Energy storage quotation decision-making system and method for combined clearing of electric energy and auxiliary service

Abstract

The invention relates to an electric energy and auxiliary service combined clearing energy storage quotation decision-making system and method. The system is technically characterized by comprising a login authentication module, a data input module, a quotation decision-making module, a short-period simulation module, a data processing module and a data output module, performing declaration scheme operation according to related parameters of the power system to obtain an energy storage declaration charging electricity price and a declaration discharging electricity price, and constructing X energy storage declaration information schemes; solving to obtain an energy storage short-period simulation result including the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit; and comparing the incomes of the X energy storage declaration information schemes to obtain an optimal decision scheme and outputting the optimal decision scheme. According to the method, the quotation decision forming model and the electric power spot market simulation model are combined, the formation of the charging and discharging power of the energy storage unit in the quotation scheme needs to meet various constraint conditions, and it is guaranteed that the simulation result can meet the actual operation reliability requirement of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of power generation and energy storage, and in particular to an energy storage quotation decision system and method for jointly clearing electric energy and auxiliary services. Background Art

[0002] In recent years, relevant national departments have improved the market mechanism for energy storage participation in accordance with the electricity reform and put forward guiding opinions on promoting the development of energy storage technology and industry. With the advancement of the domestic power market system reform, energy storage participates in the electricity spot market transactions as an independent entity, charging energy storage and paying electricity purchase fees during low market price periods, discharging energy storage and obtaining power generation income during high market price periods, and obtaining economic benefits through the difference between power generation income and electricity purchase fees.

[0003] The electricity market clearing model will transition from a single electricity energy market clearing model to a joint optimization clearing model of electricity energy and ancillary services to improve market efficiency. At present, independent energy storage power stations are in the early stages of commercialization. Researchers continue to analyze the level of market-based transactions and the profitability of energy storage based on the characteristics of energy storage power stations to achieve sustainable development of commercial energy storage. Therefore, how to combine independent energy storage power stations with the joint clearing market of electricity energy and ancillary services to improve market efficiency is an urgent problem that needs to be solved. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and to propose a system and method for energy storage quotation decision-making for the joint clearing of electric energy and ancillary services, which combines the quotation decision-making model with the electricity spot market simulation model, and can effectively realize the energy storage quotation decision-making function of the market mode of joint clearing of electric energy and ancillary services.

[0005] The present invention solves the technical problem by adopting the following technical solutions:

[0006] An energy storage quotation decision system for joint clearing of electric energy and auxiliary services, comprising a login authentication module, a data input module, a quotation decision module, a short-cycle simulation module, a data processing module and a data output module;

[0007] The login authentication module is used for user identity authentication, and after identity authentication, the user can enter the energy storage quotation decision system;

[0008] The data input module is connected to the login authentication module, and inputs the power system related parameters required by the simulation calculation module and the data processing module;

[0009] The quotation decision module is connected to the data input module, performs declaration scheme calculation according to the relevant parameters of the power system, obtains the declared charging electricity price and the declared discharging electricity price of the energy storage, and constructs X energy storage declaration information schemes;

[0010] The short-cycle simulation module is connected to the quotation decision module, receives X energy storage declaration information schemes from the quotation decision module, and obtains energy storage short-cycle simulation results including the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit through the short-cycle simulation model of the power spot market;

[0011] The data processing module is connected to the short-cycle simulation module, and calculates the income of each energy storage unit according to the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit in the energy storage short-cycle simulation result, and compares the income of the constructed X energy storage declaration information schemes. If the deviation result does not meet the planning requirements, the optimization parameters are corrected; if it meets the planning requirements, the optimal decision-making scheme is obtained and transmitted to the data output module;

[0012] The data output module is connected to the data processing module, and the optimal decision-making plan transmitted from the data processing module is formed into a report including energy storage charging electricity price and discharging electricity price and outputted.

[0013] A method for energy storage quotation decision-making for joint clearing of electric energy and auxiliary services comprises the following steps:

[0014] Step 1: Input the power system related parameters required by the simulation calculation module and the data processing module through the data input module;

[0015] Step 2: Receive power system related parameters through the quotation decision module, calculate the charging price and the discharging price, construct X energy storage declaration information schemes including the charging price and the discharging price, and transmit them to the short-cycle simulation module;

[0016] Step 3: Receive X energy storage declaration information plans through the short-cycle simulation module, establish a short-cycle simulation model for the electricity spot market, perform 96-period electricity market simulation calculations on the electricity market operation day D, obtain short-cycle simulation results for energy storage, and transmit the simulation results to the data processing module. The short-cycle simulation results include the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit;

[0017] Step 4: According to the short-term simulation results of each energy storage, the income of the energy storage unit is calculated through the data processing module, and the income of the constructed X energy storage declaration information schemes is compared to determine the optimal decision scheme and transmit the optimal decision scheme to the data output module;

[0018] Step 5: The data output module outputs the optimal decision-making plan transmitted from the data processing module in the form of a report.

[0019] The advantages and positive effects of the present invention are:

[0020] The present invention combines the quotation decision formation model with the electricity spot market simulation model, and realizes the energy storage quotation decision function of the electric energy and ancillary service joint clearing market mode. Among them, the quotation decision formation model considers the node predicted electricity price and sets logical constraints, and can obtain different quotation schemes; the electric energy and ancillary service joint clearing market is constructed through the 96-time period simulation model of the electricity spot market, and the electric energy constraint, upper reserve constraint, lower reserve constraint, upper frequency regulation constraint and lower frequency regulation constraint are fully considered. In the quotation scheme, the formation of the charging and discharging power of the energy storage unit needs to meet various constraints, which ensures that the simulation results can meet the actual operation reliability requirements of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A connection diagram of the energy storage quotation decision system for joint clearing of electric energy and auxiliary services of the present invention;

[0022] Figure 2 It is a flow chart of the energy storage quotation decision method for jointly clearing electric energy and auxiliary services of the present invention. DETAILED DESCRIPTION

[0023] The present invention is further described in detail below with reference to the accompanying drawings.

[0024] The design concept of the present invention is: the present invention is guided by the income of the energy storage unit, and is evenly divided with reference to the node predicted electricity price of the node where the energy storage unit is located. The enumeration method is adopted to form different energy storage unit quotation strategies through permutations and combinations without violating the logic of "low charge and high release".

[0025] First, the present invention needs to determine two indicators that can fully reflect the income of the energy storage unit, namely the electricity price at the node where the energy storage unit is located and the charging and discharging power of the energy storage unit; then establish a thermal power model that can reflect the unit's electricity energy cost, startup cost, and standby cost; establish an energy storage model that can reflect the operating characteristics such as energy storage charging and discharging efficiency, maximum energy storage unit charging and discharging power, and maximum storage capacity; construct a demand response behavior model based on electricity consumption characteristics and cost structure after users respond to spot market prices; and use transfer factors to establish a power grid constraint model.

[0026] Then, a 96-period simulation is performed to obtain the output of the energy storage units in the market, obtain simulation results that meet the system transmission security constraints, calculate the energy storage income of different bidding schemes, and select the scheme with the highest income as the final bidding scheme.

[0027] The innovative features of the present invention include: (1) a bidding decision-making model that takes into account the marginal electricity price of the predicted node and logical constraints; (2) a power spot market simulation model that uses mixed integer linear programming to construct a joint clearing market for electric energy and ancillary services; (3) combining the bidding strategy formation model with the power spot market simulation model to simulate market clearing and obtain the charging and discharging power and electricity price of the energy storage unit under different energy storage bidding conditions.

[0028] Based on the above design concept, the present invention proposes a storage quotation decision system for joint clearing of electric energy and auxiliary services, such as Figure 1 As shown, it includes login authentication module, data input module, quotation decision module, short cycle simulation module, data processing module and data output module. The following is a detailed description of each module in the system:

[0029] The login authentication module is used for user identity authentication, and after identity authentication, the user enters the energy storage quotation decision system.

[0030] The data input module is used to input the power system related parameters required by the simulation calculation module and the data processing module. The data input module is connected to the login authentication module. After the user logs in and authenticates, he inputs the power system related parameters; the power system related parameters include the power generation side information, the grid side information, and the load side information. Among them:

[0031] The information on the power generation side includes the installed capacity, busbar, no-load cost, climbing rate, landslide rate, startup cost, minimum output and quotation of thermal power units, as well as the installed capacity, busbar and timing power of new energy units.

[0032] The grid side information includes transmission topology, transmission flow constraints, etc.

[0033] Load side information includes substation load timing power, etc.

[0034] The quotation decision module is used to construct X energy storage declaration information schemes including charging electricity price and discharging electricity price; the quotation decision module is connected to the data input module, and can obtain the relevant data of the power generation side, the grid side and the load side given in the data input module, and perform declaration scheme calculation according to the obtained data to obtain the energy storage declared charging electricity price and declared discharging electricity price, thereby constructing X energy storage declaration information schemes and transmitting them to the short cycle simulation module.

[0035] The short-cycle simulation module is used to establish a short-cycle simulation model of the power spot market, run a 96-period timing program that meets the actual transmission safety constraints of the system, and obtain short-cycle simulation results (the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit); the short-cycle simulation module is connected to the quotation decision module, receives the calculation results of the quotation decision and the power system related parameters transmitted by the data input module, and obtains the short-cycle simulation results of energy storage (the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit) according to the short-cycle simulation model of the power spot market, and transmits the simulation results to the data processing module.

[0036] The data processing module is used to compare various energy storage declaration information schemes to obtain the optimal decision-making scheme; the data processing module is connected to the short-cycle simulation module, collects the 96-time period electricity prices and the charging and discharging power of the energy storage units of all energy storage schemes, calculates the income of the energy storage units, and compares the income of the constructed X energy storage declaration information schemes. If the deviation result does not meet the planning requirements, the optimization parameters are corrected; if it meets the planning requirements, the optimal decision-making scheme is obtained and transmitted to the data output module.

[0037] The data output module is used to output the optimal decision-making plan. The output module is connected to the data processing module and can output the optimal decision-making plan transmitted by the data processing module to form a report, which includes energy storage charging price and discharge price data.

[0038] Based on the above energy storage quotation decision system for joint clearing of electric energy and auxiliary services, the present invention also proposes an energy storage quotation decision method for joint clearing of electric energy and auxiliary services, such as Figure 2 As shown, the energy storage quotation decision method includes the following steps:

[0039] Step 1: Input the power system related parameters required by the simulation calculation module and the data processing module through the data input module.

[0040] In this step, the power system related parameters required for energy storage quotation decision system processing are input, such as the installed capacity, bus, no-load cost, climbing rate, landslide rate, startup cost, minimum output and quotation of thermal power units, the installed capacity, bus and time sequence power of new energy units, such as the transmission topology structure and transmission flow constraints on the grid side, and the load time sequence power of substations on the load side. The energy storage quotation decision method proposed in the present invention processes the above external data to obtain an energy storage quotation scheme that conforms to the laws of nature.

[0041] Step 2: Receive power system related parameters through the quotation decision module, calculate the charging price and the discharging price, construct X energy storage declaration information schemes including the charging price and the discharging price, and transmit them to the short-term simulation module.

[0042] The specific implementation method of this step includes the following steps:

[0043] Step 2.1, obtain the electricity price time series prediction curve of the node where the energy storage unit is located.

[0044] Step 2.2: Set the constraints of the energy storage bidding decision model. Specifically, the constraints of the energy storage bidding decision model are as follows:

[0045] (1) Upper limit of energy storage charging electricity price quotation

[0046]

[0047] In the formula, is the charging price of energy storage i during period t, Predict the maximum electricity price for the i energy storage in 96 time periods.

[0048] (2) Lower limit of energy storage discharge price quotation

[0049]

[0050] In the formula, is the discharge price of energy storage i during period t, The minimum electricity price for energy storage i in 96 time periods is predicted.

[0051] (3) Energy storage charging and discharging logic limitations

[0052]

[0053] Step 2.3, construct X energy storage declaration information schemes: According to the maximum and minimum electricity prices of 96 time periods obtained by the i energy storage forecast, the electricity price range is equally divided, and X energy storage declaration information schemes are formed under the constraints of step 2.2.

[0054] Step 3: Receive X energy storage declaration information schemes through the short-cycle simulation module, establish a short-cycle simulation model for the electricity spot market, perform 96-period electricity market simulation calculations on the electricity market operation day D, obtain the short-cycle simulation results of energy storage (the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit), and transmit the simulation results to the data processing module.

[0055] The specific implementation method of this step is:

[0056] Step 3.1: Determine the short-term simulation model of the electricity spot market to maximize social welfare as the objective function.

[0057] The optimization goal of the present invention is mainly social welfare, so its objective function maximizes social welfare rather than minimizing the system power generation cost. The objective function is as follows:

[0058]

[0059] In the above formula, I is the set of all units, I V is the bidding unit set, I S is the energy storage unit set, J is the set of all loads, L is the branch set, M is the section set, and T is the time period set. is the consumer surplus at load j during period t, is the demand response reserve cost for load j during period t, is the startup cost of unit i during period t, is the no-load cost of unit i, is the electricity cost of unit i during period t, is the standby cost of unit i during period t, is the frequency regulation cost of unit i during period t, u i,t is the 0-1 variable for the operation / shutdown of unit i during period t, γ L is the branch slack variable cost, γ M is the section slack variable cost, γ J is the load slack variable cost, is the branch slack variable, is the section relaxation variable, is the slack variable in the target programming.

[0060] Step 3.2: Determine the safety constraints that meet the various reliability requirements of the system and establish a power market simulation model to simulate the 96 time periods on D day.

[0061] The safety constraints of this step are as follows:

[0062] (1) Unit electricity cost

[0063]

[0064] In the above formula, BU is the quotation segment set. The output of unit i in period b is increased. The quotation for the electric energy in period b of unit i during period t.

[0065] (2) Load electricity cost

[0066]

[0067] In the above formula The output increase of the quotation period b in the load period j is: The demand response electricity energy quotation for load j in time period b.

[0068] (3) Energy storage electricity cost

[0069]

[0070] In the above formula is the energy storage discharge power, Charging power for energy storage.

[0071] (4) Unit standby cost

[0072]

[0073] In the above formula The i unit is on standby during period t. The i unit is in standby mode during period t. is the standby quotation price of unit i during period t, is the standby quotation price of unit i during period t.

[0074] (5) Load backup cost

[0075]

[0076] In the above formula The reserve for demand response of load j during period t is: is the reserve under demand response of load j during period t, is the reserve quotation price for demand response of load j during period t, is the reserve quotation price under demand response of load j during period t.

[0077] (6) Unit frequency regulation cost

[0078]

[0079] In the above formula, ra i,t is the frequency regulation capacity of unit i during period t, The price of frequency regulation combination sorting of unit i in period t.

[0080] (7) Unit startup cost

[0081]

[0082] In the above formula, y i,t is the unit startup 0-1 variable for unit i in period t, is the startup cost of unit i in period t.

[0083] (8) Output limit of unit quotation section

[0084]

[0085] In the above formula It is the upper limit of the output of the electricity energy quotation segment b of unit i in period t.

[0086] (9) Total unit output

[0087]

[0088] In the above formula, p i,t is the total output of unit i during period t.

[0089] (10) Total load demand

[0090]

[0091] In the above formula is the basic output of load j during period t, p j,t is the total load demand during load period j and time period t.

[0092] (11) Upper limit of unit output

[0093]

[0094] In the above formula, x i,t is the 0-1 variable of the winning bid for frequency regulation of unit i in period t, is the upper limit of unit frequency regulation for unit i during period t, u i,t is the running / shutdown 0-1 variable of unit i in period t, is the upper limit of unit output of unit i in period t.

[0095] (12) Lower limit of unit output

[0096]

[0097] In the above formula is the lower limit of unit frequency regulation for unit i during period t, is the lower limit of unit output of unit i in period t.

[0098] (13) Load demand upper limit

[0099]

[0100] In the above formula is the lower limit of load demand response in load j period t.

[0101] (14) Load demand lower limit

[0102]

[0103] In the above formula is the upper limit of load demand response in load j during period t.

[0104] (15) Unit standby limit

[0105]

[0106] In the above formula is the upper limit of the reserve of unit i during period t.

[0107] (16) Unit standby limit

[0108]

[0109] In the above formula is the lower reserve upper limit of unit i during period t.

[0110] (17) Load reserve limit

[0111]

[0112] In the above formula is the upper reserve limit of load j during period t.

[0113] (18) Reserve limit under load

[0114]

[0115] In the above formula is the upper limit of reserve under load j in period t.

[0116] (19) Unit frequency regulation capacity limitation

[0117]

[0118] In the above formula is the upper limit of the frequency regulation capacity of unit i in period t.

[0119] (20) Unit start and stop variable constraints

[0120]

[0121] In the above formula, z i,t is the 0-1 variable of unit shutdown during period t of unit i, u i,0 is the initial operation / shutdown 0-1 variable of unit i, is the duration that the initial state of unit i in period t needs to last.

[0122] (21) Unit frequency regulation variable constraints

[0123]

[0124] (22) Unit startup response time constraints

[0125]

[0126] (23) Minimum operating time constraints for units

[0127]

[0128] In the above formula, T min_on It is the minimum operating time of the unit.

[0129] (24) Minimum downtime constraints for units

[0130]

[0131] In the above formula, T min_off Minimum downtime of the unit

[0132] (25) Unit climbing constraints

[0133]

[0134] In the above formula, RD i is the ramp capacity of unit i, RU i is the ramp capacity of unit i.

[0135] (26) Energy storage unit model

[0136]

[0137] In the above formula, e i,t is the power of energy storage unit i during period t, η dc is the energy storage discharge power of the energy storage unit, η ch is the energy storage charging power of the energy storage unit, is the maximum power of energy storage unit i during period t, The upward flexible climbing capability provided for the energy storage discharge of energy storage unit i during period t, The downward flexible climbing capability provided for the energy storage discharge of energy storage unit i during period t, The upward flexible climbing capability provided for the energy storage charging of energy storage unit i during period t, The downward flexible climbing capability provided for the energy storage charging of energy storage unit i during period t, is the minimum discharge power of energy storage unit i during period t, is the maximum discharge power of energy storage unit i during period t, is the minimum charging power of energy storage unit i during period t, is the maximum charging power of energy storage unit i during period t.

[0138] (27) System backup constraints

[0139]

[0140] In the above formula It is the upper limit of the system reserve in period t.

[0141] (28) System backup constraints

[0142]

[0143] In the above formula It is the upper limit of the system reserve in period t.

[0144] (29) System frequency modulation capacity constraints

[0145]

[0146] In the above formula is the upper limit of frequency modulation capacity in period t.

[0147] (30) System flexibility ramping demand constraints

[0148]

[0149] in:

[0150]

[0151] In the above formula, FRU t is the upward flexibility ramp demand during period t, FRD t is the downward flexibility ramping demand during period t, is the net load during period t, is the upward deviation of the net load in period t, is the downward deviation of the net load during period t.

[0152] (31) Power balance constraint

[0153]

[0154] In the above formula, σ i is the plant utilization rate of unit i, LS t is the system network loss during period t.

[0155] (32) Branch flow constraints

[0156]

[0157] In the above formula, SF l,i,t is the transfer factor, is the lower limit of the power flow in branch l during period t, is the upper limit of the power flow in branch l during period t.

[0158] (33) Sectional flow constraints

[0159]

[0160] In the above formula is the lower limit of the tidal current in section m during period t, is the upper limit of the tidal flow in section m during period t.

[0161] Step 4: According to the short-term simulation results of each energy storage (96-period electricity price of energy storage and charging and discharging power of energy storage unit), the income of energy storage unit is calculated through the data processing module, and the income of the constructed X energy storage declaration information schemes is compared to determine the optimal decision scheme and transmit the optimal decision scheme to the data output module.

[0162] The specific implementation method of this step is:

[0163] Obtain the node predicted electricity price and simulated power information of the energy storage unit for 96 periods, multiply the electricity price and power of each period and sum them as the income of the energy storage unit:

[0164]

[0165] In the above formula, INC i,x is the total revenue of the x-bid scheme of i energy storage obtained through simulation for 96 periods, Predict the electricity price for the node where the i energy storage is located during period t.

[0166] If a plan has the highest income among the X plans constructed, then this plan is used as the optimal bidding strategy and goes to step 5 for output.

[0167] Step 5: The data output module outputs the optimal quotation solution (charging electricity price, discharging electricity price) transmitted by the data processing module in the form of a report.

[0168] It should be emphasized that the embodiments described in the present invention are illustrative rather than restrictive. Therefore, the present invention includes but is not limited to the embodiments described in the specific implementation manner. Any other implementation manners derived by those skilled in the art based on the technical solution of the present invention also fall within the scope of protection of the present invention.

Claims

1. A storage quotation decision system for joint clearing of electric energy and auxiliary services, characterized by: It includes login authentication module, data input module, quotation decision module, short cycle simulation module, data processing module and data output module; The login authentication module is used for user identity authentication, and after identity authentication, the user can enter the energy storage quotation decision system; The data input module is connected to the login authentication module, and inputs the power system related parameters required by the simulation calculation module and the data processing module; The quotation decision module is connected to the data input module, performs declaration scheme calculation according to the relevant parameters of the power system, obtains the declared charging electricity price and the declared discharging electricity price of the energy storage, and constructs X energy storage declaration information schemes; The short-cycle simulation module is connected to the quotation decision module, receives X energy storage declaration information schemes from the quotation decision module, and obtains energy storage short-cycle simulation results including the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit through the short-cycle simulation model of the power spot market; The data processing module is connected to the short-cycle simulation module, and calculates the income of each energy storage unit according to the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit in the energy storage short-cycle simulation result, and compares the income of the constructed X energy storage declaration information schemes. If the deviation result does not meet the planning requirements, the optimization parameters are corrected; if it meets the planning requirements, the optimal decision-making scheme is obtained and transmitted to the data output module; The data output module is connected to the data processing module, and the optimal decision-making plan transmitted from the data processing module is formed into a report including energy storage charging electricity price and discharging electricity price and outputted.

2. The energy storage quotation decision system for joint clearing of electric energy and auxiliary services according to claim 1 is characterized by: The power system related parameters include power generation side information, grid side information, and load side information.

3. The energy storage quotation decision system for joint clearing of electric energy and auxiliary services according to claim 2 is characterized by: The power generation side information includes the installed capacity, busbar, no-load cost, ramp rate, landslide rate, startup cost, minimum output and quotation of thermal power units, and the installed capacity, busbar and time sequence power of new energy units; The grid side information includes transmission topology and transmission power flow constraints; The load side information includes substation load time sequence power.

4. A decision-making method for an energy storage quotation decision system for joint clearing of electric energy and auxiliary services according to any one of claims 1 to 3, characterized in that: The following steps are involved: Step 1: Input the power system related parameters required by the simulation calculation module and the data processing module through the data input module; Step 2: Receive power system related parameters through the quotation decision module, calculate the charging price and the discharging price, construct X energy storage declaration information schemes including the charging price and the discharging price, and transmit them to the short-cycle simulation module; Step 3: Receive X energy storage declaration information plans through the short-cycle simulation module, establish a short-cycle simulation model for the electricity spot market, perform 96-period electricity market simulation calculations on the electricity market operation day D, obtain short-cycle simulation results for energy storage, and transmit the simulation results to the data processing module. The short-cycle simulation results include the electricity price of the node where the energy storage unit is located and the charging and discharging power of the energy storage unit; Step 4: According to the short-term simulation results of each energy storage, the income of the energy storage unit is calculated through the data processing module, and the income of the constructed X energy storage declaration information schemes is compared to determine the optimal decision scheme and transmit the optimal decision scheme to the data output module; Step 5: The data output module outputs the optimal decision-making plan transmitted from the data processing module in the form of a report.

5. The decision-making method of the energy storage quotation decision-making system for joint clearing of electric energy and auxiliary services according to claim 4 is characterized by: The specific implementation method of step 2 includes the following steps: Step 2.1, obtaining the electricity price time series prediction curve of the node where the energy storage unit is located; Step 2.2: Set the following constraints for the energy storage bidding decision model: (1) Upper limit of energy storage charging price quotation: In the formula, is the charging price of energy storage i during period t, Predict the maximum electricity price for 96 periods for the i energy storage; (2) Lower limit of energy storage discharge price quotation: In the formula, is the discharge price of energy storage i during period t, Predict the minimum electricity price for 96 time periods for energy storage i; (3) Energy storage charging and discharging logic limitations: Step 2.3, construct X energy storage declaration information schemes: According to the maximum and minimum electricity prices of 96 time periods obtained by the i energy storage forecast, the electricity price range is equally divided, and X energy storage declaration information schemes are formed under the constraints of step 2.

2.

6. The decision-making method of the energy storage quotation decision-making system for joint clearing of electric energy and auxiliary services according to claim 4 is characterized by: The short-cycle simulation model of the electricity spot market constructed in step 3 takes maximizing social welfare as its objective function, which is: In the above formula, I is the set of all units, I V is the bidding unit set, I S is the energy storage unit set, J is the set of all loads, L is the branch set, M is the section set, T is the time period set, is the consumer surplus at load j during period t, is the demand response reserve cost for load j during period t, is the startup cost of unit i during period t, is the no-load cost of unit i, is the electricity cost of unit i during period t, is the standby cost of unit i during period t, is the frequency regulation cost of unit i during period t, u i，t is the 0-1 variable for the operation / shutdown of unit i during period t, γ L is the branch slack variable cost, γ M is the section slack variable cost, γ J is the load slack variable cost, is the branch slack variable, is the section relaxation variable, is the slack variable in the target programming.

7. The decision-making method of the energy storage quotation decision-making system for joint clearing of electric energy and auxiliary services according to claim 4 is characterized by: When constructing the short-cycle simulation model of the electricity spot market in step 3, the following safety constraints are determined: Electric energy cost of the unit: In the above formula, BU is the quotation segment set. The output of unit i in period b is increased. The quotation for the electric energy quotation period b of unit i in period t; Load electrical energy cost: In the above formula The output increase of the quotation period b for the load period j is: The demand response electric energy quotation segment price of load j in period b; Energy storage electricity cost: In the above formula is the energy storage discharge power, Charging power for energy storage; Unit standby cost: In the above formula The i unit is on standby during period t. The i unit is in standby mode during period t. is the standby quotation price of unit i during period t, is the standby price of unit i at time period t; Load backup cost: In the above formula is the demand response reserve for load j during period t, is the reserve under demand response of load j during period t, is the reserve quotation price for demand response of load j during period t, is the reserve quotation price under the demand response of load j during period t; Unit frequency regulation cost: In the above formula, ra i，t is the frequency regulation capacity of unit i during period t, The price of frequency regulation combination ranking of unit i in period t; Unit startup cost: In the above formula, yi,t is the unit startup 0-1 variable of unit i in period t, is the startup cost of unit i during period t; Output limit of unit quotation section: In the above formula is the output upper limit of the electricity energy quotation period b of unit i in period t; Total output of the unit: In the above formula, p i，t is the total output of unit i during period t; Total load demand: In the above formula is the basic output of load j during period t, p j，t is the total load demand during period j of load t; Upper limit of unit output: In the above formula, x i，t is the 0-1 variable of the winning bid for frequency regulation of unit i in period t, is the upper limit of unit frequency regulation for unit i during period t, u i，t is the running / shutdown 0-1 variable of unit i in period t, is the upper limit of the unit output of unit i during period t; Unit output lower limit: In the above formula is the lower limit of unit frequency regulation for unit i during period t, is the lower limit of unit output of unit i during period t; Load demand upper limit: In the above formula is the lower limit of load demand response for load j during period t; Load demand lower limit: In the above formula is the upper limit of load demand response for load j during period t; Reserve limit on the unit: In the above formula is the upper reserve limit of unit i during period t; Unit standby limit: In the above formula is the upper limit of the reserve of unit i during period t; Reserve limit on load: In the above formula is the upper reserve limit of load j during period t; Reserve limit under load: In the above formula is the upper limit of reserve under load j during period t; Unit frequency regulation capacity limit: In the above formula is the upper limit of the frequency regulation capacity of unit i during period t; Unit start and stop variable constraints: In the above formula, z i，t is the 0-1 variable of unit shutdown during period t of unit i, u i，0 is the initial operation / shutdown 0-1 variable of unit i, The duration of the initial state of unit i during period t; Unit frequency regulation variable constraints: Unit startup response time constraints: Minimum operating time constraints for units: In the above formula, T min_on is the minimum operating time of the unit; Minimum downtime constraints for units: In the above formula, T min_off The minimum downtime of the unit; Unit climbing constraints: In the above formula, RD i is the ramp capacity of unit i, RU i is the ramp capacity of unit i; Energy storage unit model: In the above formula, e i，t is the power of energy storage unit i during period t, η dc is the energy storage discharge power of the energy storage unit, η ch is the energy storage charging power of the energy storage unit, is the maximum power of energy storage unit i during period t, The upward flexible climbing capability provided for the energy storage discharge of energy storage unit i during period t, The downward flexible climbing capability provided for the energy storage discharge of energy storage unit i during period t, The upward flexible climbing capability provided for the energy storage charging of energy storage unit i during period t, The downward flexible climbing capability provided for the energy storage charging of energy storage unit i during period t, is the minimum discharge power of energy storage unit i during period t, is the maximum discharge power of energy storage unit i during period t, is the minimum charging power of energy storage unit i during period t, is the maximum charging power of energy storage unit i during period t; Spare constraints on the system: In the above formula The upper limit of the system reserve during period t; System backup constraints: In the above formula The upper limit of the system reserve in period t; System frequency regulation capacity constraints: In the above formula is the upper limit of frequency regulation capacity during period t; System flexibility ramping demand constraints: in: In the above formula, FRU t is the upward flexibility ramp demand during period t, FRD t is the downward flexibility ramping demand during period t, is the net load during period t, is the upward deviation of the net load during period t, is the downward deviation of net load in period t; Power balance constraints: In the above formula, σ i is the plant utilization rate of unit i, LS t is the system network loss during period t; Branch flow constraints: In the above formula, SF l，i，t is the transfer factor, is the lower limit of the branch power flow in period t, is the upper limit of the branch power flow in period t; Section flow constraints: In the above formula is the lower limit of the tidal current in section m during period t, is the upper limit of the tidal flow in section m during period t.

8. The decision-making method of the energy storage quotation decision-making system for joint clearing of electric energy and auxiliary services according to claim 4 is characterized by: The method for calculating the income of the energy storage unit in step 4 is: obtaining the node predicted electricity price of the energy storage unit in 96 time periods and the power information obtained by simulation, multiplying the electricity price and power of each time period and summing them as the income of the energy storage unit: In the above formula, INC i，x is the total revenue of the x-bid scheme of i energy storage obtained through simulation for 96 periods, Predict the electricity price for the node i where the energy storage is located during period t.

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