c (t) is 0, price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price gov (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0043] According to an embodiment of the present application, in the first fitting module, the energy storage constraint conditions of the energy storage power station at least include the following energy storage constraint conditions:

[0044] Weather parameter constraint conditions;

[0045] Energy storage power station capacity constraint conditions;

[0046] Charge-discharge power upper and lower limit constraint conditions;

[0047] Power station efficiency constraint conditions;

[0048] State of charge upper and lower limit constraint conditions;

[0049] Continuous charge-discharge duration constraint conditions;

[0050] State of charge constraint conditions at the expected end.

[0051] According to an embodiment of the present application, in the first fitting module, the formula for the charge-discharge power upper and lower limit constraint conditions is:

[0052]

[0053] 0 ≤ α + β ≤ 1

[0054] P c (t) ≤ 0, P d (t) ≥ 0

[0055] α, β ∈ {0, 1}

[0056] In the above formula, represents the upper limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the upper limit of the discharging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the discharging power corresponding to the energy storage power station in the t-th second time period; P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period; α and β respectively represent 0-1 variables of the charging and discharging states of the energy storage power station in the t-th second time period, α = 1 indicates that the energy storage power station is in the charging state in the t-th second time period, and β = 1 indicates that the energy storage power station is in the discharging state in the t-th second time period.

[0057] According to an embodiment of the present application, in the first fitting module, the formula of the upper and lower limit constraints of the state of charge is:

[0058]

[0059] In the above formula, SOC(t + 1) represents the state of charge of the energy storage power station in the (t + 1)-th second time period; SOC(t) represents the state of charge of the energy storage power station in the t-th second time period; P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period; η d represents the grid connection efficiency of the energy storage power station; η c represents the off-grid efficiency of the energy storage power station.

[0060] According to an embodiment of the present application, the device further includes a winning bid prediction module, which is used to predict the winning bid time period of the energy storage power station and the winning bid information for each winning bid time period according to the quotation and quantity strategy, combined with the bidding data of market participants, the market supply and demand relationship, and other market information; and calculate the predicted winning bid profit value of the energy storage power station based on the winning bid information for each winning bid time period.

[0061] A third aspect embodiment of the present application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the method for making a quotation and quantity decision for an energy storage power station to participate in the spot market as described in the first aspect embodiment of the present application.

[0062] A fourth aspect embodiment of the present application provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the method for making a quotation and quantity decision for an energy storage power station to participate in the spot market as described in the first aspect embodiment of the present application.

[0063] A fifth aspect embodiment of the present application provides a computer program product, including a computer program, where the computer program, when executed by a processor, implements the method for making a quotation and quantity decision for an energy storage power station to participate in the spot market as described in the first aspect embodiment of the present application.

[0064] The technical solutions provided by the embodiments of the present disclosure at least bring the following beneficial effects: By fitting the electricity price prediction curve and the charge-discharge power curve, the present application reasonably sets the charging and discharging quotations, which can ensure that the energy storage power station has a competitive quotation, improve its winning bid probability in the electricity market, enhance the competitiveness of the energy storage power station in the electricity market, and finely regulate the prices for each preset charging power segment and discharging power segment to ensure that the quotation not only meets the market demand but also maximizes the economic benefits of the energy storage power station.

[0065] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0067] Figure 1 is a schematic diagram of an exemplary implementation manner of a method for making a quotation and quantity decision for an energy storage power station to participate in the spot market shown in an embodiment of the present application.

[0068] Figure 2 is a schematic diagram of an exemplary implementation manner of a method for making a quotation and quantity decision for an energy storage power station to participate in the spot market shown in an embodiment of the present application.

[0069] Figure 3 is a schematic diagram of an exemplary implementation manner of a method for making a quotation and quantity decision for an energy storage power station to participate in the spot market shown in an embodiment of the present application.

[0070] Figure 4It is a schematic diagram of a device for making decisions on quotation and quantity reporting of an energy storage power station participating in the spot market shown in an embodiment of the present application.

[0071] Figure 5 It is a schematic diagram of an electronic device shown in an embodiment of the present application. Detailed implementation manners

[0072] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application, and should not be construed as limiting the present application.

[0073] It should be noted that the acquisition, transmission, storage, use, processing, etc. of data in the technical solution of the present application all comply with the relevant regulations of laws and regulations.

[0074] Figure 1 It is a schematic diagram of an exemplary implementation manner of a method for making decisions on quotation and quantity reporting of an energy storage power station participating in the spot market shown in the present application. As Figure 1 shown, the method for making decisions on quotation and quantity reporting of the energy storage power station participating in the spot market includes the following steps:

[0075] S101, predicting a price prediction curve corresponding to the first time period in the future in the power market.

[0076] Specifically, historical electricity price data of the power market is obtained, information on the supply and demand status of the power user market is obtained, weather parameters within a preset time period are obtained, and then based on the historical electricity price data, information on the supply and demand status of the user market, and weather parameters, a price prediction curve corresponding to the first time period in the future in the power market is predicted. This price prediction provides basic data support for formulating quotation and quantity reporting strategies for the energy storage power station in the subsequent stage.

[0077] Among them, the price prediction curve represents the predicted electricity price of each second time period included in the first time period in the power market. Among them, the predicted electricity price of each second time period may be the same or different.

[0078] In some embodiments, the first time period is generally the next trading day, that is, one day.

[0079] Generally, taking 15 minutes as a time period (generally, taking 15 minutes as a time period, the electricity price is fixed within these 15 minutes and will not change), one day is divided into 96 second time periods. The following will all take the first time period as one day and the first time period includes 96 second time periods as an example.

[0080] It is not difficult to understand that in this application, the lengths of the first time period and the second time period are only for examples and should not be construed as limitations to this application.

[0081] S102. Based on the energy storage constraint conditions of the energy storage power station and in combination with the electricity price prediction curve, with the goal of maximizing the value of the first profit objective function of the energy storage power station in the first time period, fit to obtain the charge and discharge power curve corresponding to the energy storage power station in the first time period.

[0082] Obtain the pre-set energy storage constraint conditions of the energy storage power station.

[0083] Obtain the pre-set first profit objective function, where the first profit objective function is related to the charge and discharge power corresponding to the energy storage power station in each second time period and is also related to the predicted electricity price corresponding to each second time period.

[0084] The purpose of this step is to fit to obtain the charge and discharge power curve corresponding to the energy storage power station in the first time period. Among them, the charge and discharge power curve represents the charging power or discharging power of the energy storage power station in each second time period included in the first time period. Among them, the charging power or discharging power of each second time period may be the same or different.

[0085] Continuing to take the first time period as one day and dividing one day into 96 second time periods as an example, the charge and discharge power curve also represents the charging power or discharging power of 96 second time periods (15 minutes is one second time period, and the charging power or discharging power is fixed within these 15 minutes and will not change). It is not difficult to understand that each second time period is either in a charging state or a discharging state, and the two states will not appear in the same second time period.

[0086] S103. Based on the charge and discharge power curve and in combination with the electricity price prediction curve, construct the quotation constraint conditions corresponding to the energy storage power station.

[0087] On the side of the power dispatching agency, the dispatching agency aims at maximizing social welfare (i.e., minimizing the power generation cost), uses the published information as the boundary conditions for market optimization, takes the declared electricity quantity and load prediction on the user side as the demand, conducts centralized optimization, and finally forms the day-ahead market clearing result. This clearing process is based on the maximization of the total social welfare of 96 time periods.

[0088] Charging and discharging have different electricity prices in the electricity market. Specifically, if 1 unit of discharging occurs, the corresponding electricity price is the electricity price at the time of discharging (usually higher); if 1 unit of charging occurs, the corresponding electricity price is the electricity price at the time of charging (usually lower). This can also be understood as: the electricity price at the time of 1 unit of discharging minus the electricity price at the time of 1 unit of charging is the 1 unit conversion cost in the electricity market.

[0089] Combined with the above analysis, the goal of this step is to find a suitable predicted price difference based on the charge-discharge power curve and the electricity price prediction curve. This predicted price difference can be obtained in the following way: First, select a suitable second time period in the discharge state from the charge-discharge power curve, and obtain the electricity price in this second time period from the electricity price prediction curve; then select a suitable time period in the charge state from the charge-discharge power curve, obtain the electricity price in this second time period from the electricity price prediction curve, and calculate the electricity price difference between the two second time periods. This difference is the predicted price difference.

[0090] In order to enhance the competitiveness of the energy storage power station in the market and increase the winning bid probability, in the final bidding strategy, the bid price difference for each charge-discharge power segment of the energy storage power station should be less than the above predicted price difference (that is, this is a bid price constraint condition).

[0091] In this application, take the energy storage power station including 5 charging power segments (-100MW to -80MW, -80MW to -60MW, -60MW to -40MW, -40MW to -20MW, -20MW to 0, where the negative sign indicates charging), and 5 discharging power segments (0 to 20MW, 20MW to 40MW, 40MW to 60MW, 60MW to 80MW, 80MW to 100MW, where the positive number indicates discharging) as an example.

[0092] In this application, -100MW to -80MW and 80MW to 100MW are taken as a group of charge-discharge power segments, -80MW to -60MW and 60MW to 80MW are taken as a group of charge-discharge power segments, -60MW to -40MW and 40MW to 60MW are taken as a group of charge-discharge power segments, -40MW to -20MW and 20MW to 40MW are taken as a group of charge-discharge power segments, and -20MW to 0 and 0 to 20MW are taken as a group of charge-discharge power segments.

[0093] S104. Based on the bid price constraint condition, combined with the charge-discharge power curve, with the goal of maximizing the value of the second profit objective function of the energy storage power station in the first time period, fit to obtain the charging bid corresponding to each preset charging power segment and the discharging bid corresponding to each preset discharging power segment of the energy storage power station.

[0094] Among them, the second profit objective function is related to the charge-discharge power corresponding to each second time period of the energy storage power station, and is related to the bid price corresponding to the power segment where the charge-discharge power corresponding to each second time period is located.

[0095] In some embodiments, in addition to the constraint that the price difference between the quotes for each charge-discharge power segment of the energy storage power station should be less than the predicted price difference, when fitting the charging quotes corresponding to each preset charging power segment and the discharging quotes corresponding to each preset discharging power segment of the energy storage power station, other quote preset conditions can also be set. For example, it can also include: the quote for the charging power segment with a higher power segment should be lower than the quote for the charging power segment with a lower power segment; the quote for the discharging power segment with a higher power segment should be higher than the quote for the discharging power segment with a lower power segment.

[0096] S105. Generate a quote and quantity strategy based on the charging quotes corresponding to each preset charging power segment and the discharging quotes corresponding to each preset discharging power segment.

[0097] Exemplarily, the finally generated quote and quantity strategy is shown in Table 1.

[0098] Table 1 Quote and Quantity Strategy

[0099] Power range (MW) Quotation (yuan) 1 Charging -100～-80 210 2 Charging -80～-60 211 3 Charging -60～-40 212 4 Charging -40～-20 214 5 Charging -20～0 215 6 Discharging 0～20 405 7 Discharging 20～40 407 8 Discharging 40～60 409 9 Discharging 60～80 411 10 Discharging 80～100 413

[0100] The embodiment of the present application proposes a method for making a quote and quantity decision for an energy storage power station to participate in the spot market, including: predicting the electricity price prediction curve corresponding to the first time period in the future in the power market; based on the energy storage constraint conditions of the energy storage power station, combining with the electricity price prediction curve, with the goal of maximizing the value of the first profit objective function of the energy storage power station in the first time period, fitting the charge-discharge power curve corresponding to the energy storage power station in the first time period; based on the charge-discharge power curve, combining with the electricity price prediction curve, constructing the quote constraint conditions corresponding to the energy storage power station; based on the quote constraint conditions, combining with the charge-discharge power curve, with the goal of maximizing the value of the second profit objective function of the energy storage power station in the first time period, fitting the charging quotes corresponding to each preset charging power segment and the discharging quotes corresponding to each preset discharging power segment of the energy storage power station; generating a quote and quantity strategy based on the charging quotes corresponding to each preset charging power segment and the discharging quotes corresponding to each preset discharging power segment. Through the fitting based on the electricity price prediction curve and the charge-discharge power curve, the present application reasonably sets the charging and discharging quotes, which can ensure that the energy storage power station has a competitive quote, improve its winning bid probability in the power market, enhance the competitiveness of the energy storage power station in the power market, and finely regulate the prices of each preset charging power segment and discharging power segment to ensure that the quotes not only meet the market demand but also can maximize the economic benefits of the energy storage power station.

[0101] Figure 2 It is a schematic diagram of an exemplary embodiment of a method for making a quote and quantity decision for an energy storage power station to participate in the spot market shown in the present application. As Figure 2 shown, the method for making a quote and quantity decision for the energy storage power station to participate in the spot market includes the following steps:

[0102] S201. Predict the electricity price prediction curve corresponding to the first time period in the future for the electricity market.

[0103] Specifically, obtain the historical electricity price data of the electricity market, obtain the information on the supply and demand status of the electricity user market, obtain the weather parameters within a preset time period, and then predict the electricity price prediction curve corresponding to the first time period in the future for the electricity market based on the historical electricity price data, the information on the supply and demand status of the user market, and the weather parameters. This price prediction provides the basic data support for formulating the quotation and quantity strategy of the subsequent energy storage power station.

[0104] Among them, the electricity price prediction curve represents the predicted electricity price for each second time period included in the first time period of the electricity market. Among them, the predicted electricity price for each second time period may be the same or different.

[0105] S202. Based on the energy storage constraint conditions of the energy storage power station and in combination with the electricity price prediction curve, with the goal of maximizing the value of the first profit objective function of the energy storage power station in the first time period, fit the charge and discharge power curve corresponding to the first time period of the energy storage power station.

[0106] Obtain the pre-set energy storage constraint conditions of the energy storage power station. The energy storage constraint conditions at least include the following energy storage constraint conditions:

[0107] 1. Weather parameter constraint conditions: Affect the power generation of new energy sources such as wind power and photovoltaics, and affect the formulation of the charge and discharge strategy of the energy storage power station.

[0108] 2. Energy storage power station capacity constraint conditions: The total electricity storage capacity limit of the energy storage power station.

[0109] 3. Charge and discharge power upper and lower limit constraint conditions: The power limit when the energy storage power station charges and discharges.

[0110] 4. Power station efficiency constraint conditions: The energy conversion efficiency limit during the charge and discharge process.

[0111] 5. State of charge upper and lower limit constraint conditions: The range of the state of charge (SOC) of the energy storage power station.

[0112] 6. Continuous charge and discharge duration constraint conditions: The maximum continuous time of the energy storage power station in the charge or discharge mode.

[0113] 7. Desired state of charge constraint condition at the end: The target state of charge of the energy storage power station at a certain future moment during the decision-making process.

[0114] In some embodiments, the formula for the above charge and discharge power upper and lower limit constraint conditions is:

[0115]

[0116] 0 ≤ α + β ≤ 1

[0117] P c (t) ≤ 0, P d (t) ≥ 0

[0118] α, β ∈ {0, 1}

[0119] In the above formula, represents the upper limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the upper limit of the discharging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the discharging power corresponding to the energy storage power station in the t-th second time period; P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period; α and β respectively represent the 0-1 variables of the charging and discharging states of the energy storage power station in the t-th second time period. α = 1 indicates that the energy storage power station is in the charging state in the t-th second time period, and β = 1 indicates that the energy storage power station is in the discharging state in the t-th second time period.

[0120] In some embodiments, the formula for the above state of charge upper and lower limit constraint conditions is:

[0121]

[0122] In the above formula, SOC(t + 1) represents the state of charge of the energy storage power station in the (t + 1)-th second time period; SOC(t) represents the state of charge of the energy storage power station in the t-th second time period; P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period; η d represents the grid connection efficiency of the energy storage power station; η c represents the off-grid efficiency of the energy storage power station.

[0123] Among them, the grid connection efficiency refers to the conversion efficiency in the process that the direct current discharged by the energy storage system battery becomes alternating current through the Power Conversion System (PCS) during the grid connection process, and then reaches the station outlet and is incorporated into the power grid.

[0124] Among them, the off-grid efficiency is the ratio of the actual effective energy of the electric energy provided by the power grid entering the energy storage battery to the total electric energy transmitted from the power grid during the process of the energy storage power station charging from the power grid.

[0125] Among them, the formula of the first profit objective function of the energy storage power station is as follows:

[0126]

[0127] In the above formula, profit 1 represents the first profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, LMP(t) represents the electricity price corresponding to the t-th second time period on the electricity price prediction curve, η represents the charge-discharge efficiency of the energy storage power station, P d (t) represents the discharge power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the discharge state in the t-th second time period, P d (t) is a positive value. If the energy storage power station is in the charging state in the t-th second time period, P d (t) is 0, P c (t) represents the charging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the charging state in the t-th second time period, P c (t) is a negative value, and the negative value represents charging. If the energy storage power station is in the discharge state in the t-th second time period, P c (t) is 0, price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price goy (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0128] The purpose of this step is to fit and obtain the charge-discharge power curve of the energy storage power station corresponding to the first time period. Among them, the charge-discharge power curve represents the charging power or discharge power of the energy storage power station in each second time period included in the first time period. Among them, the charging power or discharge power of each second time period can be the same or different.

[0129] S203. Based on the charge-discharge power curve, combined with each second time period included in the first time period, form multiple charge-discharge second time period pairs. Among them, the charge-discharge second time period pair includes a second time period in the charging state and a second time period in the discharge state.

[0130] Specifically, determine multiple second time periods in the charging state on the charge-discharge power curve, determine multiple second time periods in the discharge state on the charge-discharge power curve, and then combine the second time periods in the charging state and the second time periods in the discharge state in pairs to form multiple charge-discharge second time period pairs. Among them, the charge-discharge second time period pair includes a second time period in the charging state and a second time period in the discharge state.

[0131] Continuing with the example where the first time period is one day and one day is divided into 96 second time periods, assuming that 30 second time periods on the charge-discharge power curve are in the charging state and 66 second time periods are in the discharging state, a total of 30×66 charge-discharge second time period pairs are generated.

[0132] S204. Based on the charge-discharge second time period pairs and combined with the electricity price prediction curve, determine the predicted electricity price spread corresponding to each charge-discharge second time period pair.

[0133] For each charge-discharge second time period pair, obtain the first electricity price corresponding to the second time period in the discharging state in the charge-discharge second time period pair on the electricity price prediction curve; obtain the second electricity price corresponding to the second time period in the charging state in the charge-discharge second time period pair on the electricity price prediction curve; obtain the difference between the first electricity price and the second electricity price, and use the difference as the predicted electricity price spread corresponding to the charge-discharge second time period pair.

[0134] S205. Determine multiple charging power segments and multiple discharging power segments corresponding to the energy storage power station, and generate the first bid constraint condition in combination with the predicted electricity price spread.

[0135] Determine the predicted electricity price spread with the smallest value from the predicted electricity price spreads corresponding to each charge-discharge second time period pair as the target predicted electricity price spread; generate the first bid constraint condition based on the target predicted electricity price spread, where the first bid constraint condition is that the bid spread of each group of charge-discharge power segments of the energy storage power station should be less than the determined target predicted electricity price spread.

[0136] In this application, taking the energy storage power station as an example, it includes 5 charging power segments (-100MW to -80MW, -80MW to -60MW, -60MW to -40MW, -40MW to -20MW, -20MW to 0, where the negative sign indicates charging) and 5 discharging power segments (0 to 20MW, 20MW to 40MW, 40MW to 60MW, 60MW to 80MW, 80MW to 100MW, where the positive number indicates discharging).

[0137] Take -100MW to -80MW and 80MW to 100MW as a group of charge-discharge power segments, take -80MW to -60MW and 60MW to 80MW as a group of charge-discharge power segments, take -60MW to -40MW and 40MW to 60MW as a group of charge-discharge power segments, take -40MW to -20MW and 20MW to 40MW as a group of charge-discharge power segments, and take -20MW to 0 and 0 to 20MW as a group of charge-discharge power segments.

[0138] S206. Based on the quotation constraint conditions and in combination with the charge-discharge power curve, with the objective of maximizing the value of the second profit objective function of the energy storage power station in the first time period, the charging quotation corresponding to each preset charging power segment and the discharging quotation corresponding to each preset discharging power segment of the energy storage power station are obtained by fitting.

[0139] In some embodiments, in addition to the constraint condition that the price difference between each set of charge-discharge power segments of the energy storage power station should be less than the determined target predicted electricity price difference, when obtaining the charging quotation corresponding to each preset charging power segment and the discharging quotation corresponding to each preset discharging power segment of the energy storage power station by fitting, other quotation preset conditions can also be set. For example, it can also include: the quotation of the charging power segment with a higher power segment should be lower than the quotation of the charging power segment with a lower power segment; the quotation of the discharging power segment with a higher power segment should be higher than the quotation of the discharging power segment with a lower power segment.

[0140] Among them, the formula of the second profit objective function is:

[0141]

[0142] In the above formula, profit 2 represents the second profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, price d (t) represents the discharging quotation corresponding to the t-th second time period, price c (t) represents the charging quotation corresponding to the t-th second time period, η represents the charge-discharge efficiency of the energy storage power station, P d (t) represents the discharging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the discharging state in the t-th second time period, P d (t) is a positive value. If the energy storage power station is in the charging state in the t-th second time period, P d (t) is 0, P c (t) represents the charging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the charging state in the t-th second time period, P c (t) is a negative value, and the negative value represents charging. If the energy storage power station is in the discharging state in the t-th second time period, P c (t) is 0, price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price gov (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0143] S207. Generate a quotation quantity strategy based on the charging quotations corresponding to each preset charging power segment and the discharging quotations corresponding to each preset discharging power segment.

[0144] In the embodiments of the present application, by fitting the electricity price prediction curve and the charge-discharge power curve, the charging and discharging quotations are reasonably set, which can ensure that the energy storage power station has a competitive quotation, improve its winning bid probability in the electricity market, enhance the competitiveness of the energy storage power station in the electricity market, and finely regulate the prices of each preset charging power segment and discharging power segment to ensure that the quotation not only meets the market demand but also can maximize the economic benefits of the energy storage power station.

[0145] Figure 3 It is a schematic diagram of an exemplary embodiment of a method for making a quotation quantity decision for an energy storage power station to participate in the spot market shown in the present application. As Figure 3 shown, the method for making a quotation quantity decision for the energy storage power station to participate in the spot market includes the following steps:

[0146] S301. Predict the electricity price prediction curve corresponding to the first time period in the future in the electricity market.

[0147] S302. Based on the energy storage constraint conditions of the energy storage power station and in combination with the electricity price prediction curve, with the goal of maximizing the value of the first profit objective function of the energy storage power station in the first time period, fit the charge-discharge power curve corresponding to the energy storage power station in the first time period.

[0148] S303. Based on the charge-discharge power curve and in combination with the electricity price prediction curve, construct the quotation constraint conditions corresponding to the energy storage power station.

[0149] S304. Based on the quotation constraint conditions and in combination with the charge-discharge power curve, with the goal of maximizing the value of the second profit objective function of the energy storage power station in the first time period, fit the charging quotations corresponding to each preset charging power segment and the discharging quotations corresponding to each preset discharging power segment of the energy storage power station.

[0150] S305. Generate a quotation quantity strategy based on the charging quotations corresponding to each preset charging power segment and the discharging quotations corresponding to each preset discharging power segment.

[0151] For the specific implementation manners of steps S301 to S305, reference may be made to the specific introduction of the relevant parts in the above embodiments, and details will not be elaborated here.

[0152] S306. According to the quotation quantity strategy, in combination with the bidding data of market participants, the market supply and demand relationship and other market information, predict the winning bid time period of the energy storage power station and the winning bid information for each winning bid time period.

[0153] It is not difficult to understand. Continuing with the example where the first time period is one day and one day is divided into 96 second time periods, the energy storage power station does not necessarily win the bid in all 96 second time periods and may only win the bid in some of the second time periods.

[0154] In this application, according to the above-determined bid price and quantity strategy, combined with the bidding data of market participants, market supply and demand relationships, and other market information, the winning bid time periods of the energy storage power station and the winning bid information for each winning bid time period are predicted (including the winning bid price within the winning bid time period. The winning bid price refers to the price at which the energy storage power station will settle with the power dispatching market, generally the price on the electricity price prediction curve corresponding to the power market, rather than the bid price of the energy storage power station).

[0155] S307. Calculate the predicted winning bid profit value of the energy storage power station based on the winning bid information for each winning bid time period.

[0156] The calculation formula for the predicted winning bid profit value is as follows:

[0157]

[0158] In the above formula, profit 3 represents the predicted winning bid profit value, n represents the nth winning bid time period, N represents a total of N winning bid time periods, LMP(n) represents the electricity price corresponding to the nth winning bid time period on the electricity price prediction curve, η represents the charge-discharge efficiency of the energy storage power station, P d (n) represents the discharge power of the energy storage power station corresponding to the nth winning bid time period, obtained from the charge-discharge power curve. If the energy storage power station is in the discharge state in the nth winning bid time period, P d (n) is a positive value. If the energy storage power station is in the charging state in the nth winning bid time period, P d (n) is 0, P c (n) represents the charging power of the energy storage power station corresponding to the nth winning bid time period, obtained from the charge-discharge power curve. If the energy storage power station is in the charging state in the nth winning bid time period, P c (n) is a negative value, and the negative value represents charging. If the energy storage power station is in the discharge state in the nth winning bid time period, P c (n) is 0, price capacity (n) represents the capacity electricity price corresponding to the nth winning bid time period, price gov (n) represents the additional unit price corresponding to the nth winning bid time period, price trans (n) represents the unit price of transmission and distribution fees corresponding to the nth winning bid time period.

[0159] The above formula can be simply understood as follows. For example, in 96 time periods, if only 20 time periods are won in the bid, then based on the obtained charge-discharge power curve and the obtained electricity price prediction curve, the predicted winning profit values of only these 20 winning time periods are calculated.

[0160] In the embodiment of the present application, by fitting the electricity price prediction curve and the charge-discharge power curve, the charging and discharging quotes can be reasonably set, which can ensure that the energy storage power station has a competitive quote, improve its winning bid probability in the power market, enhance the competitiveness of the energy storage power station in the power market, and finely regulate the prices of each preset charging power segment and discharging power segment to ensure that the quote not only meets the market demand but also can maximize the economic benefits of the energy storage power station.

[0161] Figure 4 It is a schematic diagram of a device for making a bid quantity decision for an energy storage power station participating in the spot market shown in the present application. As Figure 4 shown, the device 400 for making a bid quantity decision for the energy storage power station participating in the spot market includes an electricity price prediction module 401, a first fitting module 402, a constraint construction module 403, a second fitting module 404, and a strategy generation module 405, where:

[0162] The electricity price prediction module 401 is used to predict the electricity price prediction curve corresponding to the first time period in the future in the power market;

[0163] The first fitting module 402 is used to, based on the energy storage constraint conditions of the energy storage power station and in combination with the electricity price prediction curve, with the goal of maximizing the value of the first profit objective function of the energy storage power station in the first time period, fit the charge-discharge power curve corresponding to the energy storage power station in the first time period;

[0164] The constraint construction module 403 is used to, based on the charge-discharge power curve and in combination with the electricity price prediction curve, construct the bid constraint conditions corresponding to the energy storage power station;

[0165] The second fitting module 404 is used to, based on the bid constraint conditions and in combination with the charge-discharge power curve, with the goal of maximizing the value of the second profit objective function of the energy storage power station in the first time period, fit the charging quotes corresponding to each preset charging power segment and the discharging quotes corresponding to each preset discharging power segment of the energy storage power station;

[0166] The strategy generation module 405 is used to generate a bid quantity strategy based on the charging quotes corresponding to each preset charging power segment and the discharging quotes corresponding to each preset discharging power segment.

[0167] Further, the electricity price prediction curve represents the predicted electricity price of each second time period included in the first time period, and the charge-discharge power curve represents the charging power or the discharging power of the energy storage power station in each second time period included in the first time period. The constraint construction module 403 is further configured to: based on the charge-discharge power curve, combine each second time period included in the first time period to form a plurality of charge-discharge second time period pairs, where a charge-discharge second time period pair includes a second time period in a charging state and a second time period in a discharging state; based on the charge-discharge second time period pairs and in combination with the electricity price prediction curve, determine the predicted electricity price spread corresponding to each charge-discharge second time period pair; determine a plurality of charging power segments and a plurality of discharging power segments corresponding to the energy storage power station, and generate a first bid constraint condition in combination with the predicted electricity price spread.

[0168] Further, the constraint construction module 403 is further configured to: determine the predicted electricity price spread with the smallest value from the predicted electricity price spreads corresponding to each charge-discharge second time period pair as the target predicted electricity price spread; generate a first bid constraint condition based on the target predicted electricity price spread.

[0169] Further, the constraint construction module 403 is further configured to: obtain a first electricity price corresponding to the second time period in the discharging state in the charge-discharge second time period pair on the electricity price prediction curve; obtain a second electricity price corresponding to the second time period in the charging state in the charge-discharge second time period pair on the electricity price prediction curve; for each charge-discharge second time period pair, obtain the difference between the first electricity price and the second electricity price, and use the difference as the predicted electricity price spread corresponding to the charge-discharge second time period pair.

[0170] According to an embodiment of the present application, the formula of the first profit objective function in the first fitting module 402 is:

[0171]

[0172] In the above formula, profit 1 represents the first profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, LMP(t) represents the electricity price corresponding to the t-th second time period on the electricity price prediction curve, η represents the charge-discharge efficiency of the energy storage power station, P d (t) represents the discharging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the discharging state in the t-th second time period, P d (t) is a positive value. If the energy storage power station is in the charging state in the t-th second time period, P d (t) is 0, P c (t) represents the charging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the charging state in the t-th second time period, P c(t) is negative, and the negative value represents charging. If the energy storage power station is in the discharging state during the t-th second time period, then P c (t) is 0, and price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, and price gov (t) represents the additional unit price corresponding to the t-th second time period, and price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0173] Furthermore, the formula of the second profit objective function in the second fitting module 404 is:

[0174]

[0175] In the above formula, profit 2 represents the second profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, and price d (t) represents the discharging quotation corresponding to the t-th second time period, and price c (t) represents the charging quotation corresponding to the t-th second time period, η represents the charging and discharging efficiency of the energy storage power station, and P d (t) represents the discharging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the discharging state during the t-th second time period, then P d (t) is positive. If the energy storage power station is in the charging state during the t-th second time period, then P d (t) is 0, and P c (t) represents the charging power of the energy storage power station corresponding to the t-th second time period. If the energy storage power station is in the charging state during the t-th second time period, then P c (t) is negative, and the negative value represents charging. If the energy storage power station is in the discharging state during the t-th second time period, then P c (t) is 0, and price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, and price gov (t) represents the additional unit price corresponding to the t-th second time period, and price trans (t) represents the unit price of transmission and distribution fees corresponding to the t-th second time period.

[0176] Furthermore, in the first fitting module 402, the energy storage constraint conditions of the energy storage power station at least include the following energy storage constraint conditions:

[0177] Weather parameter constraint conditions;

[0178] Energy storage power station capacity constraint conditions;

[0179] Constraints on the upper and lower limits of charge and discharge power;

[0180] Constraints on power station efficiency;

[0181] Constraints on the upper and lower limits of state of charge;

[0182] Constraints on the continuous charge and discharge duration;

[0183] Constraints on the state of charge at the expected end.

[0184] According to an embodiment of the present application, in the first fitting module 402, the formula for the constraints on the upper and lower limits of charge and discharge power is:

[0185]

[0186] 0 ≤ α + β ≤ 1

[0187] P c (t) ≤ 0, P d (t) ≥ 0

[0188] α, β ∈ {0, 1}

[0189] In the above formula, represents the upper limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the charging power corresponding to the energy storage power station in the t-th second time period; represents the upper limit of the discharging power corresponding to the energy storage power station in the t-th second time period; represents the lower limit of the discharging power corresponding to the energy storage power station in the t-th second time period; P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d (t) represents the discharging power corresponding to the energy storage power station in the t-th second time period; α and β respectively represent the 0-1 variables of the charge and discharge states of the energy storage power station in the t-th second time period, α = 1 indicates that the energy storage power station is in the charging state in the t-th second time period, and β = 1 indicates that the energy storage power station is in the discharging state in the t-th second time period.

[0190] Further, in the first fitting module 402, the formula for the constraints on the upper and lower limits of the state of charge is:

[0191]

[0192] In the above formula, SOC(t + 1) represents the state of charge of the energy storage power station in the (t + 1)-th second time period; SOC(t) represents the state of charge of the energy storage power station in the t-th second time period; P c (t) represents the charging power corresponding to the energy storage power station in the t-th second time period; P d(t) represents the discharge power of the energy storage power station corresponding to the t-th second time period; η d represents the grid connection efficiency of the energy storage power station; η c represents the off-grid efficiency of the energy storage power station.

[0193] Furthermore, the bid and volume decision-making device 400 for the energy storage power station to participate in the spot market further includes a winning bid prediction module, which is used to predict the winning bid time period of the energy storage power station and the winning bid information for each winning bid time period according to the bid and volume strategy, combined with the bidding data of market participants, the market supply and demand relationship, and other market information; and calculate the predicted winning bid profit value of the energy storage power station based on the winning bid information for each winning bid time period.

[0194] To implement the above embodiments, an electronic device 500 is further proposed in the embodiments of the present application. As Figure 5 shown, the electronic device 500 includes: a processor 501 and a memory 502 communicatively connected to the processor. The memory 502 stores instructions executable by at least one processor. The instructions are executed by at least one processor 501 to implement the bid and volume decision-making method for the energy storage power station to participate in the spot market as shown in the above embodiments.

[0195] To implement the above embodiments, a non-transitory computer-readable storage medium storing computer instructions is further proposed in the embodiments of the present application, wherein the computer instructions are used to cause a computer to implement the bid and volume decision-making method for the energy storage power station to participate in the spot market as shown in the above embodiments.

[0196] To implement the above embodiments, a computer program product is further proposed in the embodiments of the present application, including a computer program, and the computer program implements the bid and volume decision-making method for the energy storage power station to participate in the spot market as shown in the above embodiments when executed by a processor.

[0197] In the description of the present application, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present application.

[0198] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, "a plurality of" means two or more, unless otherwise specifically defined.

[0199] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0200] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A quotation and quantity decision-making method for energy storage power stations participating in the spot market, characterized in that: include: Predicting and obtaining the electricity price forecast curve corresponding to the first time period of the electricity market in the future; Based on the energy storage constraint conditions of the energy storage power station, combined with the electricity price forecast curve, with the goal of maximizing the value of the first profit objective function of the energy storage power station in the first time period, fitting the charge and discharge power curve corresponding to the energy storage power station in the first time period; Based on the charging and discharging power curve and in combination with the electricity price forecast curve, construct the quotation constraint conditions corresponding to the energy storage power station; Based on the quotation constraint conditions, combined with the charging and discharging power curves, with the goal of maximizing the value of the second profit objective function of the energy storage power station in the first time period, the charging quotation corresponding to each preset charging power segment and the discharging quotation corresponding to each preset discharging power segment of the energy storage power station are fitted; A quotation reporting strategy is generated based on the charging quotation corresponding to each preset charging power range and the discharging quotation corresponding to each preset discharging power range.

2. The method according to claim 1, characterized in that The electricity price forecast curve represents the forecast electricity price of the electricity market in each second time period included in the first time period, the charge and discharge power curve represents the charging power or discharging power of the energy storage power station in each second time period included in the first time period, and the quotation constraint conditions corresponding to the energy storage power station are constructed based on the charge and discharge power curve and in combination with the electricity price forecast curve, including: Based on the charge-discharge power curve, in combination with each second time period included in the first time period, a plurality of charge-discharge second time period pairs are formed, wherein the charge-discharge second time period pairs include a second time period in a charging state and a second time period in a discharging state; Based on the charging and discharging second time period pairs, combined with the electricity price prediction curve, determining the predicted electricity price difference corresponding to each of the charging and discharging second time period pairs; Determine a plurality of charging power segments and a plurality of discharging power segments corresponding to the energy storage power station, and generate the first quotation constraint condition in combination with the predicted electricity price difference.

3. The method according to claim 2, characterized in that The generating the first bidding constraint condition in combination with the predicted electricity price difference includes: Determine the predicted electricity price difference with the smallest value from the predicted electricity price differences corresponding to each of the second charging and discharging time periods as the target predicted electricity price difference; The first bidding constraint condition is generated based on the target predicted electricity price difference.

4. The method according to claim 3, characterized in that For each of the second charging and discharging time period pairs, a method for determining a predicted electricity price difference corresponding to the second charging and discharging time period pair includes: Obtaining a first electricity price corresponding to a second time period in a discharging state in the second charging and discharging time period pair on the electricity price prediction curve; Obtaining a second electricity price corresponding to a second time period in a charging state in the second charging and discharging time period pair on the electricity price prediction curve; The difference between the first electricity price and the second electricity price is obtained, and the difference is used as the predicted electricity price difference corresponding to the second charging and discharging time period.

5. The method according to claim 4, characterized in that The formula of the first profit objective function of the energy storage power station is: In the above formula, profit1 represents the first profit value, t represents the t-th second time period, T represents that the first time period includes T second time periods in total, LMP(t) represents the electricity price corresponding to the t-th second time period on the electricity price prediction curve, η represents the charging and discharging efficiency of the energy storage power station, P d (t) represents the discharge power of the energy storage station in the tth second time period. If the energy storage station is in the discharge state in the tth second time period, P d (t) is a positive value. If the energy storage station is in the charging state in the tth second time period, P d (t) is 0, P c (t) represents the charging power of the energy storage station in the tth second time period. If the energy storage station is in the charging state in the tth second time period, P c (t) is a negative value, which means it is charging. If the energy storage power station is in the discharging state in the tth second time period, P c (t) is 0, price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price gov (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution electricity fee corresponding to the t-th second time period.

6. The method according to claim 5, characterized in that The formula of the second profit objective function is: In the above formula, profit2 represents the second profit value, t represents the t-th second time period, T represents that the first time period includes a total of T second time periods, and price d (t) represents the discharge quotation corresponding to the t-th second time period, price c (t) represents the charging quotation corresponding to the t-th second time period, η represents the charging and discharging efficiency of the energy storage power station, P d (t) represents the discharge power of the energy storage station in the tth second time period. If the energy storage station is in the discharge state in the tth second time period, P d (t) is a positive value. If the energy storage station is in the charging state in the tth second time period, P d (t) is 0, P c (t) represents the charging power of the energy storage station in the tth second time period. If the energy storage station is in the charging state in the tth second time period, P c (t) is a negative value, which means it is charging. If the energy storage power station is in the discharging state in the tth second time period, P c (t) is 0, price capacity (t) represents the capacity electricity price corresponding to the t-th second time period, price gov (t) represents the additional unit price corresponding to the t-th second time period, price trans (t) represents the unit price of transmission and distribution electricity fee corresponding to the t-th second time period.

7. The method according to claim 6, characterized in that The energy storage constraints of the energy storage power station include at least the following energy storage constraints: Weather parameter constraints; Energy storage power station capacity constraints; The upper and lower limit constraints of charge and discharge power; Power plant efficiency constraints; Upper and lower limit constraints of state of charge; Continuous charge and discharge time constraints; Constraints on the desired end state of charge.

8. The method according to claim 7, characterized in that The formula for the upper and lower limit constraints of the charge and discharge power is: 0≤α+β≤1 P c (t)≤0,P d (t)≥0 α,β∈{0,1} In the above formula, Indicates the upper limit of the charging power of the energy storage power station corresponding to the t-th second time period; Indicates the lower limit of the charging power of the energy storage power station corresponding to the t-th second time period; Indicates the upper limit of the discharge power of the energy storage power station corresponding to the t-th second time period; represents the lower limit of the discharge power of the energy storage power station corresponding to the second time period t; P c (t) represents the charging power of the energy storage station in the tth second time period; P d (t) represents the discharge power of the energy storage station corresponding to the t-th second time period; α and β respectively represent the 0-1 variables of the charging and discharging states of the energy storage station in the t-th second time period, α=1 represents that the energy storage station is in the charging state in the t-th second time period, and β=1 represents that the energy storage station is in the discharging state in the t-th second time period.

9. The method according to claim 7, characterized in that: The formula for the upper and lower limit constraints of the state of charge is: In the above formula, SOC(t+1) represents the state of charge of the energy storage power station in the t+1th second time period; SOC(t) represents the state of charge of the energy storage power station in the tth second time period; P c (t) represents the charging power of the energy storage station in the tth second time period; P d (t) represents the discharge power of the energy storage power station corresponding to the t-th second time period; η d Represents the grid-connected efficiency of the energy storage power station; η c Indicates the grid-connected efficiency of the energy storage power station.

10. The method according to claim 9, characterized in that After the quotation reporting strategy is generated based on the charging quotation corresponding to each preset charging power range and the discharging quotation corresponding to each preset discharging power range, the method further includes: According to the bidding quantity strategy, combined with the bidding data of market participants, market supply and demand relationship and other market information, predict the bidding time period of the energy storage power station and the bidding information of each bidding time period; The predicted winning bid profit value of the energy storage power station is calculated based on the winning bid information of each winning bid time period.

11. A quotation and quantity decision-making device for energy storage power stations participating in the spot market, characterized in that: include: The electricity price prediction module is used to predict the electricity price prediction curve corresponding to the first time period of the electricity market in the future; A first fitting module is used to fit the charging and discharging power curve corresponding to the energy storage station in the first time period based on the energy storage constraint condition of the energy storage station and in combination with the electricity price forecast curve, with the goal of maximizing the value of the first profit objective function of the energy storage station in the first time period; A constraint construction module, used to construct a quotation constraint condition corresponding to the energy storage power station based on the charging and discharging power curve and in combination with the electricity price forecast curve; A second fitting module is used to fit the charging quotation corresponding to each preset charging power segment and the discharging quotation corresponding to each preset discharging power segment of the energy storage power station based on the quotation constraint condition and in combination with the charging and discharging power curve, with the goal of maximizing the value of the second profit objective function of the energy storage power station in the first time period; The strategy generation module is used to generate a quotation reporting strategy based on the charging quotation corresponding to each preset charging power range and the discharging quotation corresponding to each preset discharging power range.

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