Pumped storage power station optimization method considering cost allocation and state transition constraints

Abstract

The application discloses a pumped storage power station optimization method considering cost allocation and state conversion constraints, and belongs to the technical field of pumped storage power stations.The method comprises the following steps: firstly, establishing PSS unit allocation operation rules;secondly, designing a PSS unit control strategy;thirdly, establishing a PSS unit operation model;and fourthly, establishing an evaluation index of the PSS unit control strategy, and designing four different control strategies in light of the optimization method.Combining the evaluation index and the established unit operation model, the size of each evaluation index under different strategies is obtained, and it is proved that the method is scientific and effective, and has strong applicability.The method can further improve the utilization degree and economic benefits of the pumped storage power station on the basis of the current pumped storage power station situation, and provides a theoretical reference for the development of the pumped storage power station.

Description

Technical Field

[0001] This invention belongs to the technical field of pumped storage power stations, and in particular relates to an optimized control strategy for pumped storage power stations that takes into account cost allocation and state transition constraints. Background Technology

[0002] As the proportion of new energy sources integrated into the power grid continues to increase, the strong fluctuations and randomness of new energy output pose certain challenges to the operation of the power grid. Energy storage has the advantages of high flexibility and bidirectional adjustment, and the application of energy storage technology can effectively solve this problem. Pumped storage power stations, as the main means of energy storage, suffer from low utilization and poor economic benefits. On the one hand, the day-ahead dispatch of pumped storage power stations is usually arranged based on past dispatch experience, which often results in less or no power generation in actual use. Social participation is low, and this valuable resource is not being used rationally. On the other hand, the lack of an appropriate electricity price mechanism in my country currently leads to low utilization of pumped storage power stations. Summary of the Invention

[0003] The technical problem to be solved by this invention is to provide an optimization method for pumped storage power stations that takes into account cost allocation and state transition constraints. The method is scientific, effective, and highly applicable. Based on the current situation of pumped storage power stations, it further improves the utilization rate and economic benefits of pumped storage power stations and provides a theoretical reference for the development of pumped storage power stations.

[0004] An optimization method for pumped storage power plants that takes into account cost allocation and state transition constraints includes the following steps, which are performed sequentially.

[0005] Step 1: Establish operating rules for pumped storage power stations, and obtain cost allocation coefficients by combining the revenue of pumped storage power stations, dispatch costs, and the lease fees paid by wind power companies to pumped storage power stations.

[0006] Step 2: Based on the pumped storage power station operation sharing rules in Step 1, with the goal of increasing the economic benefits of the pumped storage power station, consider actively participating in wind power forecasting and mitigating the error between actual and actual wind power, design a two-layer regulation mechanism for the pumped storage power station, and establish an optimized control strategy to improve the utilization of the pumped storage power station's PSS units.

[0007] Step 3: Based on the control strategy established in Step 2, establish a PSS unit operation model, including a PSS unit operation revenue model, a PSS unit operation cost model, and constraints of the PSS unit operation model.

[0008] Step 4: Establish evaluation indicators for the PSS unit control strategy, including the smoothness of thermal power output, the degree of improvement in wind power output deviation, and the utilization rate of PSS units. By adjusting the indicators, the operation mode of each unit of the pumped storage power station can be optimized.

[0009] The revenue of the pumped storage power station mentioned in step one includes revenue from electricity generation and revenue from capacity generation.

[0010] The electricity revenue is:

[0011]

[0012] In the formula, G power For PSS electricity revenue, Let t be the downward peak modulation power of PSS. Let T be the power at time t that the PSS reduces the wind power prediction error. gen Let c be the set of time periods during which PSS is in power generation mode. price，t The time-of-use contract price for the power grid is denoted as α, where α is the peak-shaving power coefficient, representing the energy that can be stored or released in actual operating conditions for every 1MW of peak-shaving power extracted by the Power Supply Service (PSS), expressed in MW·h / MW. The mileage price is the power sampling time interval ΔT, which is the power sampling time interval provided by PSS to wind power companies for upward error mitigation assistance services.

[0013] The capacity benefit is:

[0014] G cap =c app,m ·E app (2)

[0015] In the formula, G cap For PSS capacity electricity revenue, c app,m For the approved capacity electricity price in month m, E app The portion of the PSS unit capacity covered by the approved capacity tariff.

[0016] The dispatch cost of the pumped storage power station in step one includes the fixed capacity cost and the pumping power procurement cost of the PSS unit after absorbing the curtailed wind power.

[0017] The cost of the fixed capacity is:

[0018]

[0019] In the formula, F fix For the fixed cost of PSS unit capacity, F build For investment and construction costs, P pss,t Let F be the total power of the PSS unit at time t. remain For operation and maintenance costs, c cap E represents the unit capacity cost factor for PSS units. N Let y be the rated capacity of the PSS unit, κ be the present value, β be the annual maintenance cost rate, and T be the annual maintenance cost rate.pss For the expected operating cycle of the PSS unit, T y For the annual sampling period set, c w This is the depreciation cost factor incurred during the operation of the PSS unit.

[0020] The procurement cost of the pumping power is:

[0021]

[0022] In the formula, F power The cost of purchasing electricity for the PSS unit's pumping power. Let t be the upward valley filling power of the PSS unit. Let T be the power output of the PSS unit at time t that smooths out wind power prediction errors. pump This represents the set of time periods during which the PSS turbine is in pumping operation, and ε represents the proportion of electricity purchased from wind power companies but not used. c represents the pumping power price that the PSS turbine purchases from the wind power company. price，t ΔT represents the time-of-use contract feed-in tariff for the power grid, where ΔT is the power sampling time interval.

[0023] Subtracting the revenue generated by the PSS turbine from the purchased pumping power from the cost of electricity generated by the wind turbine, the PSS turbine rental fee payable by the wind power company is obtained as follows:

[0024]

[0025] In the formula The PSS leasing fee borne by the wind power company, ω is the fixed cost allocation coefficient of the wind power company's PSS capacity;

[0026] The lease fee for pumped storage power stations is shared by the power grid company and the wind power company. The sharing method is based on the weighting coefficient δ for the paid ancillary services provided by the PSS (Power Supply Service). The weighting coefficient δ is as follows:

[0027]

[0028] The first-level regulation method of the two-layer regulation mechanism of the pumped storage power station in step two is as follows:

[0029] ① Calculate the peak-shaving capacity for both operations.

[0030] Using the aforementioned allocation weighting coefficient δ, the peak-shaving capacity of pumped storage power stations used for the first-level scheduling and the capacity used for smoothing wind power fluctuations in the second-level scheduling are calculated.

[0031]

[0032] In the formula, E peak For the peak shaving capacity of the PSS unit, E staTo mitigate wind power forecasting error capacity of PSS units, E N This refers to the rated capacity of the PSS unit;

[0033] ② Design of control strategy for pumped storage power stations under scenarios of large fluctuations in equivalent load

[0034] For large fluctuations in the equivalent load, pumped storage power stations handle peak-valley differences exceeding the grid's peak-shaving capacity during periods of peak-shaving and valley-filling, and assist thermal power plants in ramping up by providing ramping capacity. Their output relationship is as follows:

[0035]

[0036]

[0037] In the formula, P eq_low and P eq_high To determine the lower and upper limits of PSS unit operation based on the load peak-valley difference, n G r is the total number of thermal power units dn,i For thermal power unit i, the lower limit of its ramp rate is r. up,i The maximum ramp rate for thermal power unit i;

[0038] ③ Design of control strategies for pumped storage power stations under scenarios with small fluctuations in equivalent load.

[0039] For small fluctuations in the equivalent load, under the premise that the pumped storage power station meets its unit operating constraints, the load curve of each unit is smoothed by pumping and power generation in an orderly manner, so that the thermal power can maintain a relatively stable unit state to meet the load demand. The expression is:

[0040]

[0041] The second-level regulation method of the pumped storage power station's dual-level regulation mechanism in step two is as follows:

[0042] ① Design the second scheduling rule 1,

[0043] The capacity used by the PSS unit for peak shaving exceeds the peak shaving capacity limit of the PSS unit. The peak shaving capacity of the pumped storage power station is insufficient. In order to meet the load demand and assist the peak shaving of thermal power, some time periods need to be abandoned to smooth out the upward or downward fluctuation of actual wind power. The capacity of the PSS unit to smooth wind power fluctuations is put into the system peak shaving to relieve the pressure on the thermal power unit.

[0044] ② Design the second scheduling rule 2,

[0045] The peak-shaving capacity of the pumped storage power station is not exceeded, and the peak-shaving capacity of the pumped storage power station is sufficient. With the aim of adjusting the error between the actual output and the predicted output of wind power, all the capacity of the pumped storage power station for smoothing wind power fluctuations and the remaining peak-shaving capacity are put into absorbing wind curtailment and smoothing downward power fluctuations, so as to ensure the acceptance rate of the wind power dispatch plan and reduce the number of deep peak-shaving operations of thermal power. At this time, the power of the PSS unit in smoothing wind power fluctuations is as follows:

[0046]

[0047] In the formula, V wind This refers to wind power forecasting errors;

[0048] ③ Design the second scheduling rule 3,

[0049] According to the PSS unit operation safety regulations, to ensure the long-term scheduling plan utilization rate of the PSS unit, the PSS unit must maintain sufficient capacity at all times to cope with the scheduling plan for the next period. The capacity status of the PSS unit must be monitored in real time, and the water level of the PSS unit must be controlled at the highest storage level and the lowest dead water level of the reservoir, which are set as the upper and lower limits of the SOP. The expression is:

[0050]

[0051] In the formula, SOP min and SOP max These are the lower and upper limits of the Standard Operating Procedure (SOP), respectively.

[0052] The revenue model for PSS unit operation in step three includes the electricity revenue generated by the PSS unit through peak-valley electricity price arbitrage, and the rental revenue obtained by the unit from providing ancillary services.

[0053] The electricity revenue generated by the PSS unit through peak-valley electricity price arbitrage is:

[0054]

[0055] In the formula, n is the total number of PSS units. Let 's' be the hydroelectric conversion efficiency of unit 's', representing the efficiency of pumping 1 m³ of water from the PSS reservoir. 3 Water can be stored or released during operation. Energy in MW·h, the unit is MW·h / m 3 , λ s Let λ be the water consumption coefficient of unit s, representing the actual water consumption λ in the reservoir for every 1MW of water pumped by unit s. s m 3 Water volume, in m³ 3 / MW, This represents the downward peak-shaving power of unit s at time t. This represents the upward peak-shaving power of unit s at time t;

[0056] The rental income obtained by the unit from providing ancillary services is:

[0057]

[0058] In the formula, This represents the upward-smoothing wind power prediction error power of unit s at time t. This represents the downward smoothing of wind power prediction error power for unit s at time t.

[0059] The third step, the PSS unit operating cost model, includes the unit start-up and shutdown cost F. change,t Unit energy loss cost F loss,t Unit life loss cost F life,t ,

[0060] ①Establishment of PSS unit start-up and shutdown costs

[0061] The start-up and shutdown costs of PSS units can be expressed as follows:

[0062]

[0063] In the formula, c on,s Let c be the start-up cost coefficient for unit s. off,s Let be the shutdown cost coefficient for unit s. and These are Boolean variables, representing whether unit s is in power generation mode and pumping mode at time t, respectively. 1 represents yes and 0 represents no.

[0064] ②Establishment of energy loss cost of PSS unit,

[0065] During pumping and power generation, the PSS inevitably results in energy loss due to unit efficiency. The cost of this lost electricity can be calculated using the grid connection price, as shown in the following formula:

[0066]

[0067] In the formula, η is the pump-turbine efficiency of the PSS unit;

[0068] ③Establishment of PSS unit life loss cost,

[0069] Each transition between operating conditions and continuous operation of the PSS unit results in a loss of unit lifespan, which can be expressed as the following formula:

[0070]

[0071] In the formula, P pss,t,s This represents the actual total power of the unit at time t.

[0072] The constraints of the PSS unit operation model in step three include PSS unit output constraints, PSS unit single state constraints, PSS unit state transition constraints, PSS unit start-stop frequency constraints, and PSS unit capacity constraints.

[0073] The output constraint of the PSS unit is:

[0074]

[0075] In the formula, and This represents the minimum and maximum power of the unit at time t;

[0076] The single-state constraint of the PSS unit is:

[0077] Six Boolean variables are introduced to describe the transition process of the unit between power generation, pumping, and static states, with 1 representing yes and 0 representing no, as shown in the following formula:

[0078]

[0079] In the formula, This is a Boolean variable used to determine whether unit s is in a static state, with 1 representing yes and 0 representing no. and These are the state variables for whether unit s transitions from power generation to quiescent and to pumping, respectively. and These are the state variables for whether unit s transitions from pumping to quiescent and from generating power, respectively. and These are the state variables for whether unit s changes from a stationary state to a power generation state and a power pumping state, respectively.

[0080] The PSS unit state transition constraint is:

[0081]

[0082] In the formula, τ is the current time period of the scheduling cycle, and T mg T pg T mp T gp T gm and T pm These are the minimum number of transition periods required for the unit to switch from static to power generation, from pumping to power generation, from static to pumping, from power generation to pumping, from power generation to static, and from pumping to static, respectively.

[0083] The constraint on the number of start-ups and shutdowns of the PSS unit is:

[0084]

[0085] In the formula, K sThis represents the maximum number of state transitions for unit s;

[0086] The capacity constraint of the PSS unit is:

[0087] For any time period τ∈T, the capacity constraint for PSS units is established as follows:

[0088]

[0089] In the formula, and These are the minimum and maximum values ​​of the PSS library capacity, respectively.

[0090] The smoothness of thermal power output in step four corresponds to the smoothness of the thermal power dispatch plan, reflecting the frequency of changes in the operating status of thermal power units during dispatch. The expression is:

[0091]

[0092] In the formula, P G,t The output of the thermal power plant at time t;

[0093] The degree of improvement in wind power output deviation corresponds to the improvement in wind power predicted output by the PSS unit, expressed as:

[0094]

[0095] In the formula, P wa,t The actual power output of the wind power at time t;

[0096] The utilization level of the PSS unit in step four is the overall utilization value of the PSS unit, expressed as:

[0097]

[0098] In the formula, P pss,t Let P be the total power of the PSS unit at time t. pss,N This refers to the rated power of the pumped storage unit.

[0099] Through the above design scheme, the present invention can bring the following beneficial effects: The pumped storage power station optimization method that takes into account cost allocation and state transition constraints addresses the current problems of low utilization rate and poor economic benefits of pumped storage power stations. By iteratively allocating weight coefficients to dynamically divide the capacity of PSS units, it aims to assist thermal power dispatch and improve wind power output errors, and effectively improve the utilization of PSS units. By incorporating state transition constraints into the unit model, it makes the unit start-up and shutdown plan and power allocation more reasonable, thereby reducing the unit operating cost. By increasing the rental income of PSS units, it indirectly increases their enthusiasm for pumping power, and also increases the total revenue of wind power companies. Attached Figure Description

[0100] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0101] Figure 1 This is a flowchart of the optimization method for pumped storage power plants that takes into account cost allocation and state transition constraints according to the present invention.

[0102] Figure 2 This is a comparison chart of the thermal power dispatching effect of PSS units in a specific implementation of the pumped storage power station optimization method of the present invention, which takes into account cost allocation and state transition constraints.

[0103] Figure 3 The diagram shows the secondary scheduling results of the PSS unit in a specific implementation of the pumped storage power station optimization method that takes into account cost allocation and state transition constraints of the present invention.

[0104] Figure 4 This is a comparison chart showing the improvement effect of the pumped storage power station optimization method of the present invention, which takes into account cost allocation and state transition constraints, on the predicted wind power output.

[0105] Figure 5 This is a comparison diagram of the capacity and state of pumped storage power station optimization method of the present invention, which takes into account cost allocation and state transition constraints. Detailed Implementation

[0106] The present invention will be further described in detail below with reference to specific embodiments. The following examples are used to illustrate the present invention, but it should be understood that the scope of protection of the present invention is not limited to the specific embodiments.

[0107] This invention provides an optimization method for pumped storage power plants that takes into account cost allocation and state transition constraints, such as... Figure 1 As shown, firstly, the allocation-based operation rules for the PSS unit are established; secondly, the control strategy for the PSS unit is designed, and an operation model for the PSS unit is established; then, evaluation indicators for the control strategy of the PSS unit are established; finally, different control strategies are designed, and the magnitudes of each evaluation indicator under different strategies are compared based on the proposed evaluation indicators and the established unit operation model to prove the feasibility of the control strategy. The specific steps are as follows:

[0108] Step 1: Establish the cost-sharing operation rules for PSS units.

[0109] First, establish the revenue expression for a pumped storage power station.

[0110] The first step is to establish the electricity revenue of the pumped storage power station, which is expressed as follows:

[0111]

[0112] In the formula, G power For PSS electricity revenue, Let t be the downward peak modulation power of PSS. Let T be the power at time t that the PSS reduces the wind power prediction error. gen Let c be the set of time periods during which PSS is in power generation mode. price t represents the time-of-use contract price of the power grid, and α represents the peak-shaving power coefficient, indicating that for every 1MW of peak-shaving power extracted by the PSS, αMW·h of energy can be stored or released under actual operating conditions, with units of MW·h / MW. In this paper, we take 0.22. The mileage price is the power sampling time interval ΔT, which is the power sampling time interval provided by PSS to wind power companies for upward error mitigation assistance services.

[0113] The second step is to establish the capacity revenue of the pumped storage power station, the expression of which is as follows:

[0114] G cap =c app,m ·E app (2)

[0115] In the formula, G cap For PSS capacity electricity revenue, c app,m For the approved capacity electricity price in month m, E pss,t Let E be the size of the PSS at time t. app This refers to the portion of the PSS (Power Supply Service) unit capacity covered by the approved capacity tariff.

[0116] Secondly, the dispatching cost of pumped storage power stations should be established.

[0117] The first step is to establish the fixed capacity cost of a pumped storage power station, which is expressed as follows:

[0118]

[0119] In the formula, F fix For PSS capacity fixed costs, F build For investment and construction costs, P pss,t Let F be the total power of the PSS at time t. remain For operation and maintenance costs, c cap The unit capacity cost coefficient for PSS is taken as 900,000 yuan / (MW·h), E N Let y be the rated capacity of the PSS, κ be the present value, β be the annual maintenance cost rate (taken as 0.024), and T be the annual maintenance cost rate. pss The estimated operating period of PSS is 40 years, T y For the annual sampling period set, c w This is the depreciation cost factor generated during PSS operation;

[0120] The second step is to establish the procurement cost of pumped hydro power for pumped storage power stations. When PSS (Power Storage System) absorbs curtailed wind power, wind power companies can reduce curtailment by purchasing pumped hydro power from PSS, essentially leasing out the pumped hydro power from PSS. Therefore, the cost of purchasing pumped hydro power from PSS can be expressed as:

[0121]

[0122] In the formula, F power The cost of purchasing electricity for PSS pumping. Let t be the upward valley filling power of PSS. Let T be the power at time t that the PSS reduces the wind power prediction error. pump The set of time periods during which PSS is in pumping operation, and ε is the proportion of electricity purchased from wind power companies but not used. The pumping power price that PSS purchases from wind power companies;

[0123] Then establish the lease fees that wind power companies need to pay to pumped storage power stations.

[0124] Since the pumped hydro electricity purchased by the PSS (Power Supply Service) to absorb curtailed wind power is wind power that wind power companies should have abandoned, the pumped hydro electricity price should be reduced to increase the net power generation revenue of the PSS. Subtracting the revenue gained by the PSS from generating electricity using curtailed wind power from the above formula yields the PSS lease fee that wind power companies need to pay. Therefore, the PSS lease fee that wind power companies need to pay can be expressed as:

[0125]

[0126] In the formula The PSS leasing fee borne by the wind power company, ω is the fixed cost allocation coefficient of the wind power company's PSS capacity, which is set to 0.26 in this article according to the relevant regulations of the National Development and Reform Commission;

[0127] Finally, calculate the cost allocation factor.

[0128] From now on, the lease fee for pumped storage power stations will be shared by the power grid company and the wind power company. The sharing method will be based on a weighting coefficient δ set according to the ancillary services provided by the PSS. The weighting coefficient δ can be expressed as:

[0129]

[0130] Step 2, Design of control strategy for pumped storage power station

[0131] First, design the first-level dispatching system for the pumped storage power station.

[0132] The first step is to calculate the peak-shaving capacity for both stages. Using the initial value of the cost-sharing coefficient calculated in step 1, we calculate the peak-shaving capacity of pumped storage power stations used for the first-level dispatch and the capacity used for smoothing wind power fluctuations in the second-level dispatch, which can be expressed as follows:

[0133]

[0134] In the formula, E peak For the peak-shaving capacity of PSS, E sta To mitigate wind power prediction error capacity of PSS;

[0135] The second step is to design a control strategy for pumped storage power stations under scenarios of large fluctuations in equivalent load. For large fluctuation events in equivalent load, pumped storage power stations handle the peak-valley difference during periods exceeding the grid's peak-shaving capacity limit by peak shaving and valley filling, and assist thermal power plants in ramping up by providing ramping capacity. The output of pumped storage power stations should satisfy the following relationship:

[0136]

[0137]

[0138] In the formula, P eq_low and P eq_high To determine the lower and upper limits of PSS action based on the load peak-valley difference, n G r is the total number of thermal power units dn,i For thermal power unit i, the lower limit of its ramp rate is r. up,i The maximum ramp rate for thermal power unit i;

[0139] The third step is to design a control strategy for pumped storage power stations under scenarios with small fluctuations in equivalent load. For small fluctuation events in the equivalent load, the pumped storage power station, while meeting its unit operation constraints, orderly controls each unit to smooth the load curve through pumping and power generation, so that the thermal power can maintain a relatively stable unit state to meet the load demand. Its expression is as follows:

[0140]

[0141] Secondly, the second scheduling of the pumped storage power station should be designed.

[0142] The first step is to design the second dispatch rule 1. When the peak shaving capacity limit of PSS is exceeded, the peak shaving capacity of pumped storage power station is insufficient. The main purpose is to meet the load demand and assist the peak shaving of thermal power. At this time, the wind curtailment (i.e. the actual wind power fluctuates upward) or the power fluctuation downward needs to be smoothed out for a certain period of time. The capacity of PSS to smooth wind power fluctuation is put into the system peak shaving to relieve the pressure on thermal power units.

[0143] The second step is to design the second dispatch rule 2. When the peak-shaving capacity limit of the pumped storage power station is not exceeded, the peak-shaving capacity of the pumped storage power station is sufficient. The main purpose is to adjust the error between the actual output and the predicted output of wind power. All the capacity of the pumped storage power station for smoothing wind power fluctuations and the remaining peak-shaving capacity are put into absorbing wind curtailment and smoothing downward power fluctuations, so as to ensure the acceptance rate of the wind power dispatch plan and reduce the number of deep peak-shaving times of thermal power. At this time, the power of the PSS that smooths wind power fluctuations is as follows:

[0144]

[0145] In the formula, V wind This refers to wind power forecasting errors;

[0146] The third step is to design the second scheduling rule 3. Based on the PSS operation safety regulations and to improve the utilization of the PSS in the face of long-term scheduling plans, ensuring that the PSS maintains sufficient capacity at all times to cope with the scheduling plan for the next period, it is necessary to monitor the capacity status of the PSS in real time. This strategy will control the PSS water level at the highest and lowest dead water levels of the reservoir, setting these as the upper and lower limits of the Standard Operating Procedure (SOP), as shown in the following expression:

[0147]

[0148] In the formula, SOP min and SOP max These are the lower and upper limits of the Standard Operating Procedure (SOP), respectively.

[0149] Step 3: Establish the PSS unit operation model

[0150] First, establish the operating revenue of the PSS unit.

[0151] The first step is to establish the PSS unit's electricity revenue, the expression of which is as follows:

[0152]

[0153] In the formula, n is the total number of PSS units. Let 's' be the hydroelectric conversion efficiency of unit 's', representing the efficiency of pumping 1 m³ of water from the PSS reservoir. 3 Water can be stored or released during operation. Energy in MW·h, the unit is MW·h / m 3 Take 0.19, λ s Let λ be the water consumption coefficient of unit s, representing the actual water consumption λ in the reservoir for every 1MW of water pumped by unit s. s m 3 Water volume, in m³ 3 / MW, This represents the downward peak-shaving power of unit s at time t. This represents the upward peak-shaving power of unit s at time t;

[0154] The second step is to establish PSS unit leasing revenue, the expression of which is as follows:

[0155]

[0156] In the formula, This represents the upward-smoothing wind power prediction error power of unit s at time t. This represents the downward-smoothing wind power prediction error power of unit s at time t;

[0157] Secondly, establish the operating costs of the PSS unit.

[0158] The first step is to establish the start-up and shutdown costs of the PSS unit, which is expressed as follows:

[0159]

[0160] In the formula, c on,s Let c be the start-up cost coefficient for unit s. off,s Let be the shutdown cost coefficient for unit s. and These are Boolean variables, representing whether unit s is in power generation mode and pumping mode at time t, respectively. 1 represents yes and 0 represents no.

[0161] The second step is to establish the energy loss cost of the PSS unit.

[0162] During pumping and power generation, the PSS inevitably results in energy loss due to unit efficiency. The cost of this lost electricity can be calculated using the grid connection price, as shown in the following formula:

[0163]

[0164] In the formula, η is the pump-turbine efficiency of the PSS unit;

[0165] The third step is to establish the life-cycle depreciation cost of the PSS unit.

[0166] Each transition between operating conditions and continuous operation of the PSS unit results in a loss of unit lifespan, which can be expressed as the following formula:

[0167]

[0168] In the formula, P pss,t,s This represents the actual total power of the unit at time t;

[0169] Then, the constraints for the operation of the PSS unit are established.

[0170] The first step is to establish output constraints for the PSS units.

[0171] To facilitate the calculation of the power gain of the PSS and reduce model complexity, the water flow constraint of the PSS is transformed into a power constraint, as shown in the following equation:

[0172]

[0173] In the formula, and This represents the minimum and maximum power of the unit at time t;

[0174] The second step is to establish single-state constraints for the PSS unit.

[0175] To facilitate the description of the limitations of state transitions between units, six Boolean variables will be introduced to describe the transition process between power generation, pumping, and static states, with 1 representing yes and 0 representing no, as shown in the following formula:

[0176]

[0177] In the formula, This is a Boolean variable used to determine whether unit s is in a static state, with 1 representing yes and 0 representing no. and These are the state variables for whether unit s transitions from power generation to quiescent and to pumping, respectively. and These are the state variables for whether unit s transitions from pumping to quiescent and from generating power, respectively. and These are the state variables for whether unit s changes from a stationary state to a power generation state and a power pumping state, respectively.

[0178] The third step is to establish unit state transition constraints.

[0179] To more accurately reflect the actual operating conditions and controllable adjustment capabilities of the PSS units, state transition constraints are added to the PSS unit operation model, making the PSS unit scheduling plan more reasonable. The constraint expressions are as follows:

[0180]

[0181] In the formula, τ is the current time period of the scheduling cycle, and T mg T pg T mp T gp T gm and T pm These are the minimum number of transition periods required for the unit to switch from static to power generation, from pumping to power generation, from static to pumping, from power generation to pumping, from power generation to static, and from pumping to static, respectively.

[0182] The fourth step is to establish constraints on the number of start-ups and shutdowns of the PSS unit.

[0183] Frequent start-ups and shutdowns of generating units can damage their mechanical components, affecting the safety and lifespan of unit operation. Therefore, it is necessary to constrain the number of start-ups and shutdowns of each unit per day, as shown in the following formula:

[0184]

[0185] In the formula, K s This represents the maximum number of state transitions for unit s;

[0186] The fifth step is to establish PSS capacity constraints.

[0187] For any time interval τ∈T, the capacity constraint of PSS is established as follows:

[0188]

[0189] In the formula, and These are the minimum and maximum values ​​of the PSS library capacity, respectively.

[0190] Step 4: Establish evaluation indicators for PSS unit control strategies.

[0191] First, establish an index for the smoothness of thermal power output.

[0192] This indicator reflects the smoothness of the thermal power dispatch plan. The smaller the indicator, the smoother the thermal power output, and the less frequently the operating status of the thermal power units needs to be changed during dispatch. It can be expressed as follows:

[0193]

[0194] In the formula, P G,t The output of the thermal power plant at time t;

[0195] Secondly, establish an index for the degree of improvement in wind power output deviation.

[0196] This indicator reflects the improvement of PSS (Power Slot System) on wind power forecast output, making it closer to the actual output, thereby increasing the acceptance rate of wind power dispatch plans. The higher the value, the better the improvement effect. It can be expressed as follows:

[0197]

[0198] In the formula, P wa,t The actual power output of the wind power at time t;

[0199] Then, establish a PSS utilization index.

[0200] This indicator reflects the overall utilization of PSS; the higher the value, the better the utilization. It can be expressed as follows:

[0201]

[0202] Specifically, the analysis method of this invention is used to perform corresponding simulation analysis on specific examples.

[0203] Based on wind power and load data from a regional power grid in Northwest China, and according to the regulation that the PSS (Power Supply Service) on-grid tariff is 75% of the benchmark price for coal-fired power generation, with a PSS on-grid tariff of 0.311 yuan / (kWh), the peak-shaving effect and wind power output improvement of PSS participation in day-ahead dispatch are compared under the following four different control strategies:

[0204] Strategy 1: PSS adopts a strategy of timed sampling based on the intraday load peak-valley difference, does not actively participate in wind power forecast error mitigation, and the unit model takes the maximum PSS profit as the objective function but has no state transition constraints.

[0205] Strategy 2: PSS considers the large and small fluctuation events in the equivalent load, only performs the first scheduling of PSS units in step 2, does not actively participate in wind power prediction error mitigation, and the unit model is the same as in Strategy 1;

[0206] Strategy 3: The PSS adopts the operating rules and control strategies in this paper, that is, it performs the first and second scheduling of the PSS unit in step 2, and the unit model is the same as in strategy 1;

[0207] Strategy 4: The PSS adopts the operating rules and control strategies described in this paper. The unit model takes the maximization of PSS profit as the objective function and has state transition constraints, which is the strategy described in this paper.

[0208] The presence or absence of state transition constraints in the unit model does not affect the scheduling effect and utilization. Therefore, when analyzing the PSS scheduling effect and utilization, strategies 3 and 4 are identical. The comparison of the PSS-assisted thermal power scheduling effects under different strategies is as follows: Figure 2 As shown in the figure, the PSS unit's first dispatch in step 2 adopts different dispatch methods in different time periods, which alleviates the output status of thermal power units under extreme conditions. Under strategy 2, the effect of PSS-assisted thermal power dispatch is better than that of strategy 1.

[0209] The effect of the second PSS scheduling is shown below. Figure 3 As shown in the figure, it is clear that compared to Strategy 2, which does not participate in wind power error mitigation, Strategy 3's PSS has directly absorbed the original wind curtailment phenomenon. Figure 4 As can be seen from this, Strategy 3 effectively reduced some of the output deviation after improving the output deviation, making the curve closer to the actual output.

[0210] PSS usage examples Figure 5As shown in the figure, observing the comparison of SOPs under different strategies reveals that strategy 3 exhibits the largest variation in SOP curves. Furthermore, by integrating each curve with the initial SOP value of 0.5 as the baseline, strategy 3 shows the largest area under the curve, indicating that strategy 3 achieves the highest utilization of PSS capacity and demonstrates the best overall utilization.

[0211] The unit model proposed in this invention can make the unit start-up and shutdown plan and power allocation more reasonable. Moreover, under the proposed control strategy, the economic benefits of different strategies are calculated and compared, showing that both the model and wind power companies have good economic benefits.

[0212] The embodiments of the present invention are not exhaustive and do not constitute a limitation on the scope of protection of the claims. Those skilled in the art, upon learning from the embodiments of the present invention, can conceive of other substantially equivalent alternatives without inventive effort, all of which are within the scope of protection of the present invention.

Claims

1. An optimization method for pumped storage power plants that takes into account cost allocation and state transition constraints, characterized by: The steps are as follows, and the steps are performed in sequence. Step 1: Establish operating rules for pumped storage power stations, and obtain cost allocation coefficients by combining the revenue of pumped storage power stations, dispatch costs, and the lease fees paid by wind power companies to pumped storage power stations. Step 2: Based on the pumped storage power station operation sharing rules in Step 1, with the goal of increasing the economic benefits of the pumped storage power station, consider actively participating in wind power forecasting and mitigating the error between actual and actual wind power, design a two-layer regulation mechanism for the pumped storage power station, and establish an optimized control strategy to improve the utilization of the pumped storage power station's PSS units. The first-level regulation method of the two-level regulation mechanism of the pumped storage power station is as follows: ① Calculate the peak-shaving capacity for both operations. Using the apportionment weighting coefficient δ Calculate the peak-shaving capacity of pumped storage power stations used for the first-level dispatch and the capacity used for smoothing wind power fluctuations in the second-level dispatch. (7) In the formula, E peak For the peak shaving capacity of PSS units, E sta To mitigate wind power forecasting error capacity of PSS units, E N This refers to the rated capacity of the PSS unit; ② Design of control strategy for pumped storage power stations under scenarios of large fluctuations in equivalent load For large fluctuations in the equivalent load, pumped storage power stations handle peak-valley differences exceeding the grid's peak-shaving capacity during periods of peak-shaving and valley-filling, and assist thermal power plants in ramping up by providing ramping capacity. Their output relationship is as follows: (8) (9) In the formula, and The lower and upper limits of PSS unit operation are determined based on the peak-valley load difference. n G This represents the total number of thermal power units. r dn,i For thermal power units i Lower limit of climbing speed r up,i For thermal power units i Climbing speed limit; ③ Design of control strategies for pumped storage power stations under scenarios with small fluctuations in equivalent load. For small fluctuations in the equivalent load, under the premise that the pumped storage power station meets its unit operating constraints, the load curve of each unit is smoothed by pumping and power generation in an orderly manner, so that the thermal power can maintain a relatively stable unit state to meet the load demand. The expression is: (10) The second-level regulation method of the dual-level regulation mechanism of the pumped storage power station is as follows: ① Design the second scheduling rule 1, The capacity used by the PSS unit for peak shaving exceeds the peak shaving capacity limit of the PSS unit. The peak shaving capacity of the pumped storage power station is insufficient. In order to meet the load demand and assist the peak shaving of thermal power, some time periods need to be abandoned to smooth out the upward or downward fluctuation of actual wind power. The capacity of the PSS unit to smooth wind power fluctuations is put into the system peak shaving to relieve the pressure on the thermal power unit. ② Design the second scheduling rule 2, The peak-shaving capacity of the pumped storage power station is not exceeded, and the peak-shaving capacity of the pumped storage power station is sufficient. With the aim of adjusting the error between the actual output and the predicted output of wind power, all the capacity of the pumped storage power station for smoothing wind power fluctuations and the remaining peak-shaving capacity are put into absorbing wind curtailment and smoothing downward power fluctuations, so as to ensure the acceptance rate of the wind power dispatch plan and reduce the number of deep peak-shaving operations of thermal power. At this time, the power of the PSS unit in smoothing wind power fluctuations is as follows: (11) In the formula, V wind This refers to wind power forecasting errors; ③ Design the second scheduling rule 3, In accordance with the PSS unit operation safety regulations, to ensure the long-term utilization rate of the PSS unit's scheduling plan, the PSS unit must maintain sufficient capacity at all times to cope with the scheduling plan for the next period. The capacity status of the PSS unit must be monitored in real time, and the water level of the PSS unit must be controlled at the highest and lowest dead water levels of the reservoir, and these levels must be set as follows: SOP The upper and lower limits are expressed as: (12) In the formula, SOP min and SOP max These are the lower and upper limits of the Standard Operating Procedure (SOP), respectively. Step 3: Based on the control strategy established in Step 2, establish a PSS unit operation model, including a PSS unit operation revenue model, a PSS unit operation cost model, and constraints of the PSS unit operation model. Step 4: Establish evaluation indicators for the PSS unit control strategy, including the smoothness of thermal power output, the degree of improvement in wind power output deviation, and the utilization rate of PSS units. By adjusting the indicators, the operation mode of each unit of the pumped storage power station can be optimized.

2. The optimization method for pumped storage power plants considering cost allocation and state transition constraints according to claim 1, characterized in that: The revenue of the pumped storage power station mentioned in step one includes revenue from electricity generation and revenue from capacity generation. The electricity revenue is: (1) In the formula, G power For PSS electricity revenue, Let t be the downward peak modulation power of PSS. Let T be the power at time t that the PSS reduces the wind power prediction error. gen Let c be the set of time periods during which PSS is in power generation mode. price，t The time-of-use contract price for the power grid is denoted as α, where α is the peak-shaving power coefficient, representing the energy that can be stored or released in actual operating conditions for every 1MW of peak-shaving power extracted by the Power Supply Service (PSS), expressed in MW·h / MW. The mileage price is the power sampling time interval ΔT, which is the power sampling time interval provided by PSS to wind power companies for upward error mitigation assistance services. The capacity benefit is: (2) In the formula, G cap For PSS capacity electricity revenue, c app,m The approved capacity electricity price for month m. E app The portion of the PSS unit capacity covered by the approved capacity tariff.

3. The optimization method for pumped storage power plants considering cost allocation and state transition constraints according to claim 1, characterized in that: The dispatch cost of the pumped storage power station in step one includes the fixed capacity cost and the pumping power procurement cost of the PSS unit after absorbing the curtailed wind power. The cost of the fixed capacity is: (3) In the formula, F fix Fixed costs for PSS unit capacity, F build For investment and construction costs, P pss,t Let t be the total power of the PSS unit. F remain For operation and maintenance costs, c cap This is the unit capacity cost coefficient for PSS units. E N The rated capacity of the PSS unit, y Ending amount κ For present value, β Annual maintenance cost rate T pss The expected operating cycle of the PSS unit, T y This is a set of annual sampling periods. c w This is the depreciation cost factor incurred during the operation of the PSS unit. The procurement cost of the pumping power is: (4) In the formula, F power The cost of purchasing electricity for the PSS unit's pumping power. Let t be the upward valley filling power of the PSS unit. Let be the power of the PSS unit at time t that reduces the wind power prediction error. T pump This refers to the collection of time periods during which the PSS unit is in pumping operation. ε This represents the percentage of electricity purchased from wind power companies but not used. c represents the pumping power price that the PSS turbine purchases from the wind power company. price，t ΔT represents the time-of-use contract feed-in tariff for the power grid, where ΔT is the power sampling time interval. Subtracting the revenue generated by the PSS turbine from the purchased pumping power from the cost of electricity generated by the wind turbine, the PSS turbine rental fee payable by the wind power company is obtained as follows: (5) In the formula, The PSS leasing fee borne by wind power companies ω The fixed cost allocation coefficient for PSS capacity of wind power enterprises; The lease fee for pumped storage power stations is shared by the power grid company and the wind power company, with the cost-sharing method based on the weighting coefficient of the ancillary services provided by the PSS (Power Supply Service). δ apportionment weighting coefficient δ for: (6)。 4. The optimization method for pumped storage power plants considering cost allocation and state transition constraints according to claim 1, characterized in that: The revenue model for PSS unit operation in step three includes the electricity revenue generated by the PSS unit through peak-valley electricity price arbitrage, and the rental revenue obtained by the unit from providing ancillary services. The electricity revenue generated by the PSS unit through peak-valley electricity price arbitrage is: (13) In the formula, n This represents the total number of PSS units. φ s For the unit s The hydroelectric conversion efficiency indicates the efficiency of pumping 1 m³ of water from the PSS reservoir. 3 Water can be stored or released during operation. φ s Energy in MW·h, the unit is MW·h / m 3 , λ s For the unit s The water consumption coefficient represents the unit's... s The actual consumption of 1MW of water pumped from the reservoir λ s m 3 Water volume, in m³ 3 / MW, express t Time crew s Downward peaking power, express t Time crew s The upward peaking power; The rental income obtained by the unit from providing ancillary services is: (14) In the formula, express t Time crew s Upward smoothing of wind power forecasting error power, express t Time crew s The downward smoothing of wind power prediction error power.

5. The optimization method for pumped storage power plants considering cost allocation and state transition constraints according to claim 1, characterized in that: Step three, the PSS unit operating cost model, includes unit start-up and shutdown costs. F change,t Unit energy loss cost F loss,t Unit life loss cost F life,t , ① Establishment of PSS unit start-up and shutdown costs, The start-up and shutdown costs of PSS units can be expressed as follows: (15) In the formula, c on,s For the unit s The start-up cost coefficient, c off,s For the unit s The shutdown cost coefficient, and These are Boolean variables, representing respectively t Time crew s Whether it is in power generation mode or pumping mode, 1 is yes and 0 is no; ②Establishment of energy loss cost of PSS unit, During pumping and power generation, the PSS inevitably results in energy loss due to unit efficiency. The cost of this lost electricity can be calculated using the grid connection price, as shown in the following formula: (16) In the formula, η The efficiency of the pump-turbine in the PSS unit; ③Establishment of PSS unit life loss cost, Each transition between operating conditions and continuous operation of the PSS unit results in a loss of unit lifespan, which can be expressed as the following formula: (17) In the formula, P pss,t,s express t Time crew s The actual total power.

6. The optimization method for pumped storage power plants considering cost allocation and state transition constraints according to claim 1, characterized in that: The constraints of the PSS unit operation model in step three include PSS unit output constraints, PSS unit single state constraints, PSS unit state transition constraints, PSS unit start-stop frequency constraints, and PSS unit capacity constraints. The output constraint of the PSS unit is: (18) In the formula, and express t Time crew s Minimum and maximum power; The single-state constraint of the PSS unit is: Six Boolean variables are introduced to describe the transition process of the unit between power generation, pumping, and static states, with 1 representing yes and 0 representing no, as shown in the following formula: (19) In the formula, To determine the unit s A Boolean variable indicating whether it is in a static state, with 1 for yes and 0 for no. and The units s Whether the state variable changes from power generation to quiescent and to pumping. and The units s Whether the state variables change from pumping to quiescent and to power generation and The units s Whether the state variable changes from static to power generation and then to pumping; The PSS unit state transition constraint is: (20) In the formula, τ This represents the current time period number within the scheduling cycle. T mg , T pg , T mp , T gp , T gm and T pm These are the minimum number of transition periods required for the unit to switch from static to power generation, from pumping to power generation, from static to pumping, from power generation to pumping, from power generation to static, and from pumping to static, respectively. The constraint on the number of start-ups and shutdowns of the PSS unit is: (21) In the formula, K s For the unit s Maximum number of state transitions; The capacity constraint of the PSS unit is: for τ ∈ T The capacity constraints for PSS units at any given time period are established as follows: (22) In the formula, and These are the minimum and maximum values ​​of the PSS library capacity, respectively.

7. The optimization method for pumped storage power plants considering cost allocation and state transition constraints according to claim 1, characterized in that: The smoothness of thermal power output in step four corresponds to the smoothness of the thermal power dispatch plan, reflecting the frequency of changes in the operating status of thermal power units during dispatch. The expression is: (twenty three) In the formula, P G,t For thermal power t Efforts made at all times; The degree of improvement in wind power output deviation corresponds to the improvement in wind power predicted output by the PSS unit, expressed as: (24) In the formula, P wa,t For wind power t Actual power at any given moment.

8. The optimization method for pumped storage power plants considering cost allocation and state transition constraints according to claim 1, characterized in that: The utilization level of the PSS unit in step four is the overall utilization value of the PSS unit, expressed as: (25) In the formula, P pss,t Let t be the total power of the PSS unit. P pss,N This refers to the rated power of the pumped storage unit.

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