Capacity Allocation Method, Device, Equipment and Medium Considering the Construction Period of Pumped Storage

Abstract

The present invention relates to the technical field of multi-energy complementary power generation, and in particular to a capacity configuration method, device, equipment and medium that considers the construction period of pumped storage. The method includes: considering the construction period of hybrid pumped storage and the annual growth of load, modeling the timing; establishing a multi-objective function of minimum life cycle cost and minimum residual load variance, establishing a joint scheduling operation strategy and operation constraints, considering the uncertainty of annual load growth, and establishing a system model including information gap decision theory; using linearization technology to convert the system model into a mixed integer linear programming model; solving the mixed integer linear programming model to obtain the optimal configuration and operation plan of each equipment in each year. In the present invention, it is possible to balance economy and load fluctuations, finely configure wind and solar capacity year by year, deeply adjust and transform thermal power to absorb excess wind and solar power, and the introduction of the construction period avoids problems such as redundant configuration and reduced energy supply quality in the later period.

Description

Technical Field

[0001] The present invention relates to the technical field of multi - energy complementary power generation, and particularly to a capacity configuration method, device, equipment and medium considering the construction period of pumped - storage power stations. Background Art

[0002] Under the background of "dual - carbon", wind power and photovoltaic power have gradually developed into the main energy sources for providing electric energy. However, due to the natural intermittency, randomness and volatility of wind power and photovoltaic energy, they are likely to have an impact on the safety and stability of the power grid. Therefore, in response to this problem, developing regulating energy has become a major solution, and the flexibility transformation of thermal power units and the construction of hybrid pumped - storage power stations have attracted the attention of the industry.

[0003] Most of the current research on regulating energy planning focuses on the configuration at the current moment. On the one hand, this method does not pay attention to the characteristics of gradually increasing load. On the other hand, it is prone to premature planning, resulting in higher costs. At the same time, due to the large construction period of hybrid pumped - storage power stations, if this scheme is also used for configuration, it will not conform to the actual situation.

[0004] Therefore, paying attention to load growth, conducting wind and photovoltaic capacity configuration and flexibility transformation planning of thermal power units once a year, considering the construction period, putting the hybrid pumped - storage power station into use after construction, and considering the life - cycle cost, this kind of problem tending to actual planning is the problem that needs to be solved urgently at present.

[0005] The information disclosed in this background - art section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0006] The present invention provides a capacity configuration method, device, equipment and medium considering the construction period of pumped - storage power stations, so as to effectively solve the problems in the background art.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a capacity configuration method considering the construction period of pumped - storage power stations, including the following steps:

[0008] Model the time - series considering the construction period of the hybrid pumped - storage power station and the annual growth of the load;

[0009] Establish a multi - objective function with the minimum life - cycle cost and the minimum variance of the remaining load, establish a joint dispatching operation strategy and operation constraint conditions, and considering the uncertainty of the annual growth of the load, establish a system model including the information - gap decision theory;

[0010] Use linearization technology to transform the system model into a mixed - integer linear programming model;

[0011] Solve the mixed-integer linear programming model to obtain the optimal configuration and operation plan of each device for each year.

[0012] Furthermore, considering the construction period of the hybrid pumped storage and the annual growth of the load, model the time series, including the following steps:

[0013] Divide the entire planning period into 4 years, and denote the sequence Y as:

[0014] Y = [Y 1 , Y 2 , Y 3 , Y 4 ;

[0015] In the formula: Y y is the y-th year;

[0016] The capacity sets of wind power, photovoltaic configuration, and thermal power unit renovation are respectively:

[0017]

[0018] In the formula: I w , I pv , and I th are the capacity sets of wind power, photovoltaic configuration, and thermal power unit renovation respectively; and are the capacities of wind power, photovoltaic configuration, and thermal power unit renovation in the y-th year respectively, where y = 1, 2, 3, 4;

[0019] Among them, the method for determining the capacity of thermal power unit renovation is:

[0020]

[0021] In the formula: N Y is the total number of planning years; T CPS is the construction period of the hybrid pumped storage, which is 3 years; is the minimum output of the thermal power unit after renovation; and are the decision variables of the renovation plan for the g-th thermal power unit in the y-th year respectively; and are the 0-1 variables for determining whether the g-th thermal power unit undergoes non-oil-firing and oil-firing deep regulation renovation in the y-th year respectively;

[0022] Among them: means that after non-oil-firing or oil-firing renovation in a certain year, no further changes will be made in the subsequent planning, that is, the thermal power unit can only be renovated once; means only in the renovation year and is only 1. For example, one year after the transformation, its value is the subtraction of two 1s. One year before the transformation, its value is the subtraction of two 0s. Only in the year of transformation, its value is 1.

[0023] Furthermore, the objective function of minimizing the total life cycle cost includes:

[0024]

[0025] R y =(1 + r) -y ;

[0026] In the formula: N Y is the total number of planned years; and are the investment cost and the operation cost respectively; F RV is the total residual value of the equipment at the end of the plan; R y is the present value coefficient in the y-th year; r is the discount rate;

[0027] The investment cost is:

[0028]

[0029] In the formula: T CPS is the construction period of the hybrid pumped storage, where y ≤ T CPS +1 means it is satisfied throughout the planning period, y = T CPS +1 means it is only satisfied in the last year, and at this time the hybrid pumped storage is put into use; c pv , c w , c th and c ps are the unit investment costs of the photovoltaic power station, the wind farm, the transformation of the thermal power unit, and the pumped storage unit respectively; and are the capacities of the construction or transformation of the photovoltaic power station, the wind farm, the transformation of the thermal power unit, and the pumped storage unit respectively;

[0030] The operation cost is:

[0031]

[0032] Among them:

[0033] In the formula: and are the operation costs of the thermal power unit, the hydropower unit, the new energy, and the pumped storage unit respectively; N S , N T , N G , N H , N PV and N WThey are the number of scenarios, the number of moments, the number of thermal power units, the number of hydropower stations, the number of photovoltaic power stations, and the number of wind farms; p s is the probability of the s-th scenario; is the output of the thermal power unit; and are the operation variables for starting up and shutting down the thermal power unit respectively; c G,su and c G,sd are the cost coefficients for starting up and shutting down the thermal power unit respectively; f(·), f coal (·) and ω loss (·) are the peak shaving function, the coal consumption function, and the unit's deep peak shaving loss function respectively; P G,max 、P G,min 、P G,min1 and P G,min2 are the maximum output, the minimum output before transformation, the minimum output of deep peak shaving without oil injection, and the minimum output of deep peak shaving with oil injection of the thermal power unit respectively; a, b, and c are the quadratic term coefficient, the linear term coefficient, and the constant term coefficient of the coal consumption cost function of the thermal power unit respectively; N t is the number of cycles for rotor cracking; S unit is the purchase cost of the unit; S cost is the fuel price; Z oil is the oil injection volume; is the start-up operation variable of the hydropower unit; c H,su is the start-up cost coefficient of the hydropower unit; and are the actual outputs of photovoltaic and wind power respectively; and are the predicted outputs of photovoltaic and wind power respectively; c PV and c W are the curtailment penalty cost coefficients of photovoltaic and wind power respectively; and are the start-up operation variables for the power generation and pumping conditions of the pumped storage unit respectively; c psG,su and c psP,su are the start-up cost coefficients for the power generation and pumping conditions of the pumped storage unit respectively;

[0034] The equipment residual value is:

[0035]

[0036] In the formula: N type is the number of equipment invested; C p,y is the investment cost of the p-th equipment in the y-th year; δ p is the net residual value rate of the p-th equipment; N p is the operable life of the p-th equipment;

[0037] The objective function of minimizing the remaining load variance includes:

[0038]

[0039] Wherein: is the remaining load; is the original load; is the hydropower output.

[0040] Furthermore, in the multi-objective function of minimizing the life-cycle cost and the variance of the remaining load, the standard boundary intersection method NBI algorithm is also used to transform the two objective functions into a single objective:

[0041] Solve the optimal values of the two objective functions, f 1 (x 1 * ) = min f 1 (x), f 2 (x 2 * ) = min f 2 (x), and substitute them into x 1 * and x 2 * , and solve f 1 (x 2 * ) and f 2 (x 1 * ) to obtain the payoff matrix Connect (f 1 (x 1 * ), f 2 (x 1 * )) and (f 1 (x 2 * ), f 2 (x 2 * )) to get the utopia line;

[0042] Normalize the separately solved objective function values. The normalized objective function is as follows:

[0043]

[0044] The normalized payoff matrix is The distance λ between any point (β 1 , β 2 ) on the utopia line and the point on the Parote front is: where β 1 + β 2= 1, and 0 ≤ β 1 ≤ 1, 0 ≤ β 2 ≤ 1; The Pareto solution set in the multi-objective problem is obtained by solving the maximized distance λ, and by changing β 1 and β 2 values, so that the distance keeps moving, and the original multi-objective problem is transformed into a series of single-objective problems, that is:

[0045] max λ

[0046]

[0047] Furthermore, the establishment of the joint dispatching operation strategy and operation constraint conditions includes:

[0048] The joint dispatching operation strategy includes:

[0049] When the hybrid pumped storage has not been completed for transformation, the hydropower station plays the role of regulating the net load. After the pumped storage transformation is completed, the hydropower and pumped storage are dispatched;

[0050] The operation constraint conditions include:

[0051] Power balance constraint:

[0052]

[0053] In the formula: and are the power of the pumped storage unit for power generation and pumping respectively;

[0054] Thermal power unit operation constraint:

[0055]

[0056]

[0057] In the formula: and are the minimum and maximum ramp rates of the thermal power unit respectively;

[0058] Wind power and photovoltaic output constraints:

[0059]

[0060] Hydropower unit operation constraint:

[0061]

[0062] In the formula: is the state variable of the hydropower unit; is the shutdown operation variable of the hydropower unit; is the power generation efficiency of the hydropower unit; Hi is the average head for power generation; is the power generation flow rate of the hydropower unit; P i H,min and P i H,max are the minimum and maximum outputs of the hydropower unit, respectively;

[0063] Operating constraints of the pumped-storage unit:

[0064]

[0065] In the formula: and are the state variables of power generation and pumping of the pumped-storage unit, respectively; and are the start-up and shutdown operation variables of power generation of the pumped-storage unit, respectively; and are the start-up and shutdown operation variables of pumping of the pumped-storage unit, respectively; η psG and η psP are the efficiencies of power generation and pumping of the pumped-storage unit, respectively; and are the power generation and pumping flow rates of the pumped-storage unit, respectively; and are the coefficients of the minimum output of the pumped-storage unit relative to the capacity of the pumped-storage unit, respectively.

[0066] Furthermore, considering the uncertainty of annual load growth, a system model including the information-gap decision theory is established, including:

[0067] Using the information-gap decision theory IGDT to simulate the uncertainty of load growth;

[0068] Assume that the optimization model considering load uncertainty is:

[0069]

[0070] In the formula: f(x 1 , x 0 ) is the objective function; x 1 and x 2 are decision variables respectively; x 0 is the uncertain load quantity; H(x 2 , x 0 ) and G(x 1 , x 2 ) are equality constraints and inequality constraints respectively;

[0071] Using IGDT to describe x 0 :

[0072]

[0073] In the formula: is the load prediction value; ψ is the deviation coefficient of the load;

[0074] Build an IGDT model that maximizes the deviation coefficient:

[0075]

[0076] In the formula: f 0 is the model objective function without considering load uncertainty; σ is the avoidance coefficient, indicating the acceptable investment capacity;

[0077] In the deterministic model, the objective function 1 is to minimize the comprehensive cost, which is When the comprehensive cost is the largest, denoted as At this time, the system model is:

[0078]

[0079] In the formula: indicates that under the condition of C total reaches the minimum value

[0080] Due to the uncertainty growth of the load, the objective function with the minimum variance of the remaining load becomes:

[0081]

[0082] Furthermore, the use of linearization technology to transform the system model into a mixed-integer linear programming model includes:

[0083] The coal consumption cost is linearized using SOS-2 constraints:

[0084] First, divide the power output range into K intervals with equal step sizes:

[0085]

[0086] Then, introduce a 0-1 variable The output of the thermal power unit and the coal consumption cost are respectively expressed as follows:

[0087]

[0088] For marking the interval where it is located, introduce a binary variable When is in the k-th interval, otherwise, when Not in the k-th interval; the above variables satisfy the following constraints:

[0089]

[0090]

[0091] Linearization of the upper and lower limit constraints of the pumped-storage unit output:

[0092] The upper and lower limit constraints of the pumped-storage unit output are:

[0093]

[0094] Among them, the non-linear parts are and is the multiplication of a 0-1 variable and a continuous variable, and the McCormick convex hull relaxation method is used for linearization; let The processing is as shown in the following formula:

[0095]

[0096] Furthermore, the solving of the mixed-integer linear programming model includes:

[0097] Using Yalmip to call the Gurobi solver, and using the mixed-integer linear programming algorithm to solve the mixed-integer linear programming model to obtain the optimal configuration plan of each device for each year.

[0098] The present invention also includes a capacity configuration device considering the pumped-storage construction period, using the method as described above, including:

[0099] A time-series modeling unit for modeling the time series by considering the construction period of the hybrid pumped-storage and the annual growth of the load;

[0100] A system model modeling unit for establishing a multi-objective function with the minimum full-life cycle cost and the minimum variance of the remaining load, establishing a joint dispatching operation strategy and operation constraint conditions, and considering the uncertainty of the annual growth of the load to establish a system model including the information gap decision theory;

[0101] A linearization unit for using linearization technology to transform the system model into a mixed-integer linear programming model;

[0102] A solving unit for solving the mixed-integer linear programming model to obtain the optimal configuration and operation plan of each device for each year.

[0103] The present invention also includes a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method as described above is implemented.

[0104] The present invention also includes a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method as described above is implemented.

[0105] The beneficial effects of the present invention are as follows: considering the construction period of the hybrid pumped storage and the annual growth of the load, the present invention models the time series; at the same time, considering the economy and the volatility of the remaining load, a multi-objective function with the minimum full-life cycle cost and the minimum variance of the remaining load is established; a combined operation strategy and operation constraint conditions of water storage and thermal power are established; considering the uncertainty of the annual growth of the load, a system model including the information gap decision theory is established; the model is converted into a mixed-integer linear programming model by using linearization technology; a mixed-integer linear programming algorithm is adopted for solution to obtain the optimal configuration and operation plan of each device in each year; the present invention can balance the economy and the load fluctuation, and for the increasing load year by year, the wind-solar capacity is refined and configured year by year, and the thermal power is deeply adjusted and transformed to absorb the redundant wind-solar power. After the construction period of the hybrid pumped storage ends, it is put into use, and the introduction of the construction period avoids problems such as redundant configuration and the decline of the later energy supply quality. Description of the Drawings

[0106] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0107] Figure 1 It is a flowchart of the method in Embodiment 1;

[0108] Figure 2 It is a structural schematic diagram of the device in Embodiment 1;

[0109] Figure 3 It is a structural schematic diagram of the power generation system in Embodiment 2;

[0110] Figure 4 It is a timing diagram for planning in Embodiment 2;

[0111] Figure 5 It is a structural schematic diagram of the computer device. Detailed Embodiments

[0112] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0113] Embodiment 1:

[0114] like Figure 1 As shown: A capacity configuration method considering the pumped storage construction period includes the following steps:

[0115] The temporal characteristics are modeled by considering the construction period of hybrid pumped storage and the annual growth of load;

[0116] Establish a multi-objective function of minimizing the life cycle cost and the variance of the remaining load, establish a joint dispatching operation strategy and operation constraints, consider the uncertainty of annual load growth, and establish a system model including information gap decision theory;

[0117] The system model is transformed into a mixed integer linear programming model using linearization techniques;

[0118] The mixed integer linear programming model is solved to obtain the optimal configuration and operation plan for each equipment in each year.

[0119] Taking into account the construction period of the hybrid pumped storage and the annual growth of the load, the timing is modeled; considering the economy and the volatility of the residual load, a multi-objective function of minimizing the full life cycle cost and minimizing the residual load variance is established; a hydro-storage-thermal power joint scheduling operation strategy and operation constraints are established; considering the uncertainty of the annual load growth, a system model including the information gap decision theory is established; the model is converted into a mixed integer linear programming model using linearization technology; the mixed integer linear programming algorithm is used for solving, and the optimal configuration and operation plan of each equipment in each year is obtained; the present invention can balance the economy and load fluctuations, and according to the increasing load year by year, the wind and solar capacity is finely configured year by year, and the thermal power is deeply adjusted to absorb the excess wind and solar power. The hybrid pumped storage is put into use after the construction period is completed. The introduction of the construction period avoids the problems of redundant configuration and the decline of energy supply quality in the later period.

[0120] In this embodiment, the construction period of the hybrid pumped storage and the annual growth of the load are considered, and the temporal sequence is modeled, including the following steps:

[0121] Since the construction of hybrid pumped storage takes about 3 years, within 1-3 years, as the load increases, wind power and photovoltaic power are configured according to the annual load. At the same time, the energy regulation has deep peak regulation of thermal power units, which is obtained by flexibility transformation. The flexibility transformation of thermal power units has the same planning time as wind and solar configuration, and is planned every year. After the construction period of hybrid pumped storage is completed, the hybrid pumped storage will be put into use in the fourth year, and its capacity will be obtained by optimization;

[0122] The entire planning period is divided into 4 years, and the sequence Y is recorded as:

[0123] Y=[Y 1 ,Y 2 ,Y3 , Y 4 ;

[0124] Where: Y y is the y-th year;

[0125] The overall configuration idea is as follows: In the first year, according to the existing load curve, configure the capacities of wind power and photovoltaic power, and at the same time, carry out flexibility transformation of thermal power units to deeply regulate the peak under the condition of large new energy output, reducing the abandonment of new energy; Secondly, in the second year, the load increases, so according to the increased load, reconfigure the wind and light and carry out flexibility transformation of thermal power units. The third year is the same as the second year; Finally, in the fourth year, the hybrid pumped storage is put into use as a flexibility regulation resource to regulate the system operation.

[0126] The capacity sets of wind power and photovoltaic power configuration and the capacity of thermal power unit transformation are respectively:

[0127]

[0128]

[0129] Where: I w , I pv and I th are respectively the capacity sets of wind power and photovoltaic power configuration and the capacity of thermal power unit transformation; and are respectively the capacities of wind power and photovoltaic power configuration and the capacity of thermal power unit transformation in the y-th year, y = 1, 2, 3, 4;

[0130] Among them, the determination method of the capacity of thermal power unit transformation is:

[0131]

[0132] Where: N Y is the total number of planned years; T CPS is the construction period of the hybrid pumped storage, 3 years; is the minimum output of the thermal power unit after transformation; and are respectively the decision variables of the transformation plan of the g-th thermal power unit in the y-th year; and are respectively the 0-1 variables for determining whether the g-th thermal power unit undergoes non-oil-firing and oil-firing deep regulation transformation in the y-th year;

[0133] Among them: means that after non-oil-firing or oil-firing transformation in a certain year, no further changes will be made in the subsequent plan, that is, the thermal power unit can only be transformed once; means only in the year of transformation and is only 1. For example, in the year after the transformation, its value is the subtraction of two 1s. In the year before the transformation, its value is the subtraction of two 0s. Only in the year of transformation, its value is 1.

[0134] The objective function 1 of the model is the comprehensive cost, including the investment cost and operation cost of each device in each year during the planning period, as well as the residual value of the device at the end of the planning period. The system includes water, wind, light, fire, and storage. The residual value of the configured device is included in the objective function, and the present value factor is used to convert all costs to the beginning of the planning period for calculation;

[0135] The objective function of minimizing the life-cycle cost includes:

[0136]

[0137] R y =(1 + r) -y ;

[0138] In the formula: N Y is the total number of years of the plan; and are the investment cost and operation cost respectively; F RV is the total residual value of the device at the end of the plan; R y is the present value factor in the y-th year; r is the discount rate;

[0139] The investment cost is:

[0140]

[0141] In the formula: T CPS is the construction period of the hybrid pumped storage, where y ≤ T CPS +1 means it is satisfied throughout the planning period, y = T CPS +1 means it is only satisfied in the last year, and at this time the hybrid pumped storage is put into use; c pv 、c w 、c th and c ps are the unit investment costs of the photovoltaic power station, wind farm, thermal power unit transformation, and pumped storage unit respectively; and are the construction or transformation capacities of the photovoltaic power station, wind farm, thermal power unit transformation, and pumped storage unit respectively;

[0142] The operation cost is:

[0143]

[0144] Among them:

[0145] In the formula: and The operating costs of thermal power units, hydropower units, new energy and pumped storage units respectively; N S 、N T 、N G 、N H 、N PV and N W are the number of scenarios, the number of time moments, the number of thermal power units, the number of hydropower stations, the number of photovoltaic power stations and the number of wind farms respectively; p s is the probability of the s-th scenario; is the output of the thermal power unit; and are the operation variables of starting up and shutting down the thermal power unit respectively; c G,su and c G,sd are the cost coefficients of starting up and shutting down the thermal power unit respectively; f(·), f coal (·) and ω loss (·) are the peak shaving function, the coal consumption function and the unit deep regulation loss function respectively; P G,max 、P G,min 、P G,min1 and P G,min2 are the maximum output, the minimum output before transformation, the minimum output of deep regulation without oil injection and the minimum output of deep regulation with oil injection of the thermal power unit respectively; a, b and c are the quadratic term coefficient, the linear term coefficient and the constant term coefficient of the coal consumption cost function of the thermal power unit respectively; N t is the number of cycles of rotor crack initiation; S unit is the purchase cost of the unit; S cost is the fuel price; Z oil is the oil injection volume; is the start-up operation variable of the hydropower unit; c H,su is the start-up cost coefficient of the hydropower unit; and are the actual outputs of photovoltaic and wind power respectively; and are the predicted outputs of photovoltaic and wind power respectively; c PV and c W are the penalty cost coefficients of abandoned electricity for photovoltaic and wind power respectively; and are the start-up operation variables of the pumped storage unit in the power generation and pumping conditions respectively; c psG,su and c psP,su are the start-up cost coefficients of the pumped storage unit in the power generation and pumping conditions respectively;

[0146] The equipment residual value is:

[0147]

[0148] In the formula: N type is the number of equipment invested; C p,yThe investment cost of the p-th device in the y-th year; δ p The net salvage value rate of the p-th device; N p The operable life of the p-th device;

[0149] The objective function of minimizing the variance of the remaining load includes:

[0150]

[0151] In the formula: Is the remaining load; Is the original load; Is the hydropower output.

[0152] In establishing the multi-objective function of minimizing the life cycle cost and the variance of the remaining load, it also includes using the standard boundary crossing method NBI algorithm to transform the two objective functions into a single objective:

[0153] Solve the optimal values of the two objective functions, f 1 (x 1 * ) = min f 1 (x), f 2 (x 2 * ) = min f 2 (x), and substitute into x 1 * And x 2 * , solve f 1 (x 2 * ) and f 2 (x 1 * ), and obtain the payoff matrix Connect (f 1 (x 1 * ), f 2 (x 1 * )) and (f 1 (x 2 * ), f 2 (x 2 * )) to get the utopia line;

[0154] Normalize the separately solved objective function values. The normalized objective function is as follows:

[0155]

[0156] The normalized payoff matrix is Any point on the utopia line (β 1 , β 2 ) and the distance λ from the point on the Parote frontier is: where β 1 + β 2 = 1, and 0 ≤ β 1 ≤ 1, 0 ≤ β 2 ≤ 1; By solving the maximum distance λ, the Pareto solution set in the multi-objective problem is obtained. Changing the values of β 1 and β 2 makes the distance move continuously, and the original multi-objective problem is transformed into a series of single-objective problems, that is:

[0157] max λ

[0158]

[0159] where, establishing the joint dispatching operation strategy and operation constraint conditions, including:

[0160] The joint dispatching operation strategy includes:

[0161] When the hybrid pumped storage has not been completed, the hydropower station plays the role of peak shaving of the net load. After the pumped storage transformation is completed, the hydropower and pumped storage are dispatched;

[0162] When the hybrid pumped storage has not been completed, the hydropower station plays the role of peak shaving of the net load. After the pumped storage transformation is completed, the hydropower and pumped storage are dispatched. To give full play to the peak shaving role of hydropower and pumped storage, water storage can be used to smooth the net load curve. If only hydropower is used for peak shaving, power generation is carried out at the peak of the net load curve and the output is reduced at the trough of the net load curve. If hydropower and pumped storage are jointly used for peak shaving, then hydropower and pumped storage are used for power generation at the peak of the net load curve, and pumped storage is used for pumping at the trough of the net load curve, which can achieve the effect of peak shaving and valley filling. This makes the output of thermal power more stable, reduces the number and depth of deep peak shaving of thermal power units at the trough of the net load, and can also reduce the peak pressure of thermal power units at the peak of the net load. This can achieve the result of hierarchical dispatching, with the upper layer aiming at minimizing the net load variance to optimize the operation of hydropower and pumped storage, and the lower layer aiming at minimizing the comprehensive cost to optimize the operation of thermal power units;

[0163] The operation constraint conditions include:

[0164] Power balance constraint:

[0165]

[0166] In the formula: and are the power for power generation and pumping of the pumped storage unit respectively;

[0167] Operating constraints of thermal power units:

[0168]

[0169] Where: and are the minimum and maximum ramping rates of the thermal power unit, respectively;

[0170] Operating constraints of wind power and PV power output:

[0171]

[0172] Operating constraints of hydroelectric units:

[0173]

[0174] Where: is the state variable of the hydroelectric unit; is the shutdown operation variable of the hydroelectric unit; is the power generation efficiency of the hydroelectric unit; H i is the average head for power generation; is the power generation flow rate of the hydroelectric unit; P i H,min and P i H,max are the minimum and maximum power outputs of the hydroelectric unit, respectively;

[0175] Operating constraints of pumped storage units:

[0176]

[0177]

[0178] Where: and are the state variables of power generation and pumping of the pumped storage unit, respectively; and are the start-up and shutdown operation variables of power generation of the pumped storage unit, respectively; and are the start-up and shutdown operation variables of pumping of the pumped storage unit, respectively; η psG and η psP are the efficiencies of power generation and pumping of the pumped storage unit, respectively; and are the power generation and pumping flow rates of the pumped storage unit, respectively; and are the coefficients of the minimum power output of the pumped storage unit relative to the capacity of the pumped storage unit.

[0179] In this embodiment, considering the uncertainty of annual load growth, a system model incorporating information gap decision theory is established, including:

[0180] The information gap decision theory (IGDT) is used to simulate the uncertainty of load growth;

[0181] In reality, the load varies greatly and its magnitude cannot be accurately predicted, being affected by economic development. The uncertainty of the load directly affects the configuration size. If the load is large, then sufficient wind power and photovoltaic power must be configured to meet the electricity consumption of users. Since there is uncertainty in load growth, the information gap decision theory (IGDT) can be used to simulate the uncertainty of load growth;

[0182] Suppose the optimization model considering load uncertainty is:

[0183]

[0184] In the formula: f(x 1 , x 0 ) is the objective function; x 1 and x 2 are decision variables respectively; x 0 is the uncertain load quantity; H(x 2 , x 0 ) and G(x 1 , x 2 ) are equality constraints and inequality constraints respectively;

[0185] Use IGDT to describe x 0 :

[0186]

[0187] In the formula: is the load prediction value; ψ is the deviation coefficient of the load;

[0188] Establish an IGDT model to maximize the deviation coefficient:

[0189]

[0190] In the formula: f 0 is the model objective function without considering load uncertainty; σ is the avoidance coefficient, indicating the acceptable investment capacity;

[0191] In the deterministic model, the objective function 1 is to minimize the comprehensive cost, which is When , the comprehensive cost is the largest, denoted as At this time, the system model is:

[0192]

[0193] In the formula: represents at Under the condition of C total reaches the minimum value

[0194] Since the load becomes an uncertain increase, the objective function of the minimum residual load variance becomes:

[0195]

[0196] As an optimization of the above embodiment, a linearization technique is used to transform the system model into a mixed-integer linear programming model, including:

[0197] The coal consumption cost is linearized using SOS-2 constraints:

[0198] First, the power output range is divided into K intervals with equal step sizes:

[0199]

[0200] Then, introduce 0-1 variables The output of thermal power units and the coal consumption cost are expressed as follows:

[0201]

[0202] To mark the interval where it is located, introduce binary variables When is in the k-th interval, otherwise, when is not in the k-th interval; the above variables satisfy the following constraint conditions:

[0203]

[0204] Linearization of the upper and lower limit constraints of the pumped-storage unit output:

[0205] The upper and lower limit constraints of the pumped-storage unit output are:

[0206]

[0207] Among them, the non-linear part is and is the multiplication of a 0-1 variable and a continuous variable, and the McCormick convex hull relaxation method is used for linearization; let The processing is as shown in the following formula:

[0208]

[0209] Among them, solving the mixed-integer linear programming model includes:

[0210] The Yalmip is used to call the Gurobi solver, and the mixed-integer linear programming algorithm is used to solve the mixed-integer linear programming model, so as to obtain the optimal configuration scheme of each device in each year.

[0211] As Figure 2 shown, this embodiment also includes a capacity configuration device considering the construction period of the pumped storage. Using the method as described above, it includes:

[0212] A time-series modeling unit, which is used to model the time series by considering the construction period of the hybrid pumped storage and the annual growth of the load;

[0213] A system model modeling unit, which is used to establish a multi-objective function with the minimum life-cycle cost and the minimum variance of the remaining load, establish a joint dispatching operation strategy and operation constraint conditions, and consider the uncertainty of the annual growth of the load to establish a system model including the information gap decision theory;

[0214] A linearization unit, which is used to transform the system model into a mixed-integer linear programming model by using linearization techniques;

[0215] A solving unit, which is used to solve the mixed-integer linear programming model to obtain the optimal configuration and operation scheme of each device in each year.

[0216] Embodiment 2:

[0217] As Figure 3 shown, the embodiment of the present invention includes a cascade hydropower station, a wind farm to be planned, and a photovoltaic power station to be planned. The regulating energy includes a thermal power plant to be flexibly retrofitted and a hybrid pumped storage power station to be built.

[0218] First, considering the construction period of the hybrid pumped storage and the annual growth of the load, the time series is modeled, including:

[0219] As Figure 4 shown, since the construction of the hybrid pumped storage takes about 3 years, within 1 - 3 years, as the load grows, wind power and photovoltaic are configured for the annual load. At the same time, the regulating energy has the deep peak shaving of the thermal power unit, which is obtained by flexible retrofitting. The flexible retrofitting of the thermal power unit is planned at the same time as the configuration of wind and light every year. After the construction period of the hybrid pumped storage ends, in the 4th year, the hybrid pumped storage is put into use, and its capacity is obtained by optimization;

[0220] The entire planning period is divided into 4 years, and the sequence Y is denoted as:

[0221] Y = [Y 1 , Y 2 , Y 3 , Y 4 ;

[0222] where: Y y is the y-th year;

[0223] The overall configuration idea is as follows: In the first year, according to the existing load curve, configure the capacities of wind power and photovoltaic power, and at the same time, carry out flexibility transformation of thermal power units to deeply regulate the peak under the condition of large new energy output, reducing the abandonment of new energy; Secondly, in the second year, the load increases, so according to the increased load, reconfigure the wind and light and carry out flexibility transformation of thermal power units. The third year is the same as the second year; Finally, in the fourth year, the hybrid pumped storage is put into use to regulate the operation of the system as a flexibility regulation resource.

[0224] The sets of capacities configured for wind power and photovoltaic power and the capacities of the thermal power unit transformation are respectively:

[0225]

[0226]

[0227] where: I w , I pv and I th are respectively the sets of capacities configured for wind power and photovoltaic power and the capacities of the thermal power unit transformation; and are respectively the capacities of wind power and photovoltaic power configured and the capacities of thermal power unit transformation in the y-th year, y = 1, 2, 3, 4;

[0228] Among them, the method for determining the capacity of the thermal power unit transformation is:

[0229]

[0230] where: N Y is the total number of planned years, 4 years; T CPS is the construction period of the hybrid pumped storage, 3 years; is the minimum output of the thermal power unit after transformation; and are respectively the decision variables of the transformation plan of the g-th thermal power unit in the y-th year; and are respectively the 0-1 variables for determining whether the g-th thermal power unit undergoes non-oil injection and oil injection deep regulation transformation in the y-th year;

[0231] Among them: indicates that after non-oil injection or oil injection transformation in a certain year, no further changes can be made in the subsequent plan, that is, the thermal power unit can only be transformed once; indicates only in the year of transformation and It is only 1. For example, one year after the transformation, its value is the subtraction of two 1s. One year before the transformation, its value is the subtraction of two 0s. Only in the year of transformation, its value is 1.

[0232] Then, considering both economy and the volatility of the remaining load, a multi-objective function with the minimum life-cycle cost and the minimum variance of the remaining load is established, including:

[0233] 1) The first objective function of the model is the comprehensive cost, including the investment cost and operation cost of each device in each year during the planning period, as well as the residual value of the device at the end of the planning period. The system includes hydropower, wind power, photovoltaic power, thermal power, and energy storage. The residual value of the configured device is included in the objective function, and the present value factor is used to convert all costs to the beginning of the planning period for calculation;

[0234]

[0235] R y =(1 + r) -y ;

[0236] In the formula: N Y is the total number of years of the plan, 4 years; and are the investment cost and operation cost respectively; F RV is the total residual value of the device at the end of the planning period; R y is the present value factor in the yth year; r is the discount rate;

[0237] The investment cost is:

[0238]

[0239] In the formula: T CPS is the construction period of the hybrid pumped storage, 3 years, where y ≤ T CPS +1 means it is satisfied throughout the planning period, y = T CPS +1 means it is only satisfied in the last year, and at this time the hybrid pumped storage is put into use; c pv 、c w 、c th and c ps are the unit investment costs of the photovoltaic power station, wind farm, thermal power unit transformation, and pumped storage unit respectively; and are the construction or transformation capacities of the photovoltaic power station, wind farm, thermal power unit transformation, and pumped storage unit respectively;

[0240] The operation cost is:

[0241]

[0242] Among them:

[0243] Wherein: and are the operating costs of thermal power units, hydropower units, new energy and pumped storage units respectively; N S , N T , N G , N H , N PV and N W are the number of scenarios, the number of time moments, the number of thermal power units, the number of hydropower stations, the number of photovoltaic power stations and the number of wind farms respectively; p s is the probability of the s-th scenario; is the output of the thermal power unit; and are the operation variables of starting up and shutting down the thermal power unit respectively; c G,su and c G,sd are the cost coefficients of starting up and shutting down the thermal power unit respectively; f(·), f coal (·) and ω loss (·) are the peak shaving function, the coal consumption function and the unit deep regulation loss function respectively; P G,max , P G,min , P G,min1 and P G,min2 are the maximum output, the minimum output before transformation, the minimum output of deep regulation without oil injection and the minimum output of deep regulation with oil injection of the thermal power unit respectively; a, b and c are the quadratic term coefficient, the linear term coefficient and the constant term coefficient of the coal consumption cost function of the thermal power unit respectively; N t is the number of rotor crack cycles; S unit is the purchase cost of the unit; S cost is the fuel price; Z oil is the oil injection amount; is the start-up operation variable of the hydropower unit; c H,su is the start-up cost coefficient of the hydropower unit; and are the actual outputs of photovoltaic and wind power respectively; and are the predicted outputs of photovoltaic and wind power respectively; c PV and c W are the penalty cost coefficients for abandoned electricity of photovoltaic and wind power respectively; and are the start-up operation variables of the pumped storage unit in the power generation and pumping conditions respectively; c psG,su and c psP,su are the start-up cost coefficients of the pumped storage unit in the power generation and pumping conditions respectively;

[0244] The equipment salvage value is:

[0245]

[0246] Wherein: N typeis the number of devices invested; C p,y is the investment cost of the p-th device in the y-th year; δ p is the net salvage value rate of the p-th device; N p is the operable life of the p-th device.

[0247] 2) The objective function 2 is to minimize the variance of the remaining load:

[0248]

[0249] In the formula: is the remaining load.

[0250] 3) The NBI algorithm is used to transform the two objective functions into a single objective:

[0251] Solve the optimal values of the two objective functions, f 1 (x 1 * ) = min f 1 (x), f 2 (x 2 * ) = min f 2 (x), and substitute them into x 1 * and x 2 * , solve f 1 (x 2 * ) and f 2 (x 1 * ), and obtain the payment matrix Connect (f 1 (x 1 * ), f 2 (x 1 * )) and (f 1 (x 2 * ), f 2 (x 2 * )) to get the utopia line;

[0252] Normalize the objective function values solved separately. The normalized objective functions are as follows:

[0253]

[0254] The normalized payment matrix is Any point (β 1 , β 2 ) on the utopia line and the point on the Parote front The distance λ is as follows: where β 1 +β 2 = 1, and 0 ≤ β 1 ≤ 1, 0 ≤ β 2 ≤ 1. By solving for the maximized distance λ, the Pareto solution set in the multi-objective problem can be obtained. By changing the values of β 1 and β 2 , such that the distance keeps moving, the original multi-objective problem is transformed into a series of single-objective problems, namely:

[0255] max λ

[0256]

[0257] Next, a combined operation strategy and operation constraint conditions for water storage and thermal power are established, including:

[0258] There are mainly two existing combined operation strategies for pumped storage and thermal power: the synchronous operation method for pumped storage and thermal power and the timed operation method for pumped storage;

[0259] The synchronous operation method for pumped storage and thermal power usually unifies the operation costs of pumped storage and thermal power and optimizes the operation of pumped storage and thermal power synchronously. There is no obvious sequence relationship in the dispatching strategy. Therefore, this method changes the pumping and generating operation modes of the pumped storage unit in real time according to the demand, which often greatly increases the start-stop times of the pumped storage, and the capacity of the pumped storage is relatively small compared to thermal power, so the maximum dispatching role of the pumped storage cannot be exerted;

[0260] The timed operation method for pumped storage arranges the pumped storage output according to the load curve of "one pumping and one generating" or "one pumping and two generating". It can pump water during the load trough and generate electricity during the load peak. This method is feasible when there is no large-scale integration of new energy. However, with the large-scale integration of wind and light, the power grid volatility is large, and the net load obtained by subtracting the wind and light output from the load does not have the characteristics of the original load peak and trough. If the traditional timed operation method for pumped storage is continued to be used, it will seriously affect the peak shaving economy of thermal power units and the system peak shaving economy;

[0261] In this embodiment, compared with the general pumped storage and thermal power dispatching, hydropower is added. The pumped storage is transformed from a cascade hydropower station and is a hybrid pumped storage. Therefore, the combined dispatching strategy for water storage and thermal power proposed by the present invention is as follows:

[0262] Before the hybrid pumped-storage power station is transformed, the hydropower station plays the role of regulating the net load. After the pumped-storage transformation is completed, the hydropower and pumped-storage are dispatched. To give full play to the peak-shaving role of hydropower and pumped-storage, water storage can be used to smooth the net load curve. If only hydropower is used for peak shaving, it generates electricity at the peak of the net load curve and reduces output at the trough of the net load curve. If hydropower and pumped-storage are jointly used for peak shaving, then hydropower and pumped-storage are used for power generation at the peak of the net load curve, and pumped-storage is used for pumping at the trough of the net load curve, which can achieve the effect of peak shaving and valley filling. This makes the output of thermal power more stable, reduces the number and depth of deep peak shaving of thermal power units at the trough of the net load, and can also reduce the peak pressure of thermal power units at the peak of the net load. This can achieve the result of hierarchical dispatching. The upper layer takes the minimum net load variance as the objective function to optimize the operation of hydropower and pumped-storage, and the lower layer takes the minimum comprehensive cost as the objective function to optimize the operation of thermal power units;

[0263] Some of the operation constraints are as follows:

[0264] 1) The power balance constraint is:

[0265]

[0266] In the formula: and are the power of the pumped-storage unit for power generation and pumping respectively;

[0267] 2) The operation constraints of thermal power units are:

[0268]

[0269] In the formula: and are the minimum and maximum ramp rates of thermal power units respectively;

[0270] 3) The output constraints of wind power and photovoltaic power are:

[0271]

[0272] 4) The operation constraints of hydropower units are:

[0273]

[0274] In the formula: is the state variable of the hydropower unit; is the shutdown operation variable of the hydropower unit; is the power generation efficiency of the hydropower unit; H i is the average head for power generation; is the power generation flow of the hydropower unit; P i H,min and P i H,maxare the minimum and maximum outputs of the hydropower unit, respectively;

[0275] 5) The operating constraints of the pumped-storage unit are:

[0276]

[0277] In the formula: and are the state variables of power generation and pumping of the pumped-storage unit, respectively; and are the start-up and shutdown operation variables of power generation of the pumped-storage unit, respectively; and are the start-up and shutdown operation variables of pumping of the pumped-storage unit, respectively; η psG and η psP are the efficiencies of power generation and pumping of the pumped-storage unit, respectively; and are the flow rates of power generation and pumping of the pumped-storage unit, respectively; and are the coefficients of the minimum output of the pumped-storage unit relative to the capacity of the pumped-storage unit, respectively.

[0278] Next, considering the uncertainty of annual load growth, a system model including information gap decision theory is established, including:

[0279] In practice, the load changes greatly and its magnitude cannot be accurately predicted, which is affected by economic development. The uncertainty of the load directly affects the configuration size. If the load is large, then sufficient wind power and photovoltaic power must be configured to meet the electricity consumption of users. Due to the uncertainty of load growth, the information gap decision theory (IGDT) can be used to simulate the uncertainty of load growth;

[0280] Suppose the optimization model considering load uncertainty is:

[0281]

[0282] In the formula: f(x 1 , x 0 ) is the objective function; x 1 and x 2 are decision variables respectively; x 0 is the uncertain load quantity; H(x 2 , x 0 ) and G(x 1 , x 2 ) are equality constraints and inequality constraints respectively;

[0283] Use IGDT to describe x 0 :

[0284]

[0285] In the formula: is the load prediction value; ψ is the deviation coefficient of the load;

[0286] Establishing an IGDT model that maximizes the deviation coefficient can maximize the robustness of the model:

[0287]

[0288] In the formula: f 0 is the model objective function without considering load uncertainty; σ is the avoidance coefficient, indicating the acceptable investment capacity;

[0289] In the deterministic model, the objective function 1 is to minimize the comprehensive cost, which is When the comprehensive cost is the largest, denoted as At this time, the IGDT programming model is:

[0290]

[0291] In the formula: indicates that under the condition of C total takes the minimum value

[0292] Due to the load becoming an uncertain growth, the objective 2 becomes:

[0293]

[0294] Next, use linearization techniques to transform the model into a mixed-integer linear programming model, including:

[0295] 1) The coal consumption cost is linearized using the SOS-2 constraint:

[0296] First, the power output range can be divided into K intervals with equal step sizes:

[0297]

[0298] Then, introduce a 0-1 variable The output of the thermal power unit and the coal consumption cost can be expressed as follows:

[0299]

[0300] To mark the interval where it is located, a binary variable is introduced When is in the k-th interval, otherwise, when Not in the k-th interval. The above variables satisfy the following constraints:

[0301]

[0302] 2) Linearization of the upper and lower limit constraints of the pumped-storage unit output:

[0303] The upper and lower limit constraints of the pumped-storage unit output are:

[0304]

[0305] Among them, the non-linear parts are and which are the multiplication of 0-1 variables and continuous variables, and the McCormick convex hull relaxation method can be used for linearization. Let The processing is as shown in the following formula:

[0306]

[0307] Finally, the mixed-integer linear programming algorithm is used for solving to obtain the optimal configuration plan of each device in each year, including:

[0308] The Yalmip is used to call the Gurobi solver to solve the mixed-integer linear programming model, and the optimal configuration plan of each device in each year is obtained.

[0309] Please refer to Figure 5 the structural schematic diagram of the computer device provided by the embodiment of the present application shown. A computer device 400 provided by an embodiment of the present application includes: a processor 410 and a memory 420. The memory 420 stores a computer program executable by the processor 410. When the computer program is executed by the processor 410, the above method is executed.

[0310] An embodiment of the present application also provides a storage medium 430. A computer program is stored on the storage medium 430. When the computer program is run by the processor 410, the above method is executed.

[0311] Among them, the storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0312] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The meaning of "plurality" is two or more, unless otherwise specifically defined.

[0313] In the present invention, unless otherwise clearly specified and limited, the terms "mounted", "connected", "connected to", "fixed" and other terms should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal connection of two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0314] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not have to be directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0315] Any process or method description represented in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations where functions may be executed not in the order shown or discussed, including in a substantially simultaneous manner according to the functions involved or in a reverse order, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0316] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing a logical function, and can be specifically implemented in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable medium on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0317] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0318] Those of ordinary skill in the art can understand that all or part of the steps carried out in implementing the above method embodiments can be completed by instructing relevant hardware through a program, and the said program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0319] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A capacity configuration method considering the construction period of pumped storage, characterized in that: The steps include: The temporal characteristics are modeled by considering the construction period of hybrid pumped storage and the annual growth of load; Establish a multi-objective function of minimizing the life cycle cost and the variance of the remaining load, establish a joint dispatching operation strategy and operation constraints, consider the uncertainty of annual load growth, and establish a system model including information gap decision theory; Converting the system model into a mixed integer linear programming model using a linearization technique; Solving the mixed integer linear programming model to obtain the optimal configuration and operation plan for each equipment in each year; The temporal modeling is carried out by considering the construction period of the hybrid pumped storage and the annual growth of the load, and includes the following steps: The entire planning period is divided into 4 years, and the sequence Y is recorded as: Y = [Y1, Y2, Y3, Y4]; Where: Y y is the yth year; The capacity of wind power, photovoltaic configuration and thermal power unit transformation are as follows: Where: I w ,I pv and I th They are the capacity of wind power, photovoltaic configuration and the capacity set of thermal power unit transformation; and are the capacity of wind power, photovoltaic power configuration and thermal power unit transformation in year y, y = 1, 2, 3, 4; Among them, the method for determining the capacity of thermal power unit transformation is: Where: N Y is the total number of planning years; T CPS The construction period for hybrid pumped storage is 3 years; It is the minimum output of the thermal power unit after transformation; and are the decision variables for the transformation plan of the g-th thermal power unit in year y; and They are 0-1 variables that determine whether the g-th thermal power unit will be modified without oil or with oil in the yth year; in: It means that after the non-oil or oil-using transformation is carried out in a certain year, no changes will be made in the subsequent planning, that is, the thermal power unit can only be transformed once; Indicates only in the year of renovation and It is 1 only. One year after the transformation, its value is two 1s subtracted. One year before the transformation, its value is two 0s subtracted. Only in the year of transformation, its value is 1. The objective function of minimizing the life cycle cost includes: R y ＝(1+r) -y ； Where: N Y The total number of planning years; and F are investment cost and operating cost respectively; RV is the total residual value of equipment at the end of the planning period; R y is the present value coefficient of the yth year; r is the discount rate; The investment cost is: Where: T CPS is the construction period of hybrid pumped storage, where y≤T CPS +1 means that the planning period is satisfied, y = T CPS +1 means that it is only met in the last year, when the hybrid pumped storage is put into use; c pv 、c w 、c th and c ps They are the unit investment costs of photovoltaic power stations, wind farms, thermal power unit renovation and pumped storage units; and They are the capacity of construction or renovation of photovoltaic power stations, wind farms, thermal power unit renovation and pumped storage units; The running cost is: in: Where: and are the operating costs of thermal power units, hydropower units, new energy units and pumped storage units respectively; N s 、N T 、N G 、N H 、N PV and N W They are the number of scenes, the number of moments, the number of thermal power units, the number of hydropower stations, the number of photovoltaic power stations and the number of wind farms; p s is the probability of the sth scenario; Provide power for thermal power units; and are the operating variables for starting and stopping the thermal power units respectively; c G，su and c G，sd are the cost coefficients for starting and stopping thermal power units, respectively; f(·), f coal (·) and ω loss (·) are peak load regulation function, coal consumption function and unit deep regulation loss function respectively; P G，max , P G，min , P G，min1 and P G，min2 are the maximum output of the thermal power unit, the minimum output before transformation, the minimum output without oil injection and the minimum output with oil injection; a, b and c are the quadratic coefficient, linear coefficient and constant coefficient of the coal consumption cost function of the thermal power unit respectively; N t is the number of rotor cracking cycles; S unit is the purchase cost of the unit; S cost is the fuel price; Z oil is the oil injection amount; is the startup operation variable of the hydropower unit; c H，su is the startup cost coefficient of the hydropower unit; and are the actual outputs of photovoltaic and wind power respectively; and are the predicted outputs of photovoltaic power and wind power respectively; c PV and c W are the penalty cost coefficients for curtailment of photovoltaic and wind power respectively; and are the startup operation variables of the pumped storage unit for power generation and pumping conditions respectively; c psG，su and c psP，su are the startup cost coefficients of the pumped storage unit for power generation and pumping conditions, respectively; The residual value of the equipment is: Where: N type is the number of equipment invested; C p，y is the investment cost of the p-th equipment in year y; p is the net residual value rate of the pth type of equipment; N p is the operational life of the pth type of equipment; The objective function for minimizing the residual load variance includes: Where: and are the power of generating electricity and pumping water by the pumped storage unit respectively; is the residual load; is the original load; Contribute to hydropower; The multi-objective function of establishing the minimum life cycle cost and the minimum residual load variance also includes converting the two objective functions into a single objective using the standard boundary intersection method NBI algorithm: Solve for the optimal values ​​of two objective functions: f1(x1 * )=min f1(x),f2(x2 * )=min f2(x), Substitute into x1 respectively * and x2 * , solve f1(x2 * ) and f2(x1 * ), and obtain the payment matrix Connect (f1 (x1 * ), f2(x1 * )) and (f1(x2 * ), f2(x2 * )), get the Utopia line; The separately solved objective function values ​​are normalized, and the normalized objective function is as follows: The normalized payoff matrix is Any point (β1, β2) on the Utopia line and a point on the Parote frontier The distance λ is: Among them, β1+β2=1, and 0≤β1≤1, 0≤β2≤1; by solving the maximized distance λ, we can get the Pareto solution set in the multi-objective problem. By changing the values ​​of β1 and β2, the distance keeps moving, and the original multi-objective problem is transformed into a series of single-objective problems, namely: Considering the uncertainty of annual load growth, a system model including information gap decision theory is established, including: The information gap decision theory IGDT is used to simulate the uncertainty of load growth; Assume that the optimization model considering load uncertainty is: Where: f(x1, x0) is the objective function; x1 and x2 are decision variables; x0 is the uncertainty load; H(x2, x0) and G(x1, x2) are equality constraints and inequality constraints respectively; Using IGDT to describe x0: Where: is the load prediction value; ψ is the load deviation coefficient; Build an IGDT model that maximizes the deviation coefficient: Where: f0 is the model objective function without considering load uncertainty; σ is the avoidance coefficient, which indicates the acceptable investment capacity; In the deterministic model, objective function 1 is to minimize the comprehensive cost, which is when When , the comprehensive cost is the largest, recorded as At this time, the system model is: Where: Indicated in Under the condition of total Get the minimum value Since the load changes into uncertainty growth, the objective function of minimizing the residual load variance becomes:

2. The capacity configuration method considering the pumped storage construction period according to claim 1 is characterized in that: The establishment of the joint dispatch operation strategy and operation constraints includes: The joint dispatch operation strategy includes: When the hybrid pumped storage system is not transformed, the hydropower station will play the role of net load peak regulation. After the pumped storage system is transformed, the hydropower station and pumped storage system will be used for dispatching. The operating constraints include: Power balance constraints: Where: and are the power of generating electricity and pumping water by the pumped storage unit respectively; Thermal power unit operation constraints: Where: and are the minimum and maximum ramp rates of thermal power units respectively; Wind power and photovoltaic output constraints: Operation constraints of hydropower units: Where: is the state variable of the hydropower unit; It is the shutdown operation variable of the hydropower unit; is the power generation efficiency of the hydropower unit; H i is the average water head for power generation; is the power generation flow of the hydropower unit; P i H，min and P i H，max are the minimum and maximum outputs of the hydropower units, respectively; Pumped storage unit operation constraints: Where: and are the state variables of power generation and water pumping of the pumped storage unit, respectively; and They are the startup and shutdown operation variables of the pumped storage unit power generation; and are the operating variables of the pumped storage unit when starting and stopping pumping water; η psG and η psP are the efficiency of power generation and water pumping of the pumped storage unit, respectively; and are the power generation and pumping flow of the pumped storage unit, respectively; and They are respectively the coefficients of the minimum output of the pumped storage unit relative to the capacity of the pumped storage unit.

3. The capacity configuration method considering the pumped storage construction period according to claim 1 is characterized in that: The method of converting the system model into a mixed integer linear programming model using a linearization technique includes: The coal consumption cost is linearized using the SOS-2 constraint: First, the power output range is divided into K intervals with equal step sizes: Then, introduce 0-1 variables The output and coal consumption cost of thermal power units are expressed as follows: For marking The interval in which we are located introduces a binary variable when In the kth interval, otherwise, when Not in the kth interval; the above variables satisfy the following constraints: Linearization of upper and lower output constraints of pumped storage units: The upper and lower limits of the output of the pumped storage unit are: in, and are the power of generating electricity and pumping water by the pumped storage unit respectively; the nonlinear part is and The 0-1 variable is multiplied by the continuous variable, and the McCormick convex envelope relaxation method is used for linearization; The processing is as follows:

4. The capacity configuration method considering the pumped storage construction period according to claim 1 is characterized in that: The solving the mixed integer linear programming model comprises: Yalmip is used to call the Gurobi solver, and a mixed integer linear programming algorithm is used to solve the mixed integer linear programming model to obtain the optimal configuration plan for each device in each year.

5. A capacity configuration device considering the construction period of pumped storage, characterized in that: Use of the method according to any one of claims 1 to 4, comprising: The time series modeling unit is used to model the time series by considering the construction period of the hybrid pumped storage and the annual growth of the load; System modeling unit, used to establish multi-objective functions of minimum life cycle cost and minimum residual load variance, establish joint dispatch operation strategy and operation constraints, consider the uncertainty of annual load growth, and establish a system model including information gap decision theory; A linearization unit, used for converting the system model into a mixed integer linear programming model using a linearization technique; The solving unit is used to solve the mixed integer linear programming model to obtain the optimal configuration and operation plan of each equipment in each year.

6. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 4 is implemented.

7. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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