Pumped storage power station marketization multi-variety collaborative transaction method and system

Abstract

The invention discloses a pumped storage power station marketization multi-variety collaborative transaction method and system. The method comprises the following steps: determining conditional risk value brought to market transaction by wind power output uncertainty; constructing a lower-layer spot market clearing model by taking minimum system operation cost as a first objective function under a first preset constraint condition according to the conditional value-at-risk; constructing an upper layer pumped storage operator optimization model by taking operation income maximization as a second objective function under a second preset constraint condition; and constructing a KKT condition of the lower-layer spot market clearing model, converting the lower-layer spot market clearing model into a constraint condition of the upper-layer pumped storage operator optimization model, and outputting a game equilibrium solution after solving by adopting Yalmip / Cplex. The decision-making advantage of pumped storage in the spot market can be effectively exerted, investment cost recovery and efficient operation are promoted, peak regulation and frequency modulation of a power grid are assisted, and the benefit win-win effect of a pumped storage power station and the power grid is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of pumped - storage energy participating in electricity market transactions, and particularly relates to a market - oriented multi - variety collaborative trading method and system for a pumped - storage power station. Background Art

[0002] In view of the problem that it is difficult to recover the investment cost of pumped - storage under the existing market mechanism, the state has gradually promoted pumped - storage power stations to enter the market, and has made efforts to improve the scientificity, operability, and effectiveness of the electricity price formation mechanism; the electricity market gives full play to the electricity price incentive to mobilize the enthusiasm of each market participant, creating more favorable conditions for the rapid development of pumped - storage power stations and the full play of their comprehensive benefits. At present, the dispatching methods for pumped - storage participating in the spot market mainly include three modes: not reporting quantity and not quoting price, reporting quantity but not quoting price, and reporting quantity and quoting price. However, all of them have the problem that they cannot fully exert the initiative of pumped - storage power stations and obtain their expected benefits, which affects the enthusiasm of pumped - storage participating in the market.

[0003] Therefore, in order to fully tap the potential of pumped - storage resources to promote the consumption of new energy in the power grid and quantify the value of its regulation services, encourage pumped - storage to participate in spot market transactions as an independent market entity, consider the coordinated dispatching between pumped - storage and other market entities, and enable it to realize the recovery of pumped - storage costs and efficient operation through a sound electricity energy market and ancillary service market, so as to meet the dual demands of electricity energy and frequency modulation for the safe, economic operation of the power grid and the consumption of new energy. At present, the market environment is in a development transition period, and there is no clear plan for pumped - storage power stations to participate in the electricity market. The market - oriented trading method of pumped - storage urgently needs further research. Summary of the Invention

[0004] The invention provides a market - oriented multi - variety collaborative trading method and system for a pumped - storage power station, proposes a collaborative bidding strategy for pumped - storage power stations to participate in the electricity energy and frequency modulation service spot markets, and constructs a principal - agent game model between pumped - storage power stations and the dual markets to promote the recovery of their investment costs and efficient operation.

[0005] In the first aspect, the invention provides a market - oriented multi - variety collaborative trading method for a pumped - storage power station, including:

[0006] Determine the conditional value - at - risk brought by the uncertainty of wind power output to market transactions;

[0007] Construct a lower - layer spot market clearing model with the minimum system operation cost as the first objective function under the first preset constraint condition according to the conditional value - at - risk;

[0008] Construct an upper - layer pumped - storage operator optimization model with the maximum operation revenue as the second objective function under the second preset constraint condition;

[0009] Construct the KKT conditions of the lower-layer spot market clearing model, convert the lower-layer spot market clearing model into the constraint conditions of the upper-layer pumped-storage power operator optimization model, and use Yalmip / Cplex to solve and output the game equilibrium solution.

[0010] In a second aspect, the present invention provides a market-oriented multi-variety collaborative trading system for a pumped-storage power station, including:

[0011] A determination module configured to determine the conditional value at risk brought by the uncertainty of wind power output to market trading;

[0012] A first construction module configured to construct a lower-layer spot market clearing model with the minimum system operation cost as the first objective function under the first preset constraint conditions according to the conditional value at risk;

[0013] A second construction module constructs an upper-layer pumped-storage power operator optimization model with the maximum operating income as the second objective function under the second preset constraint conditions;

[0014] A solution module configured to construct the KKT conditions of the lower-layer spot market clearing model, convert the lower-layer spot market clearing model into the constraint conditions of the upper-layer pumped-storage power operator optimization model, and use Yalmip / Cplex to solve and output the game equilibrium solution.

[0015] In a third aspect, an electronic device is provided, which includes: 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 enable the at least one processor to execute the steps of the market-oriented multi-variety collaborative trading method of the pumped-storage power station according to any embodiment of the present invention.

[0016] In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program instructions are executed by a processor, the processor is enabled to execute the steps of the market-oriented multi-variety collaborative trading method of the pumped-storage power station according to any embodiment of the present invention.

[0017] The market-oriented multi-variety collaborative trading method and system for pumped storage power stations of the present application establish a two-layer optimization model for the combined bidding of pumped storage participating in the electric energy market and the ancillary service market; construct a value-at-risk model for the uncertainty of wind power output; construct a clearing model for the underlying spot market; construct an optimization model for pumped storage operators in the upper layer; construct the KKT conditions for the clearing model of the underlying spot market, convert the lower-layer model into the constraint conditions of the upper-layer model, and output the game equilibrium solution after solving with Yalmip / Cplex, which can effectively exert the decision-making advantage of pumped storage in the spot market, promote the recovery of its investment costs and efficient operation, and assist the power grid in peak shaving and frequency modulation, achieving a win-win situation for both pumped storage power stations and the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a flowchart of a market-oriented multi-variety collaborative trading method for a pumped storage power station provided by an embodiment of the present invention;

[0020] Figure 2 It is a modified IEEE30 network structure diagram of a specific embodiment provided by an embodiment of the present invention;

[0021] Figure 3 It is a load power curve of a specific embodiment provided by an embodiment of the present invention;

[0022] Figure 4 It is a frequency modulation mileage factor curve in the frequency modulation demand of a specific embodiment provided by an embodiment of the present invention;

[0023] Figure 5 It is a predicted output scenario curve diagram of a wind power cluster of a specific embodiment provided by an embodiment of the present invention;

[0024] Figure 6 It is a probability distribution diagram of a wind power scenario of a specific embodiment provided by an embodiment of the present invention;

[0025] Figure 7 It is a clearing electricity price of the electric energy market and the output curve of pumped storage participating in the electric energy market of a specific embodiment provided by an embodiment of the present invention;

[0026] Figure 8 It is a bar chart of the day-ahead output of each unit in the electric energy market of a specific embodiment provided by an embodiment of the present invention;

[0027] Figure 9Provide the clearing result of a specific embodiment of the frequency modulation capacity market for an embodiment of the present invention;

[0028] Figure 10 Provide the clearing result of the frequency modulation mileage market for an embodiment of the present invention;

[0029] Figure 11 Provide the clearing results of the frequency modulation capacity electricity price and the frequency modulation mileage electricity price for an embodiment of the present invention;

[0030] Figure 12 Provide the value at risk and the pumped-storage operation income results under different risk factors for an embodiment of the present invention;

[0031] Figure 13 Provide the value at risk and the total system operation cost results under different risk factors for an embodiment of the present invention;

[0032] Figure 14 Provide the output curve of the pumped-storage participating in the electric energy market under different risk preference factors for an embodiment of the present invention;

[0033] Figure 15 Provide the structural block diagram of a market-oriented multi-variety collaborative trading system for a pumped-storage power station for an embodiment of the present invention;

[0034] Figure 16 It is the structural schematic diagram of an electronic device provided for an embodiment of the present invention. Detailed implementation manners

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0036] Please refer to Figure 1 , which shows the flowchart of a market-oriented multi-variety collaborative trading method for a pumped-storage power station of the present application.

[0037] As Figure 1 shown, the market-oriented multi-variety collaborative trading method for a pumped-storage power station specifically includes the following steps:

[0038] Step S101, determine the conditional value at risk brought by the uncertainty of wind power output to market trading.

[0039] In this step, the expression for calculating the conditional value at risk (CVaR) brought by the uncertainty of wind power output to market transactions is as follows:

[0040]

[0041] In the formula, C CVaR is the conditional value at risk of the uncertainty of wind power output, β is the confidence level, α is the value at risk at the β confidence level, N represents the number of scenarios of wind power output, π i is the probability of scenario i, is the risk loss in the i-th scenario, C loss is the risk loss, λ RE is the penalty coefficient for wind power output deviation.

[0042] Step S102: Construct a lower-layer spot market clearing model with the minimum system operation cost as the first objective function under the first preset constraint conditions according to the conditional value at risk.

[0043] In this step, the expression of the first objective function is:

[0044] m in f 2 = C bs + C pump + μC CvaR ,

[0045] In the formula, min f 2 is to minimize the objective function of the lower-layer spot market, C bs is the bid cost of thermal power units, C pump is the pumping / generation cost of pumped storage units, C CVaR is the conditional value at risk of the uncertainty of wind power output, and μ is the risk preference factor.

[0046] It should be noted that the first preset constraint conditions include power balance constraint, frequency modulation capacity / mileage balance constraint, thermal power frequency modulation capacity / mileage operation constraint, upper and lower limits of thermal power unit output, line transmission power safety check, CVaR risk value constraint, and upper and lower limits of pumped storage energy / frequency modulation capacity;

[0047] The power balance constraint is:

[0048]

[0049] In the formula, P t L is the market demand load at time t; P t WT，f is the wind power output at time t; represents the output of fixed units at time t. Units that do not participate in market regulation are called fixed units, and the others are bidding units; is the dual of the equation, P t T is the pumped-storage power generation at time t, is the power generation of thermal power unit i at time t, P t P is the pumped-storage pumping power at time t;

[0050] The frequency regulation capacity / mileage balance constraint is:

[0051]

[0052] In the formula, is the frequency regulation capacity declared by thermal power unit i in the ancillary service market at time t, P t f is the frequency regulation capacity declared by pumped-storage at time t, is the frequency regulation mileage declared by thermal power unit i in the ancillary service market at time t, R is the ratio of frequency regulation mileage to frequency regulation capacity, is the frequency regulation capacity in the spot market at time t, is the frequency regulation mileage demand at time t, is the clearing price of frequency regulation capacity in the spot market at time t, is the clearing price of frequency regulation mileage at time t;

[0053] The thermal power frequency regulation capacity / mileage operation constraint is:

[0054]

[0055] In the formula, is the maximum frequency regulation capacity of thermal power unit i at time t, is the ratio of frequency regulation mileage to frequency regulation capacity of thermal power unit i at time t, are the dual variables of the corresponding constraint conditions respectively;

[0056] The upper and lower limits of thermal power unit output constraint are:

[0057]

[0058] In the formula, P i THmin 、P i THmax are the maximum and minimum power generations of generator set i respectively, is the power generation of generator set i, δ i is the ramp rate percentage of generator set i, is the power generation of generator set i at time t, is the power generation of generator set i at time t - 1, are the dual variables of the corresponding constraint conditions respectively;

[0059] The line transmission power security check is as follows:

[0060]

[0061] In the formula, P l max is the power transmission limit of Line 1, g l，k is the transmission power distribution factor of Node k to Line 1, q k，t is the total output of the unit at Node k at time t, D k,t is the load at Node k at time t, are the dual variables of the corresponding constraint conditions respectively, and N is the total number of nodes in the network;

[0062] The CVaR value-at-risk constraint is as follows:

[0063]

[0064] In the formula, Z i is the introduced auxiliary variable, representing the difference between the loss function and the value-at-risk under Scenario i, λ RE is the wind power output deviation penalty coefficient, P t wT，r is the actual wind power output at time t, P t wT，f is the predicted wind power output at time t, and α is the value-at-risk (VaR value) at the β confidence level, are the dual variables of the corresponding constraint conditions respectively;

[0065] The upper and lower limit constraints of the pumped-storage electric energy / frequency regulation capacity are as follows:

[0066]

[0067] In the formula, is the minimum power generation of the pumped-storage, P t P is the pumping power of the pumped-storage at time t, P t f is the power generation of the pumped-storage at time t, and is the maximum power generation of the pumped-storage, is the maximum frequency regulation capacity of the pumped-storage at time t, is the frequency regulation capacity of the pumped-storage at time t, are the dual variables of the corresponding constraint conditions respectively.

[0068] Step S103: Construct an upper-layer pumped-storage operator optimization model with the maximum operating revenue as the second objective function under the second preset constraint conditions.

[0069] In this step, the expression of the second objective function is:

[0070]

[0071] where max f 1 is the maximum value of the objective function of the upper - layer pumped - storage operator, is the clearing price of the electricity energy market at time t, and P t P is the pumping power of the pumped - storage at time t, and P t T is the generating power of the pumped - storage at time t, is the clearing price of the frequency - regulation capacity in the spot market at time t, and P t f is the declared frequency - regulation capacity of the pumped - storage in the t - period, is the clearing price of the frequency - regulation mileage in the spot market at time t, and R is the ratio of the frequency - regulation mileage to the frequency - regulation capacity.

[0072] It should be noted that the second preset constraint conditions include the upper and lower limits of the unit output constraint, the operating state constraint of the pumped - storage unit, the daily start - stop times constraint of the pumped - storage unit, and the reservoir capacity constraint;

[0073] The upper and lower limits of the unit output constraint are:

[0074]

[0075] where are all Boolean variables, representing the pumping operating state and the generating operating state of the pumped - storage unit at time t respectively;

[0076] The operating state constraint of the pumped - storage unit is:

[0077]

[0078] where represent that the pumped - storage is in the starting state of the generating condition and the starting state of the pumping condition at time t respectively, and are all Boolean variables. The Boolean variable is the shutdown state of the pumped - storage in the pumping condition at time t, and the Boolean variable is the shutdown state of the pumped - storage in the generating condition at time t;

[0079] The daily start - stop times constraint of the pumped - storage unit is:

[0080]

[0081] where W pump is the maximum allowable number of start - stop times of the pumped - storage unit per day;

[0082] The reservoir capacity constraint is:

[0083]

[0084] where V t h is the energy capacity (MWh) equivalent to the upper reservoir storage at time t, and represent the maximum and minimum equivalent energy capacities (MWh) of the upper reservoir storage respectively, η is the comprehensive operating efficiency of the pumped-storage unit, V init and are the equivalent energy capacities (MWh) of the upper reservoir storage at the initial time and time T respectively, is the energy capacity (MWh) equivalent to the upper reservoir storage at time t - 1.

[0085] Step S104: Construct the KKT conditions of the lower-layer spot market clearing model, convert the lower-layer spot market clearing model into the constraint conditions of the upper-layer pumped-storage operator optimization model, and use Yalmip / Cplex to solve and output the game equilibrium solution.

[0086] In this step, input the initial bid quantities and pumped-storage operation parameters of each market participant and the electricity quantity of the load demand; construct the strategy sets of the game participants, where the strategy sets of the game participants include the leader strategy set and the follower strategy set; use the scenario analysis method to generate typical wind power scenarios, use the Monte Carlo method to randomly generate a large number of sample data, reduce the typical wind power scenarios through K-means clustering, and calculate the probability values of different scenarios; convert the lower-layer spot market clearing model into the constraints of the upper-layer pumped-storage operator optimization model using the KKT conditions, and linearize the objective function of the upper-layer pumped-storage operator optimization model; use Yalmip / Cplex to solve the transformed single-layer linear optimization model; output the game equilibrium solution, including the optimal clearing electricity price of each market and the optimal winning bid electricity quantity of each market participant, and the game process ends.

[0087] In summary, the method of this application establishes a two-layer optimization model for the joint bidding of pumped-storage participation in the electricity energy market and the ancillary service market; constructs a value-at-risk model for the uncertainty of wind power output; constructs a lower-layer spot market clearing model; constructs an upper-layer pumped-storage operator optimization model; constructs the KKT conditions of the lower-layer spot market clearing model, converts the lower-layer model into the constraint conditions of the upper-layer model, and uses Yalmip / Cplex to solve and output the game equilibrium solution, which can effectively exert the decision-making advantage of pumped-storage in the spot market, promote the recovery of its investment costs and efficient operation, and assist the power grid in peak regulation and frequency modulation, achieving a win-win situation for pumped-storage power stations and the power grid.

[0088] In a specific embodiment, the case simulation is based on the IEEE 30-node system. On this basis, four market participants, namely, one pumped-storage unit, two thermal power units, and one wind power cluster, are introduced, all of which are competitive bidding units. Among them, the total installed capacity of the two thermal power units is 600 MW; the installed capacity of the wind power cluster is 500 MW, and the installed capacity of the pumped-storage is 160 MW. The parameters of the pumped-storage unit are shown in Table 1, and the detailed parameters of the thermal power units are shown in Table 2. The modified IEEE 30-node network is as Figure 2 shown: Among them, two competitive bidding thermal power units, one pumped-storage unit, and one wind power unit are respectively set at nodes 11, 13, 18, and 24, and the rest of the conventional units are fixed units.

[0089] The system base capacity is taken as 100 MVA, and the base voltage is taken as the average rated voltage; the maximum transmission power of the line is obtained according to the line impedance parameters; the total load ratio borne by each load node is shown in Appendix B, and the total sum forms the total load demand power, as Figure 3 shown. The quotation of the pumped-storage in the electric energy market is 229.6 yuan / MW; the ratio R of the frequency regulation mileage to the frequency regulation capacity of the pumped-storage unit is 6; the frequency regulation mileage factors of the two thermal power units are 7 and 8 respectively; the quotations of each unit in the frequency regulation market are shown in Table 3. The system frequency regulation demand is 3% of the total load. The change curve of the frequency regulation mileage factor in the market frequency regulation demand is as Figure 4 shown.

[0090] Table 1 Operating parameters of pumped-storage units

[0091]

[0092] Table 2 Quotation parameters of thermal power units

[0093]

[0094] Table 3 Quotations of each unit in the frequency regulation market

[0095]

[0096] Using the Monte Carlo method, 200 wind power output scenarios are generated, and 5 typical scenarios are obtained by combining the K-means clustering method, as Figure 5 shown, and the probability distribution of each scenario is as Figure 6 shown. The scheduling period is set to 24 hours, with a total of 96 trading periods, and the trading time interval is 15 minutes. The quotation range of the thermal power unit is 189 - 450 yuan / MWh; the maximum number of starts and stops of the pumped-storage per day is 6 times, and the daily pumping and generating balance is satisfied. The confidence level β of CVaR is 0.95, the risk preference coefficient μ is 1, and the penalty coefficient λRE is set to 10.

[0097] (1) Analysis of the clearing results of the day-ahead spot market electric energy

[0098] The output plan of the pumped-storage power station participating in the day-ahead electricity energy market and the clearing results of the electricity energy price are as Figure 7 shown: From Figure 7 it can be seen that during the low-load period from 23:00 to 9:00, the pumped-storage power station stores wind power at night; after 9:00, the pumped-storage power station generates electricity during the peak electricity consumption period to make up for the load deficit, achieving peak shaving and valley filling of the load power and promoting the efficient utilization of pumped-storage resources. The clearing price is jointly determined by the load level, wind power output, pumped-storage power output, and the operating status of thermal power units participating in the bidding. The clearing prices at 96 time points correspond to the peak and valley periods of the load. The highest price is 268.31 yuan / MWh, and the lowest price is 190 yuan / MWh. From the perspective of the revenue of the pumped-storage power station participating in the spot market clearing, the pumping cost is 87,311 yuan, the power generation revenue is 115,510 yuan, and the profit of the all-day electricity energy market is 28,201 yuan. The total system cost is 2,028,341 yuan.

[0099] The bar chart of the electricity energy power balance of all units at each moment when the risk preference factor μ = 1 is as Figure 8 shown, including the power clearing plans of the pumped-storage power station, each thermal power unit, and wind power. It can be seen from the figure that the output of clean energy dominates. Under the incentive of the electricity price, the pumped-storage power station pumps water during the low-load period and generates electricity during the peak period, realizing peak-valley arbitrage. In addition, through the regulation of the spot market, the pumped-storage power station has minimized the load power fluctuation after the access of wind power within the range of meeting the reservoir capacity and operation constraints, effectively exerting the regulation potential; at the same time, the two thermal power units also participated in the market peak shaving. From the perspective of the electricity sales volume, the electricity sales of the pumped-storage power station in the electricity energy market are relatively small, and the load demand is mainly met by wind power and conventional units. Figure 9 and Figure 10 are respectively the clearing results of the frequency modulation capacity and frequency modulation mileage of each market participant in the ancillary service market. Figure 11 is the clearing result of the frequency modulation capacity price and frequency modulation mileage price in the ancillary service market.

[0100] From Figure 9 and Figure 10 it can be seen that both the pumped-storage units and each thermal power unit participated in the frequency modulation of the ancillary service market. Compared with thermal power units, the pumped-storage power station undertakes a larger proportion of the frequency modulation tasks and plays a leading role in the frequency modulation market. During the two peak stages of the load frequency modulation demand curve, the pumped-storage power station provides strong frequency modulation capacity support. Compared with conventional units, the pumped-storage power station can quickly track the load changes and is a high-quality resource in the frequency modulation market. After calculation, the frequency modulation capacity and frequency modulation mileage provided by the pumped-storage power station account for 61.455% and 60.401% of the total market demand respectively, and the remaining small amount of frequency modulation demand is met by the frequency modulation of thermal power units.

[0101] From Figure 11It can be seen that the clearing curves of the frequency modulation capacity price and the mileage price are basically similar. Combining Figure 9 and Figure 10 in the clearing results of the frequency modulation market, since the marginal cost of frequency modulation of thermal power units is relatively high, when thermal power units participate in frequency modulation, the clearing price of the frequency modulation market is relatively high. When a large number of pumped-storage units participate in frequency modulation, the clearing price of the auxiliary service capacity will decrease. In addition, a large number of pumped-storage units participating in frequency modulation will reduce the participation degree of thermal power units, thereby reducing the market frequency modulation cost.

[0102] Table 4 is a comparison table of the revenues of pumped-storage units participating in a single energy market and a combined market. It can be seen from Table 4 that the revenue of pumped-storage units when only participating in the energy market is 29,916 yuan, and the energy revenue when participating in both the energy market and the frequency modulation market decreases to 28,201 yuan, because the frequency modulation market occupies a part of the pumped-storage capacity. In addition, the revenue of pumped-storage units in the frequency modulation market accounts for 65.482% of the total revenue, which is much greater than their revenue in the energy market. This shows that the operating revenue of pumped-storage energy mainly comes from auxiliary service revenue. Participating in both the energy market and the frequency modulation market can promote the cost recovery of pumped-storage units and achieve the profitability of pumped-storage units. In terms of market participation, the participation degree of pumped-storage units in the frequency modulation market also far exceeds that in the energy market. In terms of the total system operating cost, when pumped-storage units do not participate in the frequency modulation market, the frequency modulation of the system is entirely borne by thermal power units, and the total operating cost is 2,058,548 yuan. After pumped-storage units participate in the frequency modulation market, the system frequency modulation cost decreases, and the total system operating cost decreases to 2,028,341 yuan, which has a promoting and motivating effect on the marketization process of pumped-storage energy.

[0103] Table 4 Revenues of Pumped-Storage Units Participating in a Single Energy Market and a Combined Market

[0104]

[0105] (2) Influence of the risk preference factor on the day-ahead spot market transaction

[0106] The risk preference factor represents the degree of attention of decision-makers to the uncertainty risk of wind power output. To compare the influence of different risk coefficients on the day-ahead market clearing and the operating benefits of pumped-storage units, Figure 12 、 Figure 13 present the change curves of the CVaR cost, the operating revenue of pumped-storage units, and the system operating cost when the preference factor μ rises from 0.5 to 10.

[0107] Figure 12In the data, under different preference factors, there is a positive proportional relationship between risk cost and pumped storage power station operating income. As the risk factor increases, the decision makers pay more attention to the risk, which will encourage decision makers to adopt a more conservative dispatching strategy, reduce system uncertainty, and reduce risk costs. Since the main source of risk is wind power output, the dispatched wind power output participating in the day-ahead market will decrease with the increase of risk factors, and then the system's regulation demand for wind power after grid access will weaken, and the income of pumped storage power stations as a regulating power source will also be relatively reduced.

[0108] Figure 13 In the process, as the preference factor increases, the spot market trading center pays more attention to the impact of risk on the execution of its trading plan, and the risk cost gradually decreases, while the system operation cost increases. The reason is that as the risk factor increases, the uncertainty of wind power output decreases, the actual wind power output decreases, and the system needs to increase the thermal power units to fill the gap in wind power output, so the system operation cost increases. In addition, when the risk factor increases to a certain extent, the change in system operation cost also tends to be stable.

[0109] In order to further illustrate the relationship between pumping regulation intensity and risk preference factors, Figure 14 The situation of pumped storage participating in electricity energy market regulation under different preference factors is given.

[0110] from Figure 14 It can be seen that as the risk preference coefficient increases, the deterministic output of wind power that can be dispatched gradually decreases, the impact of system uncertainty risk decreases, the volatility caused by wind power to the system decreases, the demand for pumped storage regulation resources required by the system also decreases, and the power generation / pumping output of pumped storage tends to be conservative. In order to balance the safety, stability and operational economy brought to the market by the randomness of wind power output, decision makers need to choose an appropriate risk preference coefficient.

[0111] See also Figure 15 , which shows a structural block diagram of a market-oriented multi-variety collaborative trading system for a pumped-storage power station of the present application.

[0112] like Figure 15 As shown, the market-oriented multi-variety collaborative trading system 200 for pumped-storage power stations includes a determination module 210, a first construction module 220, a second construction module 230 and a solution module 240.

[0113] Among them, a determination module 210 is configured to determine the conditional value at risk brought by the uncertainty of wind power output to market transactions; a first construction module 220 is configured to construct a lower-layer spot market clearing model with the minimum system operation cost as the first objective function under the first preset constraint condition according to the conditional value at risk; a second construction module 230 constructs an upper-layer pumped-storage power operator optimization model with the maximum operation revenue as the second objective function under the second preset constraint condition; a solution module 240 is configured to construct the KKT conditions of the lower-layer spot market clearing model, convert the lower-layer spot market clearing model into the constraint conditions of the upper-layer pumped-storage power operator optimization model, and output the game equilibrium solution after solving with Yalmip / Cplex.

[0114] It should be understood that Figure 15 The various modules described in Figure 1 correspond to the respective steps in the method described in Figure 15 Therefore, the operations, features, and corresponding technical effects described above for the method also apply to

[0115] the various modules in

[0116] In some other embodiments, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program instructions are executed by a processor, the processor is caused to execute the pumped-storage power station market-oriented multi-variety collaborative trading method in any of the above method embodiments;

[0117] As an implementation manner, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are set as:

[0118] Determine the conditional value at risk brought by the uncertainty of wind power output to market transactions;

[0119] Construct a lower-layer spot market clearing model with the minimum system operation cost as the first objective function under the first preset constraint condition according to the conditional value at risk;

[0120] Construct the KKT conditions of the lower-layer spot market clearing model, convert the lower-layer spot market clearing model into the constraint conditions of the upper-layer pumped-storage power operator optimization model, and output the game equilibrium solution after solving with Yalmip / Cplex.

[0121] A computer-readable storage medium may include a program storage area and a data storage area. Among them, the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created according to the use of the market-oriented multi-variety collaborative trading method system of a pumped-storage power station, etc. In addition, the computer-readable storage medium may include high-speed random access memory, and may also include memories, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the computer-readable storage medium may optionally include a memory remotely provided with respect to the processor, and these remote memories may be connected to the market-oriented multi-variety collaborative trading method system of the pumped-storage power station through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0122] Figure 16 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention, as Figure 16 shown, the device includes: a processor 310 and a memory 320. The electronic device may further include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330, and the output device 340 may be connected through a bus or other means, Figure 16 taking the connection through the bus as an example. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running non-volatile software programs, instructions, and modules stored in the memory 320, that is, implements the market-oriented multi-variety collaborative trading method of the pumped-storage power station in the above method embodiment. The input device 330 may receive input digital or character information, and generate key signal inputs related to user settings and function controls of the market-oriented multi-variety collaborative trading method system of the pumped-storage power station. The output device 340 may include a display device such as a display screen.

[0123] The above electronic device may execute the method provided by the embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.

[0124] As an implementation manner, the above electronic device is applied to the market-oriented multi-variety collaborative trading method system of a pumped-storage power station, and is used for a client, 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 so that the at least one processor can:

[0125] Determine the conditional value at risk brought by the uncertainty of wind power output to market trading;

[0126] Construct a lower-layer spot market clearing model with the minimum system operation cost as the first objective function according to the conditional value at risk under the first preset constraint condition;

[0127] Construct an upper-layer pumped-storage power operator optimization model with the maximum operation revenue as the second objective function under the second preset constraint condition;

[0128] Construct the KKT conditions of the lower-layer spot market clearing model, convert the lower-layer spot market clearing model into the constraint conditions of the upper-layer pumped-storage power operator optimization model, and output the game equilibrium solution after solving with Yalmip / Cplex.

[0129] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiments.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for market-oriented multi-variety collaborative trading of pumped storage power stations, characterized in that: include: Determine the conditional risk value that wind power output uncertainty brings to market transactions; According to the conditional risk value, a lower-level spot market clearing model is constructed under the first preset constraint condition with the minimum system operation cost as the first objective function; Under the second preset constraint condition, an upper-level pumped storage operator optimization model is constructed with the maximization of operating income as the second objective function; The KKT conditions of the lower-layer spot market clearing model are constructed, the lower-layer spot market clearing model is converted into the constraint conditions of the upper-layer pumped storage operator optimization model, and the game equilibrium solution is output after solving it using Yalmip / Cplex.

2. A method for market-oriented multi-variety collaborative trading of pumped storage power stations according to claim 1, characterized in that: The expression for calculating the conditional risk value brought by wind power output uncertainty to market transactions is: In the formula, C CVaR is the conditional risk value of wind power output uncertainty, β is the confidence level, α is the risk value under the β confidence level, N represents the number of wind power output scenarios, π i is the probability of scene i, is the risk loss in the ith scenario, C loss is the risk loss, λ RE is the penalty coefficient for wind power output deviation.

3. A method for market-oriented multi-variety collaborative trading of pumped storage power stations according to claim 1, characterized in that: The expression of the first objective function is: min f2=C bs +C pump +μC CVaR , Where min f2 is the minimum objective function of the lower-level spot market, C bs The quoted cost of the thermal power unit, C pump is the pumping / power generation cost of the pumped storage unit, C CVaR is the conditional risk value of wind power output uncertainty, and μ is the risk preference factor.

4. A method for market-oriented multi-variety collaborative trading of pumped storage power stations according to claim 1, characterized in that: The first preset constraint conditions include power balance constraint, frequency regulation capacity / mileage balance constraint, thermal power frequency regulation capacity / mileage operation constraint, thermal power unit output upper and lower limit constraint, line transmission power safety verification, CVaR risk value constraint, and pumped storage power / frequency regulation capacity upper and lower limit constraint; The power balance constraint is: In the formula, is the market demand load at time t; P t WT，f is the wind power output at time t; Represents the output of fixed units at time t. Units that do not participate in market regulation are called fixed units, and others are bidding units; is the dual of the equation, is the pumped storage power at time t, is the power generation capacity of thermal power unit i at time t, is the pumped storage power at time t; The frequency regulation capacity / mileage balance constraint is: In the formula, is the frequency regulation capacity reported by thermal power unit i in the ancillary service market at time t, is the frequency regulation capacity declared by pumped storage in period t, is the frequency regulation mileage declared by thermal power unit i in the auxiliary service market at time t, R is the ratio of frequency regulation mileage to frequency regulation capacity, is the frequency regulation capacity of the spot market at time t, is the frequency modulation mileage demand at time t, is the frequency regulation capacity clearing price in the spot market at time t, is the frequency modulation mileage clearing price at time t; The thermal power frequency regulation capacity / mileage operation constraints are: In the formula, is the maximum frequency regulation capacity of thermal power unit i at time t is the frequency regulation mileage reported by thermal power unit i in the ancillary service market at time t, is the ratio of the frequency regulation mileage and frequency regulation capacity of thermal power unit i at time t, are the dual variables of the corresponding constraints respectively; The upper and lower limits of the thermal power unit output are: In the formula, are the maximum and minimum power generation of generator set i, respectively. is the power generation of generator set i, δ i is the climbing rate percentage of generator set i, is the power generated by generator set i at time t, is the power generated by generator set i at time t-1, are the dual variables of the corresponding constraints respectively; The line transmission power safety check is: In the formula, is the power transmission limit of line l, g l，k is the transmission power distribution factor of node k to line l, q k，t is the total output of the unit on node k at time t, D k，t is the load of node k at time t, are the dual variables of the corresponding constraints, N is the total number of network nodes; The CVaR risk value constraint is: In the formula, Z i is an auxiliary variable introduced, representing the difference between the loss function and the risk value under scenario i, λ RE is the wind power output deviation penalty coefficient, is the actual wind power output at time t, is the predicted wind power output at time t, α is the risk value (VaR value) at the β confidence level, are the dual variables of the corresponding constraints respectively; The upper and lower limits of the pumped storage energy / frequency regulation capacity are: In the formula, is the minimum power generation capacity of pumped storage, is the pumped storage power at time t, is the pumped storage power at time t, is the maximum power generation capacity of pumped storage, is the maximum frequency regulation capacity of pumped storage at time t, is the pumped storage frequency regulation capacity at time t, are the dual variables of the corresponding constraints.

5. A method for market-oriented multi-variety collaborative trading of pumped storage power stations according to claim 1, characterized in that: The expression of the second objective function is: Where max f1 is the maximum value of the upper pumped storage operator’s objective function, is the electricity market clearing price at time t, is the pumped storage power at time t, is the pumped storage power at time t, is the frequency regulation capacity clearing price in the spot market at time t, is the frequency regulation capacity declared by pumped storage in period t, is the clearing price of frequency modulation mileage in the spot market at time t, and R is the ratio of frequency modulation mileage to frequency modulation capacity.

6. A method for market-oriented multi-variety collaborative trading of pumped storage power stations according to claim 1, characterized in that: The second preset constraint conditions include upper and lower limit constraints of unit output, operating state constraints of pumped storage units, daily start and stop times constraints of pumped storage units, and storage capacity constraints; The upper and lower limits of the unit output are: In the formula, Both are Boolean variables, representing the pumping operation state and power generation operation state of the pumped storage unit at time t respectively; The operating state constraints of the pumped storage unit are: In the formula, Represents that the pumped storage is in the power generation mode and pumping mode at time t, both are Boolean variables. is the shutdown state of the pumped storage unit under pumping conditions at time t, the Boolean variable The pumped storage is in the shutdown state under power generation condition at time t; The daily start and stop times of the pumped storage unit are constrained as follows: Where W pump The maximum number of starts and stops allowed per day for the pumped storage unit; The storage capacity constraint is: In the formula, is the energy capacity of the upper storage capacity equivalent at time t (MWh), and Represent the maximum and minimum equivalent energy capacity of the upper storage capacity (MWh), η is the comprehensive operating efficiency of the pumped storage unit, V init and are the equivalent energy capacity of the storage capacity at the initial moment and at time T (MWh), It is the energy capacity (MWh) equivalent to the upper storage capacity at time t-1.

7. A method for market-oriented multi-variety collaborative trading of pumped storage power stations according to claim 1, characterized in that: The output of the game equilibrium solution after solving by Yalmip / Cplex includes: Input the initial bids and quantities quoted by each market participant, pumped storage operation parameters, and load demand; Constructing a game participant strategy set, wherein the game participant strategy set includes a leader strategy set and a follower strategy set; Generate typical wind power scenarios using scenario analysis method, randomly generate a large amount of sample data using Monte Carlo method, reduce typical wind power scenarios through K-means clustering, and calculate the probability values ​​of different scenarios; The lower-level spot market clearing model is converted into the constraints of the upper-level pumped storage operator optimization model using KKT conditions, and the objective function of the upper-level pumped storage operator optimization model is linearized; Use Yalmip / Cplex to solve the transformed single-layer linear optimization model; The game equilibrium solution is output, including the optimal clearing electricity price in each market and the optimal winning electricity volume of each market participant, and the game process ends.

8. A market-oriented multi-variety collaborative trading system for pumped storage power stations, characterized in that: include: A determination module configured to determine the conditional risk value brought by wind power output uncertainty to market transactions; A first construction module is configured to construct a lower-level spot market clearing model based on the conditional risk value under a first preset constraint condition and taking the minimum system operation cost as a first objective function; The second building module builds an upper-level pumped storage operator optimization model with maximizing operating revenue as a second objective function under a second preset constraint condition; A solving module is configured to construct the KKT conditions of the lower-layer spot market clearing model, convert the lower-layer spot market clearing model into the constraint conditions of the upper-layer pumped storage operator optimization model, and output the game equilibrium solution after solving by Yalmip / Cplex.

9. An electronic device, characterized in that: include: 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 enable the at least one processor to execute the method described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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