Establishment method of compact and simple model of wind, light, water and fire nuclear storage multi-source conservation and supply

Abstract

The invention relates to the technical field of power system dispatching, in particular to a wind-light-water-fire nuclear storage multi-source guarantee supply tight and simple model establishing method, which comprises the following steps of: establishing a weekly plan model to obtain maintenance plans and electric quantity plans of a thermal power generating unit and a nuclear power generating unit; establishing a compact and simple model of the wind-light-water-fire nuclear storage multi-source system; establishing an intraday planning model, and obtaining a water pumping and power generation plan of a pumped storage power station, a start-stop plan and an output plan of a thermal power unit, an output plan of a nuclear power unit and a battery charging and discharging plan; establishing a rolling plan model, and correcting the power generation plan of the thermal power and nuclear power unit in the remaining time period in the day in a rolling manner; establishing a real-time plan model, and modifying the output plan of the thermal power generating unit in the next time period in real time; and outputting a multi-source power system guarantee supply optimization scheme. According to the method, the scheduling plan is continuously updated and corrected along with the shortening of the time scale, and the scheduling plan with a higher matching degree with the actual load is finally formulated, so that the capability of absorbing the abandoned wind and light is improved.

Description

Technical Field

[0001] This invention relates to the field of power system dispatching technology, and in particular to a method for establishing a simple and efficient multi-source power supply model involving wind, solar, hydro, thermal, nuclear, and energy storage. Background Technology

[0002] Since the goal of "peak carbon and carbon neutrality" was proposed, new energy power generation forms such as wind power, photovoltaic power, hydropower, and nuclear power have become important strategic development directions for my country to achieve clean power generation. The scale of new energy power generation and energy storage systems is continuously expanding, enabling them to effectively complement traditional thermal power. This ultimately forms a comprehensive energy system with multiple energy sources, including wind, solar, hydro, coal, and nuclear power—a multi-source system (wind-solar-hydro-thermal-nuclear-storage system). This system can maximize the advantages of various energy sources, improving the peak-shaving performance of thermal power units while achieving good economic benefits for grid operation. The multi-energy system can maximize the advantages of different energy sources and form mutual complementarity, playing a crucial role in effectively solving the problem of traditional wind and solar curtailment, increasing the proportion of new energy, and optimizing the energy structure.

[0003] The uncertainties inherent in renewable energy generation, such as peak shaving, volatility, disorder, and poor coordination, pose significant challenges to the safe operation of the power grid. Existing hydro-thermal coordinated dispatch measures are insufficient to address the new development trend of the power grid with multiple energy sources coexisting. Therefore, it is urgent to conduct research on the construction of multi-timescale supply guarantee models for multi-energy complementary systems (wind, solar, hydro, thermal, nuclear, and storage) under extreme operating conditions such as continuous high temperatures. This research aims to clarify the coupling mechanism and integrated operation and control methods of the various energy power subsystems within the wind, solar, hydro, thermal, nuclear, and storage systems, providing technical means to ensure the power balance of the system over a wide area and throughout all time periods.

[0004] Power system unit combination optimization has a significant impact on the economic operation and safe dispatch of the power system. It can not only save substantial economic costs but also improve the reliability of the power system through a certain amount of spinning reserve. The unit combination optimization problem involves two sub-problems: unit combination, which determines which units are contributing power; and economic load allocation, which determines how much power these units need to contribute. The decision variables in the unit combination optimization problem involve not only discrete variables representing the unit operating states (operating and shutting down are represented by 1 and 0 respectively) but also semi-continuous variables representing unit output. Constraints include power balance, spinning reserve, minimum start-up and shutdown, start-up cost, and ramp rate.

[0005] Existing unit commitment (UC) models for power systems suffer from low computational efficiency, making them ill-suited for the practical needs of power grid dispatching and operation. Existing unit output and ramp constraints are not sufficiently tight, further hindering computational efficiency. Redundant ramp constraints increase computational complexity. Furthermore, existing UC models rarely provide methods for constructing constraint equality or inequality equations, hindering their generalization to multi-energy systems considering various complex constraints. Therefore, power grid companies urgently require a computationally efficient, compact, and concise power system model incorporating multiple energy sources such as wind, solar, hydro, thermal, nuclear, and energy storage. This model would enable the control and dispatch of power generation resources, ensuring power supply even under extreme operating conditions such as continuous high temperatures, thereby achieving resource optimization and energy conservation / emission reduction goals. Summary of the Invention

[0006] To address the problem of difficulty in improving the efficiency and accuracy of solving large-scale multi-source power system economic dispatch problems in existing technologies, this invention provides a method for establishing a compact and simple model for multi-source power supply guarantee involving wind, solar, hydro, thermal, nuclear, and energy storage. The specific technical solution is as follows:

[0007] A method for establishing a simple and efficient multi-source supply guarantee model for wind, solar, hydro, thermal, nuclear, and energy storage includes the following steps:

[0008] Step S1: Using a 1-day period and a 1-week cycle, based on the long-term forecasts of wind power, solar power, and load power, and the maintenance plans submitted by thermal power units and nuclear power units, a weekly planning model is established with the optimization objective of minimizing the sum of the maintenance costs and power generation costs of thermal power units and nuclear power units, thus obtaining the maintenance plans and power generation plans for thermal power units and nuclear power units; Step S2: With the optimization objective of minimizing the sum of the costs of curtailing wind, solar, and nuclear power and the power generation and start-up costs of thermal power units, a compact and simple model of a multi-source system of wind, solar, hydro, thermal, nuclear, and energy storage is established.

[0009] The constraints of the model include operational constraints of wind, solar, hydro, thermal, nuclear, and energy storage power sources, spinning reserve constraints, and power balance constraints.

[0010] The operational constraints for wind, solar, hydro, thermal, nuclear, and energy storage power sources include wind power operation constraints, solar power operation constraints, hydropower operation constraints, thermal power operation constraints, nuclear power operation constraints, and battery energy storage power station operation constraints.

[0011] Step S3: Using 1 hour as the time period and 1 day as the cycle, based on the maintenance plans submitted by thermal power units and nuclear power units and the daily predicted values ​​of planned electricity generation, wind power, photovoltaic power and load power formulated by the weekly planning model, an intraday planning model is established with the objective function of the compact and concise model of the multi-source system of wind, solar, hydro, thermal, nuclear and storage as the optimization objective. The pumping and power generation plans of pumped storage power stations, the start-up and shutdown plans and output plans of thermal power units, the output plans of nuclear power units and the battery charging and discharging plans are obtained. The constraints of the intraday planning model include intraday planned power generation constraints, wind, solar, hydro, thermal, nuclear and storage power operation constraints, spinning reserve constraints and power balance constraints.

[0012] Step S4: Using 1 hour as a scheduling period, the daily planning model is updated every 4 hours. In the last period before the end of the previous 4 hours, based on the start-up and shutdown plan of thermal power units, the power generation plan of hydropower and battery storage, the daily power generation plan, the short-term forecast values ​​of wind power, photovoltaic power and load power, and the actual power generation of the units in the previous 4 hours, a rolling planning model is established with the optimization objective of minimizing the sum of the costs of curtailing wind, solar and nuclear power and the power generation cost of thermal power units. The thermal power output plan and the power generation plan of nuclear power units for the remaining period of the day are continuously revised. The constraints of the rolling planning model include the planned power generation constraints for the remaining period of the day, wind power operation constraints, photovoltaic operation constraints, thermal power operation constraints, nuclear power operation constraints, spinning reserve constraints, and power balance constraints.

[0013] Step S5: Using 15-minute scheduling periods, the rolling planning model is updated every 15 minutes. A real-time planning model is established with the optimization objective of minimizing the sum of wind curtailment, solar curtailment, and real-time adjustment costs of thermal power units. Before the end of the previous scheduling period, the output plan of thermal power units for the next period is modified in real time based on the known ultra-short-term forecast values ​​of wind power, solar power, and load power. The constraints include: wind power operation constraints, solar power operation constraints, thermal power operation constraints, spinning reserve constraints, and power balance constraints.

[0014] Step S6: Output the multi-source power system supply optimization scheme.

[0015] Preferably, the objective function of the weekly planning model in step S1 is:

[0016]

[0017] Among them, f w T represents the objective function value of the weekly plan. week N represents the number of time periods in the weekly plan. T N N These refer to the number of thermal power units and nuclear power units, respectively. Let be the maintenance costs of thermal power unit i and nuclear power unit i on day t, respectively. These represent the maintenance status of thermal power unit i and nuclear power unit i on day t, respectively. The value is 0 when maintenance is in progress and 1 otherwise. These represent the planned power generation and unit power cost of thermal power unit i on day t, respectively.

[0018] The constraints of the weekly planning model include system power balance constraints, daily planned power generation constraints, weekly planned power generation constraints, unit maintenance constraints, and system reserve constraints.

[0019] (1) The system power balance constraints are as follows:

[0020]

[0021] in, These are the predicted output power values ​​of the wind farm and the photovoltaic farm on day t, respectively. Let i be the planned electricity generation of nuclear power unit i on day t. This represents the predicted system load power consumption for day t.

[0022] (2) The daily planned power generation constraints are as follows:

[0023] Daily planned power generation constraints for thermal power units:

[0024] Daily planned power generation constraints for nuclear power units:

[0025] Among them, P i T,max P i N,max These represent the maximum power generation of thermal power unit i and nuclear power unit i in a single time period, respectively.

[0026] (3) Weekly planned power generation constraints are as follows:

[0027] Weekly planned power generation constraints for thermal power units:

[0028] Weekly planned power generation constraints for nuclear power units:

[0029] in, These are the minimum power generation capacities of thermal power unit i and nuclear power unit i, respectively. These are the maximum power generation of thermal power unit i and nuclear power unit i, respectively.

[0030] (4) The constraints for unit maintenance are as follows:

[0031]

[0032]

[0033] in, These are the maintenance start times for thermal power unit i and nuclear power unit i, respectively. These refer to the maintenance duration for thermal power unit i and nuclear power unit i, respectively.

[0034] The system's standby constraints are as follows:

[0035]

[0036] in, These are the predicted average power output values ​​for the wind farm and the solar power plant on day t, respectively; P t D,max Let t be the predicted peak load value of the system on day t. This represents the system's standby capacity on day t.

[0037] Preferably, the objective function of the compact and concise model of the multi-source system (wind, solar, hydro, thermal, nuclear, and energy storage) is:

[0038]

[0039] Where T is the total number of time periods in the scheduling cycle; These represent the costs of wind and solar power curtailment during time period t. Let i be the power generation cost and start-up cost of thermal power unit i in time period t; Let i be the cost of decommissioning nuclear power unit i during time period t;

[0040] The costs of curtailing wind, solar, and nuclear power are calculated as follows:

[0041]

[0042]

[0043]

[0044] Where, δ W δ PV δ N These represent the unit costs for wind, solar, and nuclear power curtailment, respectively.

[0045] These represent the predicted available power for wind power and solar power in time period t, respectively.

[0046] P t W P t PV These represent the actual dispatched power of wind power and solar power during time period t, respectively.

[0047] The actual dispatched power of nuclear power unit i during time period t;

[0048] The cost calculation for thermal power units is as follows:

[0049] Power generation cost of thermal power units:

[0050] Among them, a i b i c i The correlation coefficient for the operating costs of thermal power units. This indicates the output of nuclear power unit i during time period t; for Perform a projection transformation to obtain

[0051]

[0052] Among them, P i T,max P i T,min The upper and lower limits of the output of thermal power unit i; u i,t Let i be the state variable of thermal power unit i during time period t, where "1" indicates operation and "0" indicates shutdown.

[0053] but Represented as:

[0054]

[0055]

[0056]

[0057]

[0058] Start-up cost of thermal power units

[0059] in, The hot start cost of thermal power unit i; The portion of the start-up cost of thermal power unit i that exceeds the hot start cost; v i,t This represents the startup status of thermal power unit i during time period t. The value is 1 if the unit is running, and 0 otherwise.

[0060] Preferably, the daily planned power generation constraint in step S3 is as follows:

[0061] Daily planned power generation constraints for thermal power units:

[0062]

[0063] Daily planned power generation constraints for nuclear power units:

[0064]

[0065] Among them, T day This refers to the number of time slots planned for the day. These are the daily planned power generation limits for thermal power unit i and nuclear power unit i, respectively. These are the daily planned power limits for thermal power unit i and nuclear power unit i, respectively; the specific limits are determined by the weekly planning model, and the calculation method is as follows:

[0066]

[0067]

[0068] Preferably, the objective function of the rolling planning model in step S4 is:

[0069]

[0070] Among them, T roll The number of time periods in the rolling plan decreases continuously with each rolling update;

[0071] The specific constraints on planned power generation for the remaining period of the day are as follows:

[0072] Daily planned power generation constraints for thermal power units: Daily planned power generation constraints for nuclear power units: The upper and lower limits of the planned power generation for each unit during the remaining time of the day will be updated using the following formula:

[0073]

[0074]

[0075] in, These represent the actual power generation of thermal power unit i and nuclear power unit i in the first 4 hours, respectively.

[0076] Preferably, the objective function of the real-time planning model in step S5 is:

[0077]

[0078] Where, ρ i,t The unit output adjustment cost of thermal power unit i during time period t; The output of thermal power unit i in time period t in the real-time plan; Let i be the output of thermal power unit i in time period t in the rolling planning model.

[0079] Preferably, the operational constraints of the wind, solar, hydro, thermal, nuclear, and energy storage power sources are as follows:

[0080] (1) Wind power operation constraints:

[0081]

[0082] (2) Photoelectric operation constraints:

[0083]

[0084] (3) Constraints on hydropower operation:

[0085] a. State constraints of pumped storage power stations:

[0086]

[0087] in, The variable is a binary variable representing the energy storage state of a pumped storage power station. It is 1 when the power station is in the energy storage state and 0 otherwise. The variable is a binary variable representing the power generation status of a pumped storage power station. It is 1 when the power station is generating electricity and 0 otherwise.

[0088] b. Power generation constraints and pumping power constraints of pumped storage power stations:

[0089]

[0090]

[0091] Among them, P t H,in P represents the electricity consumed by a pumped-storage power station during time period t for pumping water. Hin,max P Hin,min These represent the upper and lower limits of the electricity consumption of a pumped storage power station in a single time period; P t H,out P represents the output power of a pumped-storage hydroelectric power station during time period t. Hout,max P Hout,min These represent the upper and lower limits of the electricity output of a pumped storage power station during a single time period.

[0092] c. Reservoir capacity constraints of pumped storage power stations:

[0093] V min ≤V t ≤V max ;

[0094]

[0095] Among them, V t V represents the reservoir capacity of a pumped storage power station during time period t; max V min These represent the upper and lower limits of the reservoir capacity of a pumped storage power station; V t+1 η represents the reservoir capacity of the pumped storage power station at time t+1. in η outThese are the pumping efficiency and power generation efficiency of the pumped storage power station's reservoir capacity, respectively.

[0096] (4) Constraints on thermal power plant operation:

[0097] a. Binary variable logical constraints for thermal power units:

[0098] v i,t -w i,t =u i,t -u i,t-1 ;

[0099] Among them, w i,t The shutdown status of thermal power unit i during time period t is 1 if the unit is shut down, and 0 otherwise.

[0100] b. Initial state constraints:

[0101] u i,t =u i,0 , t∈[1,L,U i +L i ];

[0102] U i =[min[T,u i,0 ( T on,i -T i,0 )]] + ;

[0103] L i =[min[T,(1-u i，0 ()( T off，i +T i，0 )]] + ;

[0104] Among them, u i,0 This represents the state of thermal power unit i during the initial period, i.e., the period before the start of the dispatch cycle, where "1" indicates operation and "0" indicates shutdown; U i L represents the time that thermal power unit i still needs to run at the initial moment. i This indicates the time that thermal power unit i still needs to be shut down at the initial moment; T is the total number of scheduling periods, [·] + This represents max(0,·); T on,i This represents the minimum start-up time of thermal power unit i; T off,i T represents the minimum shutdown time of thermal power unit i; i,0 This indicates the number of time periods during which thermal power unit i has been continuously started or shut down before the start of the scheduling cycle;

[0105] c. Minimum start-up and shutdown constraints:

[0106]

[0107]

[0108] d. New binary variable constraints:

[0109] The scheduling cycle T of each generator unit and the time period before the scheduling cycle, totaling T+1 time periods, can be divided into T-M+2 intersecting sliding windows of size M; the leftmost end of the m-th sliding window is the m-th time period of the scheduling cycle, and the rightmost end is the m+M-1-th time period, where m∈[0,T-M+1].

[0110] Introducing new state variables This represents the start-up and shutdown status of thermal power unit i within the m-th window; if thermal power unit i starts up during any time period h in the m-th window, i.e., u h =1, when h>m, u h-1 =0, and continue running until the end of time period k, i.e., u k =1, when k < m + M - 1, u k+1 =0, then otherwise The specific constraints are as follows:

[0111]

[0112]

[0113]

[0114] e. Startup cost constraints:

[0115]

[0116] in, The cold start cost of thermal power unit i; T cold,i Let τ be the cold start time of thermal power unit i; if τ- T off,i - T cold,i ≤0 and [-T i,0 ] + <|τ- T off,i - T cold,i -1|+1, then f init,i,t =1, otherwise f init,i,t =0;

[0117] f. Upper and lower limits of thermal power unit output:

[0118] Based on the unit combination basic data, the upper / lower bounds of unit output are projected to 0 to 1, constructing a continuous variable of projected unit output, and establishing upper and lower limit constraints for unit output:

[0119]

[0120]

[0121]

[0122]

[0123]

[0124] Among them, P i T,up This represents the upward ramp rate of thermal power unit i; P represents the upward ramp rate of thermal power unit i after projection transformation; i T,down This represents the downward ramp rate of thermal power unit i; P represents the downward ramp rate of thermal power unit i after projection transformation; i T,start This represents the minimum output value of thermal power unit i when it is started up. P represents the minimum output value of thermal power unit i at startup after projection transformation; i T,shut This indicates the maximum output value of thermal power unit i when it is shut down; This represents the maximum output value of thermal power unit i after projection transformation when it is shut down;

[0125] g. Climbing constraints for thermal power units:

[0126]

[0127]

[0128] t∈[m+1,m+M-1]; a∈[1,tm];

[0129] (5) Nuclear power plant operation constraints:

[0130] Divide the nuclear power safety peak shaving depth range into n equal parts k For the k-th level of nuclear power unit i, the peak-shaving depth is:

[0131]

[0132] Among them, P i N,max The minimum output allowed for nuclear power unit i;

[0133] The nuclear power output of nuclear power unit i during the low-power phase at the k-th peak shaving depth is:

[0134]

[0135] u i,k,j,t Let be the power increase / decrease operating state variable of nuclear power unit i in the j-th state of the k-th peak shaving depth during time period t. There are 3 power increase / decrease states under each peak shaving depth, and the corresponding nuclear power output is:

[0136]

[0137] Nuclear power output can be linearly expressed as:

[0138]

[0139] Among them, h i,t Let l be the rated power operating state variable of nuclear power unit i during time period t; i,k,t For nuclear power unit i, the low-power operation state variable during time period t at peak shaving depth k;

[0140] b. Constraints on runtime state variables:

[0141]

[0142] c. Coupling constraints of operating state variables when the power rise / fall time is 2 hours:

[0143] h i,t+1 ≥l i,k,t-1 +u i,k,2,t -1;

[0144] l i,k,t+1 ≥h i,t-1 +u i,k,2,t -1;

[0145] d. Coupling constraints of operating state variables when the power rise / fall time is 3 hours:

[0146] h i,t+1 ≥u i,k,1,t-1 +u i,k,3,t -1;

[0147] l i,k,t+1 ≥u i,k,3,t-1 +u i,k,1,t -1;

[0148] u i,k,1,t+1 ≥h i,t-1 +u i,k,3,t -1;

[0149] u i,k,3,t+1 ≥l i,k,t-1 +ui,k,1,t -1;

[0150] e. Constraints on rated power and low-power operation time of nuclear power units:

[0151]

[0152]

[0153] in, These are the minimum continuous operating time at full power and the minimum continuous operating time at low power for nuclear power unit i, respectively.

[0154] (6) Operational constraints of battery energy storage power stations:

[0155] a. Charge / discharge state constraints:

[0156] Battery energy storage actually has three states of charge and discharge: charging, discharging, and standby. In any given time period t, battery energy storage can only be in one state of charge and discharge, namely:

[0157] u c,t +u d,t ≤1

[0158] Among them, u c,t u d,t The variables representing the charge and discharge states of a battery energy storage power station are respectively: u during charging. c,t If u is 1, otherwise it is 0; when the battery discharges... d,t It is 1 if it is true, otherwise it is 0;

[0159] b. Charge / discharge power constraints:

[0160] 0≤P c,t ≤u c,t P c,max ;

[0161] 0≤P d,t ≤u d,t P d,max ;

[0162] Among them, P c,t P d,t P represents the charging power and discharging power of the battery energy storage power station during time period t, respectively. c,max P d,max These represent the maximum charging power and maximum discharging power of the battery energy storage power station, respectively.

[0163] c. Energy constraint:

[0164] During any scheduling period, the energy of the battery energy storage station should be within its allowable energy range; to ensure the sustainability of the battery energy storage station's scheduling, the stored energy should be restored to its initial value at the end of the scheduling cycle, i.e.:

[0165] E b,t+1 =E b,t +η c P c,t Δt-P d,t Δt / η d ;

[0166] E b,min ≤E b,t ≤E b,max ;

[0167] E b,T =E b,0 ;

[0168] Among them, E b,t η represents the remaining energy of the battery storage power station during time period t. c η d These represent the charging and discharging efficiency of the battery energy storage power station; Δt is the time length corresponding to the time period of the scheduling plan; E b,max E b,min These represent the upper and lower limits of the remaining energy of the battery storage power station, respectively; E b,T E represents the remaining energy of the battery storage power station at the end of the dispatch cycle. b,0 This indicates the initial remaining energy of the battery energy storage power station.

[0169] Preferably, the rotational spare constraint is as follows:

[0170]

[0171]

[0172] in, Let t be the system's required value for positive rotational reserve during time period t; This represents the system's negative rotational reserve requirement during time period t.

[0173] Preferably, the power balance constraint is:

[0174]

[0175] Among them, P t D The system load power prediction value for time period t.

[0176] Compared with the prior art, the beneficial effects of the present invention are as follows: The scheduling strategy of the present invention includes four time scales: weekly plan, daily plan, rolling plan and real-time plan. As the time scale shortens, the scheduling plan is continuously updated and revised, and finally a scheduling plan with a higher degree of matching with the actual load is formulated, thereby improving the ability to absorb wind and solar power curtailment. Attached Figure Description

[0177] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0178] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0179] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0180] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0181] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0182] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0183] like Figure 1 As shown in the figure, this embodiment provides a method for establishing a simple and concise model for multi-source supply guarantee involving wind, solar, hydro, thermal, nuclear, and energy storage, including the following steps:

[0184] Step S1: Using 1 day as a time period and 1 week as a cycle (a total of 7 time periods), based on the long-term forecast values ​​of wind power, solar power, and load power, and the maintenance plans submitted by thermal power units and nuclear power units, a weekly planning model is established with the optimization objective of minimizing the sum of the maintenance cost and the power generation cost of thermal power units and nuclear power units, to obtain the maintenance plan and power generation plan of thermal power units and nuclear power units.

[0185] The objective function of the weekly planning model is:

[0186]

[0187] Among them, f w T represents the objective function value of the weekly plan. week N represents the number of time periods in the weekly plan. T N N These refer to the number of thermal power units and nuclear power units, respectively. Let be the maintenance costs of thermal power unit i and nuclear power unit i on day t, respectively. These represent the maintenance status of thermal power unit i and nuclear power unit i on day t, respectively. The value is 0 when maintenance is in progress and 1 otherwise. These represent the planned power generation and unit power cost of thermal power unit i on day t, respectively.

[0188] The constraints of the weekly planning model include system power balance constraints, daily planned power generation constraints, weekly planned power generation constraints, unit maintenance constraints, and system reserve constraints.

[0189] (1) The system power balance constraints are as follows:

[0190]

[0191] in, These are the predicted output power values ​​of the wind farm and the photovoltaic farm on day t, respectively. Let i be the planned electricity generation of nuclear power unit i on day t. This represents the predicted system load power consumption for day t.

[0192] (2) The daily planned power generation constraints are as follows:

[0193] Daily planned power generation constraints for thermal power units:

[0194] Daily planned power generation constraints for nuclear power units:

[0195] Among them, P i T,max P i N,max These represent the maximum power generation of thermal power unit i and nuclear power unit i in a single time period, respectively.

[0196] (3) Weekly planned power generation constraints are as follows:

[0197] Weekly planned power generation constraints for thermal power units:

[0198] Weekly planned power generation constraints for nuclear power units:

[0199] in, These are the minimum power generation capacities of thermal power unit i and nuclear power unit i, respectively. These are the maximum power generation of thermal power unit i and nuclear power unit i, respectively.

[0200] Specifically, in this embodiment of the invention, the maximum and minimum weekly power generation of thermal power and nuclear power units are set based on fuel contracts, fuel transportation capacity, unit performance, the principle of fairness, openness and impartiality, and social factors.

[0201] (4) The constraints for unit maintenance are as follows:

[0202]

[0203]

[0204] in, These are the maintenance start times for thermal power unit i and nuclear power unit i, respectively. These are the maintenance durations for thermal power unit i and nuclear power unit i, respectively. In this embodiment of the invention, the maintenance start time and maintenance duration are determined by the provided maintenance plan.

[0205] (5) The system standby constraints are as follows:

[0206]

[0207] in, These are the predicted average power output values ​​for the wind farm and the solar power plant on day t, respectively; P t D,max Let t be the predicted peak load value of the system on day t. Let t be the system reserve capacity on day t. Specifically, in this embodiment of the invention, 10% of the predicted peak load value of the system is selected as the system reserve capacity.

[0208] Step S2: With the goal of minimizing the sum of the costs of curtailing wind, solar, and nuclear power and the power generation and start-up costs of thermal power units, a compact and simple model of a multi-source system of wind, solar, hydro, thermal, nuclear, and energy storage is established.

[0209] The constraints of the model include operational constraints of wind, solar, hydro, thermal, nuclear, and energy storage power sources, spinning reserve constraints, and power balance constraints.

[0210] The operational constraints for wind, solar, hydro, thermal, nuclear, and energy storage power sources include wind power operation constraints, solar power operation constraints, hydropower operation constraints, thermal power operation constraints, nuclear power operation constraints, and battery energy storage power station operation constraints.

[0211] The objective function of the compact and concise model of the multi-source system (wind, solar, hydro, thermal, nuclear, and energy storage) is:

[0212]

[0213] Where T is the total number of time periods in the scheduling cycle; These represent the costs of wind and solar power curtailment during time period t. Let i be the power generation cost and start-up cost of thermal power unit i in time period t; Let i be the cost of decommissioning nuclear power unit i during time period t;

[0214] The costs of curtailing wind, solar, and nuclear power are calculated as follows:

[0215]

[0216]

[0217]

[0218] Where, δ W δ PV δ N These represent the unit costs for wind, solar, and nuclear power curtailment, respectively.

[0219] These represent the predicted available power for wind power and solar power in time period t, respectively.

[0220] P t W P t PV These represent the actual dispatched power of wind power and solar power during time period t, respectively.

[0221] The actual dispatched power of nuclear power unit i during time period t;

[0222] The cost calculation for thermal power units is as follows:

[0223] Power generation cost of thermal power units:

[0224] Among them, a i b i c i The correlation coefficient for the operating costs of thermal power units. This indicates the output of nuclear power unit i during time period t; for Perform a projection transformation to obtain

[0225]

[0226] Among them, P i T,max P i T,min The upper and lower limits of the output of thermal power unit i; u i,t Let i be the state variable of thermal power unit i during time period t, where "1" indicates operation and "0" indicates shutdown.

[0227] but Represented as:

[0228]

[0229]

[0230]

[0231]

[0232] Start-up cost of thermal power units

[0233] in, The hot start cost of thermal power unit i; The portion of the start-up cost of thermal power unit i that exceeds the hot start cost; v i,t This represents the startup status of thermal power unit i during time period t. The value is 1 if the unit is running, and 0 otherwise.

[0234] The operational constraints of wind, solar, hydro, thermal, nuclear, and energy storage power sources are as follows:

[0235] (1) Wind power operation constraints:

[0236]

[0237] (2) Photoelectric operation constraints:

[0238]

[0239] (3) Constraints on hydropower operation:

[0240] a. State constraints of pumped storage power stations:

[0241]

[0242] in, The variable is a binary variable representing the energy storage state of a pumped storage power station. It is 1 when the power station is in the energy storage state and 0 otherwise. The variable is a binary variable representing the power generation status of a pumped storage power station. It is 1 when the power station is generating electricity and 0 otherwise.

[0243] b. Power generation constraints and pumping power constraints of pumped storage power stations:

[0244]

[0245]

[0246] Among them, P t H,in P represents the electricity consumed by a pumped-storage power station during time period t for pumping water. Hin,max P Hin,min These represent the upper and lower limits of the electricity consumption of a pumped storage power station in a single time period; P t H,out P represents the output power of a pumped-storage hydroelectric power station during time period t. Hout,max P Hout,min These represent the upper and lower limits of the electricity output of a pumped storage power station during a single time period.

[0247] c. Reservoir capacity constraints of pumped storage power stations:

[0248] V min ≤V t ≤V max ;

[0249]

[0250] Among them, V t V represents the reservoir capacity of a pumped storage power station during time period t; max V min These represent the upper and lower limits of the reservoir capacity of a pumped storage power station; V t+1 η represents the reservoir capacity of the pumped storage power station at time t+1. in η out These are the pumping efficiency and power generation efficiency of the pumped storage power station's reservoir capacity, respectively.

[0251] (4) Constraints on thermal power plant operation:

[0252] a. Binary variable logical constraints for thermal power units:

[0253] v i,t -w i,t =u i,t -u i,t-1 ;

[0254] Among them, w i,t The shutdown status of thermal power unit i during time period t is 1 if the unit is shut down, and 0 otherwise.

[0255] b. Initial state constraints:

[0256] u i,t =u i,0, t∈[1,L,U i +L i ];

[0257] U i =[min[T,u i,0 ( T on,i -T i,0 )]] + ;

[0258] L i =[min[T,(1-u i，0 ()( T off，i +T i，0 )]] + *

[0259] Among them, u i,0 This represents the state of thermal power unit i during the initial period, i.e., the period before the start of the dispatch cycle, where "1" indicates operation and "0" indicates shutdown; U i L represents the time that thermal power unit i still needs to run at the initial moment. i This indicates the time that thermal power unit i still needs to be shut down at the initial moment; T is the total number of scheduling periods, [·] + This represents max(0,·); T on,i This represents the minimum start-up time of thermal power unit i; T off,i T represents the minimum shutdown time of thermal power unit i; i,0 This indicates that thermal power unit i has been continuously running before the start of the dispatching cycle (T). i,0 Take a positive value) or turn off (T) i,0 The number of time periods (taking negative values);

[0260] c. Minimum start-up and shutdown constraints:

[0261]

[0262]

[0263] d. New binary variable constraints:

[0264] The scheduling cycle T of each generator unit and the time period before the scheduling cycle, totaling T+1 time periods, can be divided into T-M+2 intersecting sliding windows of size M; the leftmost end of the m-th sliding window is the m-th time period of the scheduling cycle, and the rightmost end is the m+M-1-th time period, where m∈[0,T-M+1].

[0265] Introducing new state variables This represents the start-up and shutdown status of thermal power unit i within the m-th window; if thermal power unit i starts up during any time period h in the m-th window, i.e., u h =1, when h>m, u h-1 =0, and continue running until the end of time period k, i.e., u k =1, when k < m + M - 1, u k+1 =0, then otherwise The specific constraints are as follows:

[0266]

[0267]

[0268]

[0269] e. Startup cost constraints:

[0270]

[0271] in, The cold start cost of thermal power unit i; T cold,i Let τ be the cold start time of thermal power unit i; if τ- T off,i - T cold,i ≤0 and [-T i,0 ] + <|τ- T off,i - T cold,i -1|+1, then f init,i,t =1, otherwise f init,i,t =0;

[0272] f. Upper and lower limits of thermal power unit output:

[0273] Based on the unit combination basic data, the upper / lower bounds of unit output are projected to 0 to 1, constructing a continuous variable of projected unit output, and establishing upper and lower limit constraints for unit output:

[0274]

[0275]

[0276]

[0277]

[0278]

[0279] Among them, Pi T,up This represents the upward ramp rate of thermal power unit i; P represents the upward ramp rate of thermal power unit i after projection transformation; i T,down This represents the downward ramp rate of thermal power unit i; P represents the downward ramp rate of thermal power unit i after projection transformation; i T,start This represents the minimum output value of thermal power unit i when it is started up. P represents the minimum output value of thermal power unit i at startup after projection transformation; i T,shut This indicates the maximum output value of thermal power unit i when it is shut down; This represents the maximum output value of thermal power unit i after projection transformation when it is shut down;

[0280] g. Climbing constraints for thermal power units:

[0281]

[0282]

[0283] t∈[m+1,m+M-1]; a∈[1,tm];

[0284] (5) Nuclear power plant operation constraints:

[0285] Divide the nuclear power safety peak shaving depth range into n equal parts k For the k-th level of nuclear power unit i, the peak-shaving depth is:

[0286]

[0287] Among them, P i N,max The minimum output allowed for nuclear power unit i;

[0288] The nuclear power output of nuclear power unit i during the low-power phase at the k-th peak shaving depth is:

[0289]

[0290] u i,k,j,t Let be the power increase / decrease operating state variable of nuclear power unit i in the j-th state of the k-th peak shaving depth during time period t. There are 3 power increase / decrease states under each peak shaving depth, and the corresponding nuclear power output is:

[0291]

[0292] Nuclear power output can be linearly expressed as:

[0293]

[0294] Among them, h i,t Let l be the rated power operating state variable of nuclear power unit i during time period t; i,k,t For nuclear power unit i, the low-power operation state variable during time period t at peak shaving depth k;

[0295] b. Constraints on runtime state variables:

[0296]

[0297] c. Coupling constraints of operating state variables when the power rise / fall time is 2 hours:

[0298] h i,t+1 ≥l i,k,t-1 +u i,k,2,t -1;

[0299] l i,k,t+1 ≥h i,t-1 +u i,k,2,t -1;

[0300] d. Coupling constraints of operating state variables when the power rise / fall time is 3 hours:

[0301] h i,t+1 ≥u i,k,1,t-1 +u i,k,3,t -1;

[0302] l i,k,t+1 ≥u i,k,3,t-1 +u i,k,1,t -1;

[0303] u i,k,1,t+1 ≥h i,t-1 +u i,k,3,t -1;

[0304] u i,k,3,t+1 ≥l i,k,t-1 +u i,k,1,t -1;

[0305] e. Constraints on rated power and low-power operation time of nuclear power units:

[0306]

[0307]

[0308] in, These are the minimum continuous operating time at full power and the minimum continuous operating time at low power for nuclear power unit i, respectively.

[0309] (6) Operational constraints of battery energy storage power stations:

[0310] a. Charge / discharge state constraints:

[0311] Battery energy storage actually has three states of charge and discharge: charging, discharging, and standby. In any given time period t, battery energy storage can only be in one state of charge and discharge, namely:

[0312] u c,t +u d,t ≤1

[0313] Among them, u c,t u d,t The variables representing the charge and discharge states of a battery energy storage power station are respectively: u during charging. c,t If u is 1, otherwise it is 0; when the battery discharges... d,t It is 1 if it is true, otherwise it is 0;

[0314] b. Charge / discharge power constraints:

[0315] 0≤P c,t ≤u c,t P c,max ;

[0316] 0≤P d,t ≤u d,t P d,max ;

[0317] Among them, P c,t P d,t P represents the charging power and discharging power of the battery energy storage power station during time period t, respectively. c,max P d,max These represent the maximum charging power and maximum discharging power of the battery energy storage power station, respectively.

[0318] c. Energy constraint:

[0319] Overcharging and over-discharging batteries will shorten their cycle life. Therefore, during any scheduling period, the energy of the battery energy storage station should be within its allowable energy range. To ensure the sustainability of the battery energy storage station's scheduling, the stored energy should be restored to its initial value at the end of the scheduling cycle.

[0320] E b,t+1 =E b,t +η c P c,t Δt-P d,t Δt / η d ;

[0321] E b,min ≤E b,t ≤E b,max ;

[0322] E b,T =E b,0 ;

[0323] Among them, E b,t η represents the remaining energy of the battery storage power station during time period t. c η d These represent the charging and discharging efficiency of the battery energy storage power station; Δt is the time length corresponding to the time period of the scheduling plan; E b,max E b,min These represent the upper and lower limits of the remaining energy of the battery storage power station, respectively; E b,T E represents the remaining energy of the battery storage power station at the end of the dispatch cycle. b,0 This indicates the initial remaining energy of the battery energy storage power station.

[0324] The specific rotational standby constraint is as follows:

[0325]

[0326]

[0327] in, Let t be the system's required value for positive rotational reserve during time period t; This represents the system's negative rotational reserve requirement during time period t.

[0328] The power balance constraint is:

[0329]

[0330] Among them, P t D The system load power prediction value for time period t.

[0331] Step S3: Using 1-hour time periods and 1-day cycles (a total of 24 time periods), based on the maintenance plans submitted by thermal power units and nuclear power units and the daily predicted values ​​of planned electricity generation, wind power, photovoltaic power, and load power formulated by the weekly planning model, an intraday planning model is established with the objective function of the compact and concise model of the multi-source system of wind, solar, hydro, thermal, nuclear, and storage as the optimization objective. This yields the pumping and power generation plans of pumped storage power stations, the start-up and shutdown plans and output plans of thermal power units, the output plans of nuclear power units, and the battery charging and discharging plans. The constraints of the intraday planning model include intraday planned power generation constraints, wind, solar, hydro, thermal, nuclear, and storage power operation constraints, spinning reserve constraints, and power balance constraints.

[0332] The objective function to be optimized is minf d =f;

[0333] The specific constraints on the planned power generation for the day are as follows:

[0334] Daily planned power generation constraints for thermal power units:

[0335]

[0336] Daily planned power generation constraints for nuclear power units:

[0337]

[0338] Among them, T day This refers to the number of time slots planned for the day. These are the daily planned power generation limits for thermal power unit i and nuclear power unit i, respectively. These are the daily planned power limits for thermal power unit i and nuclear power unit i, respectively; the specific limits are determined by the weekly planning model, and the calculation method is as follows:

[0339]

[0340]

[0341] In this embodiment of the invention, the initial reservoir capacity of the pumped storage power station is...

[0342] Step S4: Using a 1-hour scheduling period, the daily planning model is updated every 4 hours. In the last period before the end of the previous 4 hours, based on the daily plan's start-up and shutdown schedule for thermal power units, hydropower and battery energy storage plans, daily power generation plan, short-term forecasts of wind power, solar power, and load power, and the actual power generation of the units in the previous 4 hours, a rolling planning model is established with the optimization objective of minimizing the sum of wind, solar, and nuclear curtailment costs and thermal power unit generation costs. This model continuously adjusts the thermal power output plan and nuclear power unit generation plan for the remaining time periods of the day. The hydropower generation plan is determined by the daily plan, and the start-up and shutdown status of the thermal power units is as follows: i,t It is determined by the intraday plan. The constraints of the rolling plan model include the planned power generation for the remaining period of the day, wind power operation constraints, photovoltaic operation constraints, thermal power operation constraints, nuclear power operation constraints, spinning reserve constraints, and power balance constraints.

[0343] Unit start-up and shutdown status u i,t Pumped storage power station energy storage status Pumped storage power station power generation status Battery energy storage power station charge and discharge status u c,t and u d,t Determined by the intraday plan, the objective function of the rolling plan model is:

[0344]

[0345] Among them, T roll The number of time periods in the rolling plan decreases continuously with each rolling update;

[0346] The specific constraints on planned power generation for the remaining period of the day are as follows:

[0347] Daily planned power generation constraints for thermal power units:

[0348] Daily planned power generation constraints for nuclear power units:

[0349] The upper and lower limits of the planned power generation for each unit during the remaining time of the day will be updated using the following formula:

[0350]

[0351]

[0352] in, These represent the actual power generation of thermal power unit i and nuclear power unit i in the first 4 hours, respectively.

[0353] In this embodiment of the invention, the initial value of the reservoir capacity of the pumped storage power station in each scheduling cycle is equal to the reservoir capacity of the last time period before the end of the previous 4 hours; the initial remaining energy of the battery energy storage power station is equal to the remaining energy of the last time period before the end of the previous 4 hours.

[0354] Step S5: Using 15-minute scheduling periods, the rolling planning model is updated every 15 minutes. A real-time planning model is established with the optimization objective of minimizing the sum of wind curtailment, solar curtailment, and real-time adjustment costs of thermal power units. Before the end of the previous scheduling period, the output plan of thermal power units for the next period is modified in real time based on the known ultra-short-term forecast values ​​of wind power, solar power, and load power. The constraints include: wind power operation constraints, solar power operation constraints, thermal power operation constraints, spinning reserve constraints, and power balance constraints.

[0355] The objective function of the real-time planning model is:

[0356]

[0357] Where, ρ i,t The unit output adjustment cost of thermal power unit i during time period t; The output of thermal power unit i in time period t in the real-time plan; Let x be the output of thermal power unit i in time period t in the rolling planning model. Since the rolling plan uses 1 hour as a time period, while the real-time plan uses 15 minutes as a time period, in this embodiment, the output of the rolling plan in time period x, which contains the t-th time period of the real-time plan, is used. of As P t T,S ; This represents the output of thermal power unit i in the real-time plan during period t.

[0358] Step S6: Output the multi-source power system supply optimization scheme.

[0359] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for establishing a concise and simple multi-source supply guarantee model for wind, solar, hydro, thermal, nuclear, and energy storage, characterized in that, Includes the following steps: Step S1: Using 1 day as the time period and 1 week as the cycle, based on the long-term forecast values ​​of wind power, solar power, and load power, and the maintenance plans submitted by thermal power units and nuclear power units, a weekly planning model is established with the optimization objective of minimizing the sum of the maintenance cost and the power generation cost of thermal power units and nuclear power units, so as to obtain the maintenance plan and power generation plan of thermal power units and nuclear power units. Step S2: With the goal of minimizing the sum of the costs of curtailing wind, solar, and nuclear power and the power generation and start-up costs of thermal power units, a compact and simple model of a multi-source system of wind, solar, hydro, thermal, nuclear, and energy storage is established. The constraints of the model include operational constraints of wind, solar, hydro, thermal, nuclear, and energy storage power sources, spinning reserve constraints, and power balance constraints. The operational constraints for wind, solar, hydro, thermal, nuclear, and energy storage power sources include wind power operation constraints, solar power operation constraints, hydropower operation constraints, thermal power operation constraints, nuclear power operation constraints, and battery energy storage power station operation constraints. Step S3: Using 1 hour as the time period and 1 day as the cycle, based on the maintenance plans submitted by thermal power units and nuclear power units and the daily predicted values ​​of planned electricity, wind power, photovoltaic power and load power formulated by the weekly planning model, and taking the objective function of the compact and simple model of the multi-source system of wind, solar, hydro, thermal, nuclear and storage as the optimization objective, an intraday planning model is established; the pumping and power generation plans of pumped storage power stations, the start-up and shutdown plans and output plans of thermal power units, the output plans of nuclear power units, and the battery charging and discharging plans are obtained; The constraints of the intraday planning model include intraday planned power generation constraints, wind, solar, hydro, thermal, nuclear and energy storage power operation constraints, spinning reserve constraints, and power balance constraints. Step S4: Using 1 hour as a scheduling period, the daily planning model is updated every 4 hours. In the last period before the end of the first 4 hours, based on the start-up and shutdown plan of thermal power units, the power generation plan of hydropower and battery storage, the daily power plan, the short-term forecast values ​​of wind power, photovoltaic power and load power, and the actual power generation of the units in the first 4 hours, a rolling planning model is established with the optimization objective of minimizing the sum of the cost of curtailing wind, solar and nuclear power and the power generation cost of thermal power units. The thermal power output plan and the power generation plan of nuclear power units for the remaining period of the day are then continuously revised. The constraints of the rolling planning model include the planned power generation for the remaining time period within the day, wind power operation constraints, photovoltaic operation constraints, thermal power operation constraints, nuclear power operation constraints, spinning reserve constraints, and power balance constraints. Step S5: Using 15-minute scheduling periods, the rolling planning model is updated every 15 minutes. A real-time planning model is established with the optimization objective of minimizing the sum of wind curtailment, solar curtailment, and real-time adjustment costs of thermal power units. Before the end of the previous scheduling period, the output plan of thermal power units for the next period is modified in real time based on the known ultra-short-term forecast values ​​of wind power, solar power, and load power. The constraints include: wind power operation constraints, solar power operation constraints, thermal power operation constraints, spinning reserve constraints, and power balance constraints. Step S6: Output the multi-source power system supply optimization scheme.

2. The method for establishing a concise and efficient multi-source supply guarantee model based on wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, is characterized in that... The objective function of the weekly planning model in step S1 is: Among them, f w T represents the objective function value of the weekly plan. week N represents the number of time periods in the weekly plan. T N N These refer to the number of thermal power units and nuclear power units, respectively. Let be the maintenance costs of thermal power unit i and nuclear power unit i on day t, respectively. These represent the maintenance status of thermal power unit i and nuclear power unit i on day t, respectively. The value is 0 when maintenance is in progress and 1 otherwise. These represent the planned power generation and unit power cost of thermal power unit i on day t, respectively. The constraints of the weekly planning model include system power balance constraints, daily planned power generation constraints, weekly planned power generation constraints, unit maintenance constraints, and system reserve constraints. (1) The system power balance constraints are as follows: in, These are the predicted output power values ​​of the wind farm and the photovoltaic farm on day t, respectively. Let i be the planned electricity generation of nuclear power unit i on day t. This represents the predicted system load power consumption for day t. (2) The daily planned power generation constraints are as follows: Daily planned power generation constraints for thermal power units: Daily planned power generation constraints for nuclear power units: Among them, P i T,max P i N,max These represent the maximum power generation of thermal power unit i and nuclear power unit i in a single time period, respectively. (3) Weekly planned power generation constraints are as follows: Weekly planned power generation constraints for thermal power units: Weekly planned power generation constraints for nuclear power units: in, These are the minimum power generation capacities of thermal power unit i and nuclear power unit i, respectively. These are the maximum power generation of thermal power unit i and nuclear power unit i, respectively. (4) The constraints for unit maintenance are as follows: in, These are the maintenance start times for thermal power unit i and nuclear power unit i, respectively. These refer to the maintenance duration for thermal power unit i and nuclear power unit i, respectively. The system's standby constraints are as follows: in, These are the predicted average power output values ​​for the wind farm and the solar power plant on day t, respectively; P t D,max Let t be the predicted peak load value of the system on day t. This represents the system's standby capacity on day t.

3. The method for establishing a concise and efficient multi-source supply guarantee model based on wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, is characterized in that... The objective function of the compact and concise model of the multi-source system (wind, solar, hydro, thermal, nuclear, and energy storage) is: Where T is the total number of time periods in the scheduling cycle; These represent the costs of wind and solar power curtailment during time period t. Let i be the power generation cost and start-up cost of thermal power unit i in time period t; Let i be the cost of decommissioning nuclear power unit i during time period t; The costs of curtailing wind, solar, and nuclear power are calculated as follows: Where, δ W δ PV δ N These represent the unit costs for wind, solar, and nuclear power curtailment, respectively. These represent the predicted available power for wind power and solar power in time period t, respectively. P t W P t PV These represent the actual dispatched power of wind power and solar power during time period t, respectively. The actual dispatched power of nuclear power unit i during time period t; The cost calculation for thermal power units is as follows: Power generation cost of thermal power units: Among them, a i b i c i The correlation coefficient for the operating costs of thermal power units. This indicates the output of nuclear power unit i during time period t; for Perform a projection transformation to obtain Among them, P i T,max P i T,min The upper and lower limits of the output of thermal power unit i; u i,t Let i be the state variable of thermal power unit i during time period t, where "1" indicates operation and "0" indicates shutdown. but Represented as: Start-up cost of thermal power units in, The hot start cost of thermal power unit i; The portion of the start-up cost of thermal power unit i that exceeds the hot start cost; v i,t This represents the startup status of thermal power unit i during time period t. The value is 1 if the unit is running, and 0 otherwise.

4. The method for establishing a concise and efficient multi-source supply model for wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, characterized in that... The specific daily planned power generation constraints in step S3 are as follows: Daily planned power generation constraints for thermal power units: Daily planned power generation constraints for nuclear power units: Among them, T day This refers to the number of time slots planned for the day. These are the daily planned power generation limits for thermal power unit i and nuclear power unit i, respectively. These are the daily planned power limits for thermal power unit i and nuclear power unit i, respectively; the specific limits are determined by the weekly planning model, and the calculation method is as follows:

5. The method for establishing a concise and efficient multi-source supply guarantee model based on wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, characterized in that... The objective function of the rolling planning model in step S4 is: Among them, T roll The number of time periods in the rolling plan decreases continuously with each rolling update; The specific constraints on planned power generation for the remaining period of the day are as follows: Daily planned power generation constraints for thermal power units: Daily planned power generation constraints for nuclear power units: The upper and lower limits of the planned power generation for each unit during the remaining time of the day will be updated using the following formula: in, These represent the actual power generation of thermal power unit i and nuclear power unit i in the first 4 hours, respectively.

6. The method for establishing a concise and simple multi-source supply guarantee model based on wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, is characterized in that... The objective function of the real-time planning model in step S5 is: Where, ρ i,t The unit output adjustment cost of thermal power unit i during time period t; The output of thermal power unit i in time period t in the real-time plan; Let i be the output of thermal power unit i in time period t in the rolling planning model.

7. The method for establishing a concise and simple multi-source supply guarantee model based on wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, is characterized in that... The operational constraints for the wind, solar, hydro, thermal, nuclear, and energy storage power sources are as follows: (1) Wind power operation constraints: (2) Photoelectric operation constraints: (3) Constraints on hydropower operation: a. State constraints of pumped storage power stations: in, The variable is a binary variable representing the energy storage state of a pumped storage power station. It is 1 when the power station is in the energy storage state and 0 otherwise. The variable is a binary variable representing the power generation status of a pumped storage power station. It is 1 when the power station is generating electricity and 0 otherwise. b. Power generation constraints and pumping power constraints of pumped storage power stations: Among them, P t H,in P represents the electricity consumed by a pumped-storage power station during time period t for pumping water. Hin,max P Hin,min These represent the upper and lower limits of the electricity consumption of a pumped storage power station in a single time period; P t H,out P represents the output power of a pumped-storage hydroelectric power station during time period t. Hout ,max P Hout,min These represent the upper and lower limits of the electricity output of a pumped storage power station during a single time period. c. Reservoir capacity constraints of pumped storage power stations: In min ≤V t ≤V max ; Among them, V t V represents the reservoir capacity of a pumped storage power station during time period t; max V min These represent the upper and lower limits of the reservoir capacity of a pumped storage power station; V t+1 η represents the reservoir capacity of the pumped storage power station at time t+1. in η out These are the pumping efficiency and power generation efficiency of the pumped storage power station's reservoir capacity, respectively. (4) Constraints on thermal power plant operation: a. Binary variable logical constraints for thermal power units: v i,t -w i,t =u i,t -u i,t-1 ; Among them, w i,t The shutdown status of thermal power unit i during time period t is 1 if the unit is shut down, and 0 otherwise. b. Initial state constraints: and i,t =and i,0 ,t∈[1,L,U i +L i ]; U i = [min[T,u] i,0 ( T on,i -T i,0 )]] + ; L i =[min[T,(1-u i，0 ()( T off，i +T i，0 )]] + ; Among them, u i,0 This represents the state of thermal power unit i in the initial period, i.e., the period before the start of the dispatch cycle, where "1" indicates operation and "0" indicates shutdown; U i L represents the time that thermal power unit i still needs to run at the initial moment. i This indicates the time that thermal power unit i still needs to be shut down at the initial moment; T is the total number of scheduling periods, [·] + This represents max(0,·); T on,i This represents the minimum start-up time of thermal power unit i; T off,i T represents the minimum shutdown time of thermal power unit i; i,0 This indicates the number of time periods during which thermal power unit i has been continuously started or shut down before the start of the scheduling cycle; c. Minimum start-up and shutdown constraints: d. New binary variable constraints: The scheduling cycle T of each generator unit and the time period before the scheduling cycle, totaling T+1 time periods, can be divided into T-M+2 intersecting sliding windows of size M; the leftmost end of the m-th sliding window is the m-th time period of the scheduling cycle, and the rightmost end is the m+M-1-th time period, where m∈[0,T-M+1]. Introducing new state variables This represents the start-up and shutdown status of thermal power unit i within the m-th window; if thermal power unit i starts up during any time period h in the m-th window, i.e., u h =1, when h>m, u h-1 =0, and continue running until the end of time period k, i.e., u k =1, when k < m + M - 1, u k+1 =0, then otherwise The specific constraints are as follows: e. Startup cost constraints: in, The cold start cost of thermal power unit i; T cold,i Let τ be the cold start time of thermal power unit i; if τ- T off,i - T cold,i ≤0 and [-T i,0 ] + <|τ- T off,i - T cold,i -1|+1, then f init,i,t =1, otherwise f init,i,t =0; f. Upper and lower limits of thermal power unit output: Based on the unit combination basic data, the upper / lower bounds of unit output are projected to 0 to 1, constructing a continuous variable of projected unit output, and establishing upper and lower limit constraints for unit output: Among them, P i T,up This represents the upward ramp rate of thermal power unit i; P represents the upward ramp rate of thermal power unit i after projection transformation; i T,down This represents the downward ramp rate of thermal power unit i; P represents the downward ramp rate of thermal power unit i after projection transformation; i T,start This represents the minimum output value of thermal power unit i when it is started up. P represents the minimum output value of thermal power unit i at startup after projection transformation; i T,shut This indicates the maximum output value of thermal power unit i when it is shut down; This represents the maximum output value of thermal power unit i after projection transformation when it is shut down; g. Climbing constraints for thermal power units: t∈[m+1,m+M-1]; a∈[1,tm]; (5) Nuclear power plant operation constraints: Divide the nuclear power safety peak shaving depth range into n equal parts k For the k-th level of nuclear power unit i, the peak-shaving depth is: Among them, P i N,max The minimum output allowed for nuclear power unit i; The nuclear power output of nuclear power unit i during the low-power phase at the k-th peak shaving depth is: u i,k,j,t Let be the power increase / decrease operating state variable of nuclear power unit i in the j-th state of the k-th peak shaving depth during time period t. There are 3 power increase / decrease states under each peak shaving depth, and the corresponding nuclear power output is: Nuclear power output can be linearly expressed as: Among them, h i,t Let l be the rated power operating state variable of nuclear power unit i during time period t; i,k,t For nuclear power unit i, the low-power operation state variable during time period t at peak shaving depth k; b. Constraints on runtime state variables: c. Coupling constraints of operating state variables when the power rise / fall time is 2 hours: h i,t+1 ≥l i,k,t-1 +u i,k,2,t -1; the i,k,t+1 ≥h i,t-1 +and i,k,2,t -1; d. Coupling constraints of operating state variables when the power rise / fall time is 3 hours: h i,t+1 ≥u i,k,1,t-1 +u i,k,3,t -1; the i,k,t+1 and i,k,3,t-1 +and i,k,1,t -1; in i,k,1,t+1 ≥h i,t-1 +in i,k,3,t -1; in i,k,3,t+1 ≥l i,k,t-1 +in i,k,1,t -1; e. Constraints on rated power and low-power operation time of nuclear power units: in, These are the minimum continuous operating time at full power and the minimum continuous operating time at low power for nuclear power unit i, respectively. (6) Operational constraints of battery energy storage power stations: a. Charge / discharge state constraints: Battery energy storage actually has three states of charge and discharge: charging, discharging, and standby. In any given time period t, battery energy storage can only be in one state of charge and discharge, namely: in c,t +in d,t ≤1 Among them, u c,t u d,t The variables representing the charge and discharge states of a battery energy storage power station are respectively: u during charging. c,t If u is 1, otherwise it is 0; when the battery discharges... d,t It is 1 if it is true, otherwise it is 0; b. Charge / discharge power constraints: 0≤P c,t ≤u c,t P c,max ; 0≤P d,t ≤u d,t P d,max ; Among them, P c,t P d,t P represents the charging power and discharging power of the battery energy storage power station during time period t, respectively. c,max P d,max These represent the maximum charging power and maximum discharging power of the battery energy storage power station, respectively. c. Energy constraint: During any scheduling period, the energy of the battery energy storage station should be within its allowable energy range; to ensure the sustainability of the battery energy storage station's scheduling, the stored energy should be restored to its initial value at the end of the scheduling cycle, i.e.: E b,t+1 =E b,t +n c P c,t Δt-P d,t Δt / h d ; AND b,min ≤E b,t ≤E b,max ; AND b,T =And b,0 ; Among them, E b,t η represents the remaining energy of the battery storage power station during time period t. c η d These represent the charging and discharging efficiency of the battery energy storage power station; Δt is the time length corresponding to the time period of the scheduling plan; E b,max E b,min These represent the upper and lower limits of the remaining energy of the battery storage power station, respectively; E b,T E represents the remaining energy of the battery storage power station at the end of the dispatch cycle. b,0 This indicates the initial remaining energy of the battery energy storage power station.

8. The method for establishing a concise and efficient multi-source supply model for wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, characterized in that... The specific rotational spare constraint is as follows: in, Let t be the system's required value for positive rotational reserve during time period t; This represents the system's negative rotational reserve requirement during time period t.

9. The method for establishing a concise and efficient multi-source supply guarantee model based on wind, solar, hydro, thermal, nuclear, and energy storage as described in claim 1, characterized in that... The power balance constraint is: Among them, P t D The system load power prediction value for time period t.

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