A medium- and long-term optimization scheduling method and system based on short-term water-solar complementary strategy

Abstract

The present invention discloses a medium- and long-term optimization scheduling method and system based on a short-term hydro-photovoltaic complementary strategy. The method includes: formulating a short-term hydro-photovoltaic complementary strategy based on historical operation data of a hydro-photovoltaic complementary power generation system, and extracting complementary power information in the short-term hydro-photovoltaic complementary process; further constructing a medium- and long-term hydro-photovoltaic complementary scheduling model; using an improved intelligent algorithm to solve the medium- and long-term hydro-photovoltaic complementary scheduling model, and the process introduces a boundary search optimization mechanism to globally optimize the medium- and long-term complementary scheduling boundary to obtain a medium- and long-term optimization scheduling method for a hydro-photovoltaic complementary power generation system. The present invention can further coordinate the spatiotemporal characteristics of hydropower, improve the storage and complementary efficiency of cascade reservoirs, effectively avoid the risk of power abandonment in the hydro-photovoltaic complementary process, and improve the power consumption efficiency of the medium- and long-term hydro-photovoltaic complementary power generation system. At the same time, it can smooth the random fluctuation amplitude of the photovoltaic short-term output process and improve the quality of power grid connection.

Description

Technical Field

[0001] The present invention relates to a hydro-photovoltaic complementary power generation technology, and in particular to a medium- and long-term optimization scheduling method and system based on a hydro-photovoltaic short-term complementary strategy. Background Art

[0002] Regarding the short-term complementary strategy of hydropower and photovoltaic power, the main application method is currently concentrated on the day-ahead dispatch of power generation, which is not of sufficient guiding significance for the optimization of medium- and long-term power generation dispatch, and it is impossible to formulate medium- and long-term hydropower power dispatch arrangements; in terms of the research on medium- and long-term complementary dispatch of hydropower and photovoltaic power, the main focus is on the optimization of power consumption, which does not fully consider the impact of short-term volatility of photovoltaic power on the medium- and long-term complementary dispatch process. First, there is a risk of power abandonment in the hydropower and photovoltaic complementary power generation system, resulting in power efficiency loss. The resulting abandonment of photovoltaic power or hydropower has an adverse effect on the stable operation of the system. Second, when the hydropower generation is low, it is difficult to smooth the random volatility of short-term photovoltaic output. The resulting power transmission fluctuations will have an adverse effect on the power system. Summary of the invention

[0003] Purpose of the invention: One purpose of the present invention is to provide a medium- and long-term optimization scheduling method based on the short-term hydro-photovoltaic complementary strategy, so as to improve the medium- and long-term hydro-photovoltaic complementary power generation system's power consumption capacity, avoid the impact of short-term water or light abandonment, and at the same time smooth the fluctuation amplitude of the sawtooth output during the short-term photovoltaic output process, and improve the power transmission and grid-connected quality of the hydro-photovoltaic complementary power generation system.

[0004] Another object of the present invention is to provide a medium- and long-term optimization scheduling system based on the short-term complementary strategy of water and light.

[0005] Technical solution: A medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy of the present invention comprises the following steps:

[0006] S1. Collect historical operation data of the hydro-photovoltaic complementary power generation system, randomly select one day, obtain the short-term hydropower output constraints, short-term photovoltaic output characteristics, and maximum capacity of the transmission channel of the hydro-photovoltaic complementary power generation system on that day, formulate a short-term hydro-photovoltaic complementary strategy, and extract complementary power information in the short-term hydro-photovoltaic complementary process. The hydro-photovoltaic complementary power generation system includes a hydropower station and a photovoltaic power station;

[0007] S2. Construct a medium- and long-term complementary dispatch model for hydropower and photovoltaic power generation, including: establishing the objective function of the long-term complementary dispatch of hydropower and photovoltaic power generation, establishing the objective function of the medium- and long-term complementary dispatch of hydropower and photovoltaic power generation, and establishing the constraints of long-term and medium- and long-term complementary dispatch; among which, the objective function of the long-term complementary dispatch of hydropower and photovoltaic power generation is the optimal power consumption of the hydropower and photovoltaic power generation system, and the objective function of the medium- and long-term complementary dispatch is consistent with the long-term complementary dispatch as a whole, except that the average monthly output of hydropower is further refined to the average daily output of hydropower within the month;

[0008] S3. Use the improved intelligent algorithm to solve the medium- and long-term hydro-photovoltaic complementary scheduling model and obtain the medium- and long-term optimal scheduling method of the hydro-photovoltaic complementary power generation system.

[0009] Furthermore, the complementary power information in the short-term hydropower-photovoltaic complementary process in step S1 includes: short-term guaranteed hydropower output, guaranteed photovoltaic power discard, short-term maximum hydropower output and short-term hydropower fluctuation smoothing power, specifically:

[0010] S11, Short-term guaranteed hydropower output Ph min The calculation formula is:

[0011]

[0012] in, To ensure the output of hydropower, T is the number of time periods in the short-term complementary scheduling cycle, and Δt is the calculation step length of the short-term complementary scheduling cycle;

[0013] S12, photovoltaic guaranteed discarded power Ps q The calculation formula is:

[0014]

[0015]

[0016] in, It is the short-term photovoltaic power output process; It is the space for absorbing the short-term output of photovoltaic power; N g is the maximum capacity of the transmission channel, t = 1…T;

[0017] S13, hydropower short-term smoothing fluctuations Ph s The calculation formula is:

[0018]

[0019] For the process of hydropower compensating photovoltaic power output, the mapping function relationship f1 is introduced and further expressed as:

[0020] Ph s =f1(ΔS)

[0021] Among them, ΔS is the PV output sawtooth depth standard;

[0022] S14, short-term maximum hydropower output Ph max The calculation formula is:

[0023]

[0024] Among them, ST t is the maximum hydropower output space in period t, N g is the maximum capacity of the transmission channel; The short-term output limit of hydropower. N y Estimated contribution to hydropower; N t For hydropower installed capacity.

[0025] Furthermore, in step S13, the hydropower output compensation process for photovoltaic The calculation method is:

[0026] S131. Extracting the short-term photovoltaic power output absorption space As a photovoltaic fluctuation compensation process Initial process, the process of using hydropower to compensate photovoltaic output Further calculation of photovoltaic fluctuation compensation output process Among them, the photovoltaic fluctuation compensation output process in the nth calculation The calculation formula is:

[0027] When n=1:

[0028] When n>1:

[0029] in, This is the process of hydropower compensating photovoltaic power output in the n-1th calculation;

[0030] S132. Define the period of time when there is sawtooth output in the short-term photovoltaic output process. The calculation formula is:

[0031] When there is satisfy and When t s =t, indicating the tth s There is a sawtooth output in the short-term photovoltaic output during the period, otherwise, there is no sawtooth output in the short-term photovoltaic output process;

[0032] S133. Determine the depth of photovoltaic sawtooth output during short-term photovoltaic output Specifically include:

[0033] First, the photovoltaic sawtooth output depth is defined as 0 in all time periods, and the calculation formula is:

[0034]

[0035] Then, if there exists t s , calculate the photovoltaic sawtooth output depth during this period, the calculation formula is:

[0036]

[0037] S134, when the PV sawtooth output depth exceeds the PV output sawtooth depth standard ΔS, the hydropower output is increased to compensate for the PV output. In the nth calculation, the hydropower output compensation process for the PV The calculation formula is:

[0038]

[0039] S135, perform loop calculation according to step S131 to step S134 until any All meet The short-term hydropower output process is completed to compensate the short-term photovoltaic output process, and the cycle calculation is completed. There are n cycles in total, and the hydropower to photovoltaic compensation output process is obtained. The calculation formula is:

[0040]

[0041] Further, step S2 includes:

[0042] S21. Long-term hydro-photovoltaic complementary scheduling takes one year as the scheduling cycle and one month as the calculation step. It adopts the average monthly output of hydropower and the hourly output of photovoltaic power generation, and aims to optimize the power consumption of the hydro-photovoltaic complementary power generation system. Specifically, it includes:

[0043]

[0044] Among them, E cq The power consumption of the hydro-photovoltaic complementary power generation system throughout the year under the long-term hydro-photovoltaic complementary scheduling; E m The amount of electricity consumed by the hydro-photovoltaic complementary power generation system in month m; Ph is the short-term hydropower fluctuation smoothing power in the mth month; m is the hydropower generation in month m; is the short-term guaranteed hydropower output in the mth month, m = 1…12; δ is the penalty factor;

[0045] S22. The medium- and long-term complementary scheduling of hydropower and photovoltaic power takes one year as the scheduling cycle and one day as the calculation step. The objective function of medium- and long-term complementary scheduling is consistent with that of long-term complementary scheduling. The difference is that the average monthly output of hydropower is taken as Further accurate to the average daily output of hydropower within the month Specifically include:

[0046]

[0047] Among them, E zq The electricity consumed by the hydro-photovoltaic complementary power generation system throughout the year under the medium- and long-term complementary scheduling of hydro-photovoltaic power generation; E m,d The power consumed by the hydro-photovoltaic complementary power generation system on the d day of the mth month; Ph is the short-term hydropower fluctuation smoothing power on the d day of the mth month; m,d is the hydroelectric power generation on the dth day of the mth month; The short-term guaranteed hydropower output on the d day of the mth month, m = 1…12, d = 1…D m , D m is the number of days in the mth month;

[0048] S23. Long-term and medium- and long-term complementary dispatching constraints include: output balance of cascade hydropower stations, water balance of cascade reservoirs, hydraulic connection of cascade reservoirs, water level limit of cascade reservoirs, flow limit of cascade power stations, and power generation limit of cascade hydropower stations.

[0049] Furthermore, in step S21, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system in the mth month is E m The calculation method is:

[0050] In long-term complementary scheduling, the hourly output process of photovoltaic power is obtained through a typical year Taking the water level process of cascade hydropower in the long-term operation as the decision variable, the average monthly output of hydropower is obtained through runoff calculation. Divide each month into D m According to the short-term complementary strategy of water and light in step S1, D m The complementary power information of the short-term complementary process is accumulated to obtain the short-term guaranteed output power of hydropower in that month. Photovoltaic guaranteed discarded electricity Short-term maximum output of hydropower Hydropower short-term smoothing of fluctuating electricity Information, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system this month is E m The calculation formula is:

[0051]

[0052] Where Δt1 is the long-term complementary calculation step, t = 1…T, m = 1…12, d = 1…D m , D m The number of days in the mth month.

[0053] Furthermore, in step S22, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system on the mth day of the month is E m,d The calculation method is:

[0054] In the medium- and long-term complementary dispatching, the hourly output process of photovoltaic power is obtained through a typical year. Taking the water level process of cascade hydropower in the long-term operation as the decision variable, the average daily output of hydropower is obtained through runoff calculation. According to the short-term hydro-solar complementary strategy in step S1, the complementary power information of each day is obtained: short-term guaranteed output power of hydropower Photovoltaic guaranteed discarded electricity Short-term maximum output of hydropower Hydropower short-term smoothing of fluctuating electricity Information, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system is E m,d The calculation formula is:

[0055]

[0056] Among them, Δt2 is the medium- and long-term complementary calculation step, t = 1...T, m = 1...12, d = 1...D m .

[0057] Furthermore, the medium- and long-term complementary scheduling constraint conditions in step S23 are specifically:

[0058] (1) Output balance of cascade hydropower stations;

[0059]

[0060] in, The hydropower output for the t period; is the average output of the ith hydropower station in the tth period, and L is the number of hydropower stations in the cascade;

[0061] (2) Water balance of cascade reservoirs;

[0062] V i,t+1 =V i,t +(RQ i,t -Q i,t -qs i,t )Δt

[0063] Among them, V i,t 、V i,t+1 are the initial and final reservoir storage capacities of the ith hydropower station in the tth period; RQ i,t , Q i,t 、qs i,t are the inflow, power generation and abandoned water flow of the i-th hydropower station in the t-th period respectively;

[0064] (3) Hydraulic connection of cascade reservoirs;

[0065] RQ i,t =Q i-1,t +qs i-1,t +QJ i,t

[0066] Among them, QJ i,t is the interval flow from the i-1th power station to the i-th power station;

[0067] (4) Water level restrictions of cascade reservoirs;

[0068] Zi,min ≤Z i ≤Z i,max

[0069] Among them, Z i,min , Z i,max are the lowest and highest operating water levels of the i-th hydropower station respectively;

[0070] (5) Cascade power station flow restrictions;

[0071] Q i,t,min ≤Q i,t +qs i,t ≤Q i,t,max

[0072] Among them, Q i,t,min , Q i,t,max are the lower and upper limits of the discharge flow of the i-th hydropower station in period t respectively;

[0073] (6) Restrictions on cascade hydroelectric power generation;

[0074]

[0075] in, is the average monthly output of hydropower in long-term complementary scheduling, Δt1 is the calculation step length of long-term complementary scheduling; is the average daily output of hydropower in medium- and long-term complementary dispatching, Δt2 is the calculation step length of medium- and long-term complementary dispatching, m = 1…12, d = 1…D m , D m The number of days in the mth month.

[0076] Furthermore, in step S3, a coupling algorithm framework based on PSO and DPSA is used to solve the medium- and long-term complementary scheduling model of water and light, which specifically includes:

[0077] S31, call in the PSO algorithm, set parameters, and perform the no-level medium- and long-term complementary scheduling calculation, n=1, o=1; no means that the o-th nested medium-term complementary scheduling in the n-level long-term complementary scheduling is being performed;

[0078] S32, the water level of the cascade reservoirs is used as the decision variable, each particle is initialized, and the initial population is generated; if n=1 and o=1, it indicates the initial calculation, and the annual system power consumption is calculated directly based on the particle water level information; if n>1 and o=1, it indicates that the medium-term complementary scheduling information for months 1 to n-1 has been determined, but the medium-term complementary scheduling calculation for the nth month has not been performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37; if n>1 and o>1, it indicates that the scheduling information for months 1 to n-1 has been determined, and the medium-term complementary scheduling calculation for the nth month is being performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37, and the water level at the end of the nth month and the system power consumption call the three sets of medium-term complementary scheduling information of step S36; the water levels for months n to 12 are randomly selected within the constraint range, and the long-term complementary scheduling is completed by PSO optimization. After comparison, the particle scheduling information with the largest system power consumption for the whole year is selected, and the scheduling information includes the water level for each month and the system power consumption;

[0079] S33, if o=1, it means that the mid-term complementary scheduling has not been carried out in month n, and the process goes to step S34; if o≥O, it means that the mid-term complementary scheduling in month n is completed, and the mid-term complementary scheduling mode in month n is determined, and the process goes to step S37; O is a constant, which indicates the threshold number of times of nested mid-term complementary scheduling;

[0080] S34, call in the DPSA algorithm, set parameters, and perform mid-term complementary scheduling calculation;

[0081] S35, extracting the scheduling information of n months in step S32, including the water levels at the beginning and end of the month;

[0082] S36, taking the water level at the end of month n as the initial water level, performing the oth boundary search, obtaining three water level nodes, combining the water level at the beginning of month n and the three groups of water level nodes at the end of month n, and obtaining three groups of medium-term complementary scheduling information for n months based on the above three water level nodes through DPSA optimization, including the system power consumption in the nth month and the corresponding water level information; o=o+1;

[0083] S37. Record and store the daily water level and system power consumption information for month n. If n<12, set n=n+1, o=1, and return to step S32 to perform the next level of medium- and long-term complementary scheduling calculation; if n=12, complete the medium- and long-term optimal scheduling.

[0084] Furthermore, in step S36, the mid-term and long-term boundary search optimization methods are specifically as follows:

[0085] At the initial water level of long-term complementary scheduling, the search step length is up and down. Take 1 search point and get the first water level boundary control set There are three water level control points. The o+1th up and down search step adopts the spatial search step based on dichotomy, which is expressed as:

[0086] when hour,

[0087] when hour,

[0088] when hour,

[0089] when hour,

[0090] in, is the oth upward search step length; is the oth downward search step length; is the o+1th upward search step length; is the o+1th downward search step length; Z n,o The initial water level for the oth search at the end of the nth month; Z n,o+1 The initial water level for the o+1th search at the end of the nth month.

[0091] A medium- and long-term optimization scheduling system based on a short-term water-solar complementary strategy of the present invention comprises:

[0092] Data collection module, used to collect historical operation data of the hydro-photovoltaic complementary power generation system;

[0093] The short-term hydro-photovoltaic complementary scheduling module randomly selects one day based on the historical operation data of the hydro-photovoltaic complementary power generation system, formulates a short-term hydro-photovoltaic complementary strategy, and extracts complementary power information during the short-term hydro-photovoltaic complementary process, including: short-term guaranteed hydropower output, guaranteed photovoltaic discarded power, short-term maximum hydropower output, and short-term hydropower fluctuation smoothing power;

[0094] The long-term hydro-solar complementary scheduling module further constructs a medium- and long-term hydro-solar complementary scheduling model based on the complementary power information output by the short-term hydro-solar complementary scheduling module;

[0095] The model solving module uses an improved intelligent algorithm to solve the medium- and long-term hydro-photovoltaic complementary scheduling model to obtain the medium- and long-term optimal scheduling method of the hydro-photovoltaic complementary power generation system.

[0096] Beneficial effects: Compared with the prior art, the method of the present invention analyzes the system power consumption, hydropower generation constraint range and photovoltaic guaranteed discarded power in each scheduling period through the short-term hydro-photovoltaic complementary strategy, and then introduces the above information into the medium- and long-term complementary scheduling process and solves it. The process adopts an improved intelligent algorithm, improves the solution efficiency through medium- and long-term nested calculations, and introduces a boundary search optimization mechanism to solve the local optimal problem in the medium- and long-term nested calculation process. The calculation results show that this method can further guide the transfer of hydropower generation within the medium- and long-term scheduling cycle, realize the reasonable spatial and temporal allocation of hydropower at the generation time nodes and power generation, avoid the abandonment of light or water in the complementary process, improve the power consumption level of the medium- and long-term hydro-photovoltaic complementary power generation system, and effectively smooth the random fluctuation amplitude of the photovoltaic output process in the short term, and improve the comprehensive benefits of the hydro-photovoltaic complementary power generation system and the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] Figure 1 is a flow chart of the method of the present invention;

[0098] Figure 2 This is a schematic diagram of the short-term complementary process between water and light;

[0099] Figure 3 It is an improved intelligent algorithm solution flow chart;

[0100] Figure 4 This is a schematic diagram of the water level process before and after the long-term complementarity between water and light;

[0101] Figure 5 This is a schematic diagram of hydropower generation before and after long-term complementarity between water and light;

[0102] Figure 6 It is a schematic diagram of the frontier search optimization process;

[0103] Figure 7 This is a schematic diagram of the medium- and long-term optimization scheduling of water and light. DETAILED DESCRIPTION

[0104] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0105] A water-photovoltaic complementary power generation system is selected for example analysis. The system consists of a distributed photovoltaic power station and six cascade hydropower stations. Through the form of a shared transmission channel for hydropower and photovoltaic power generation, a joint power generation system is formed; the maximum capacity of the transmission channel, the scale of hydropower installed capacity, and the scale of photovoltaic installed capacity are all 10 million kW. The basic information of the cascade hydropower station is shown in Table 1. Among them, reservoir ② has a strong control effect on the distribution of downstream cascade runoff. The water level process of reservoir ② is used below to show the scheduling plan of the cascade hydropower station. According to the photovoltaic output information of the multi-year runoff data of the address, in view of the stable characteristics of the total annual photovoltaic power generation, it is advisable to use the typical annual photovoltaic output process for example calculation.

[0106] Table 1 Scale parameters of cascade hydropower stations

[0107]

[0108]

[0109] like Figure 1 As shown, a medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy of the present invention comprises the following steps:

[0110] S1. Establish a short-term water-solar complementary strategy and extract the complementary power information in the short-term water-solar complementary process;

[0111] like Figure 2 As shown in the figure, the short-term hydro-photovoltaic complementary process takes the day as the scheduling cycle and the hour as the calculation step length; according to the historical operation data of the hydro-photovoltaic complementary power generation system, a day is randomly selected to obtain the short-term hydropower output constraints, photovoltaic short-term output characteristics, and maximum capacity of the transmission channel of the hydro-photovoltaic complementary power generation system on that day to formulate a short-term hydro-photovoltaic complementary strategy. The short-term hydro-photovoltaic complementary strategy is: the lower limit of the short-term hydropower output takes priority to occupy the transmission channel space, and the remaining space of the transmission channel first accommodates the photovoltaic short-term output process, and then compensates for the reduced hydropower; then extract the complementary power information in the short-term hydro-photovoltaic complementary process: ① hydropower short-term guaranteed output power; ② photovoltaic guaranteed discarded power; ③ hydropower short-term maximum output power; ④ hydropower short-term smoothing fluctuation power information, the specific process is as follows:

[0112] S11. The lower limit of short-term hydropower output is subject to the guaranteed hydropower output. The short-term guaranteed hydropower output is calculated as Ph. min , the calculation formula is:

[0113]

[0114] In the formula, To ensure the output of hydropower, T is the number of time periods in the short-term complementary scheduling cycle, and Δt is the calculation step length of the short-term complementary scheduling cycle.

[0115] S12. Calculate the guaranteed photovoltaic power discard Ps based on the photovoltaic short-term output consumption spaceq ;

[0116] Photovoltaic short-term output consumption space The calculation formula is:

[0117]

[0118] In the formula, is the photovoltaic short-term output process; N g is the maximum capacity of the transmission channel; In order to meet the short-term output lower limit of hydropower and the maximum capacity constraint of transmission channel, there is short-term output absorption space for photovoltaic power, t=1…T.

[0119] Photovoltaic guaranteed discarded power Ps q The calculation formula is:

[0120]

[0121] Where Ps q The amount of electricity discarded to ensure photovoltaic power generation refers to the amount of photovoltaic power generation that must be discarded during the short-term photovoltaic power generation process to prevent damage to hydropower output.

[0122] S13. Calculate the short-term hydropower fluctuation suppression power Ph based on the compensation mechanism of hydropower for photovoltaic short-term output process. s ;

[0123] There is random volatility in the short-term photovoltaic output process. Hydropower is used to compensate for the random fluctuations in the short-term photovoltaic output process. The hydropower compensation amount is: the short-term hydropower fluctuation amount; the compensation mechanism of the short-term hydropower output process for the short-term photovoltaic output process is: smoothing the sawtooth output process caused by the random volatility of photovoltaics, specifically including:

[0124] S131. Extracting the short-term photovoltaic power output absorption space As a photovoltaic fluctuation compensation process Initial process, the process of using hydropower to compensate photovoltaic output Further calculation of photovoltaic fluctuation compensation output process Among them, the photovoltaic fluctuation compensation output process in the nth calculation The calculation formula is:

[0125] When n=1:

[0126] When n>1:

[0127] In the formula, It is the photovoltaic fluctuation compensation output process in the nth calculation, where n is the number of cycles; The process of hydropower compensating photovoltaic power output in the n-1th calculation, the calculation of which is shown in step S134, t=1...T;

[0128] S132. Define the period of time when there is sawtooth output in the short-term photovoltaic output process. The calculation formula is:

[0129] When there is satisfy and When t s =t, indicating the tth s The photovoltaic short-term output has a sawtooth output during the period; otherwise, the photovoltaic short-term output process does not have a sawtooth output; S133, determining the photovoltaic sawtooth output depth during the photovoltaic short-term output process Specifically include:

[0130] First, the photovoltaic sawtooth output depth is defined as 0 in all time periods, and the calculation formula is:

[0131]

[0132] in, is the photovoltaic sawtooth output depth in the nth calculation;

[0133] Then, if there exists t s , calculate the photovoltaic sawtooth output depth during this period, the calculation formula is:

[0134]

[0135] S134, when the PV sawtooth output depth exceeds the PV output sawtooth depth standard ΔS, the hydropower output is increased to compensate for the PV output. In the nth calculation, the hydropower output compensation process for the PV The calculation formula is:

[0136]

[0137] S135, perform loop calculation according to step S131 to step S134 until any situation, The short-term hydropower output process is completed to compensate the short-term photovoltaic output process, and the cycle calculation is completed. There are n cycles in total, and the hydropower to photovoltaic compensation output process is obtained. The calculation formula is:

[0138]

[0139] According to the process of hydropower compensating photovoltaic power output Calculate the short-term hydropower fluctuation Ph s , the calculation formula is:

[0140]

[0141] The process of hydropower compensating photovoltaic power output Determined by the photovoltaic output sawtooth depth standard ΔS, it is further expressed by introducing the mapping function relationship f1:

[0142] Ph s =f1(ΔS)

[0143] In the formula, the smaller ΔS is, the more hydropower compensates for the short-term photovoltaic output process, and the more obvious the effect of smoothing the sawtooth fluctuation amplitude of the short-term photovoltaic output is. In the embodiment, ΔS is 100,000 kW.

[0144] S14. The upper limit of hydropower short-term output is subject to the expected hydropower output and hydropower installed capacity. In addition, since the hydropower-photovoltaic complementary power generation system involves the form of multi-energy complementary shared transmission channel, the maximum hydropower output space is subject to the upper limit of hydropower short-term output, the photovoltaic short-term output process, and the maximum capacity of the transmission channel. The maximum short-term hydropower output Ph is calculated. max , the calculation formula is:

[0145]

[0146]

[0147]

[0148] Where N y Estimated contribution to hydropower; N t for hydropower installed capacity; It is the short-term output limit of hydropower; ST t It is the maximum hydropower output space in the tth period, t=1…T.

[0149] S2. Based on the complementary power information in the short-term hydro-solar complementary process, a medium- and long-term hydro-solar complementary scheduling model is constructed;

[0150] S21. Long-term hydro-photovoltaic complementary scheduling takes one year as the scheduling cycle and one month as the calculation step. The goal is to achieve the optimal power consumption of the hydro-photovoltaic complementary power generation system. The calculation formula is:

[0151]

[0152] In the formula, E cq The power consumption of the hydro-photovoltaic complementary power generation system throughout the year under the long-term hydro-photovoltaic complementary scheduling; E m The amount of electricity consumed by the hydro-photovoltaic complementary power generation system in month m; Ph is the short-term hydropower fluctuation smoothing power in the mth month; m is the hydropower generation in month m; is the short-term guaranteed output of hydropower in the mth month; δ is the penalty factor, and in the embodiment, δ=10 6 , m=1…12; if the short-term hydropower fluctuation smoothing power in the mth month is greater than the hydropower generation in the current month minus the short-term guaranteed hydropower output, it means that the hydropower generation in the current month is not enough to compensate and smooth the sawtooth output caused by the random volatility of the short-term photovoltaic output in the current month while giving priority to the guaranteed hydropower output. This process is reflected by introducing a penalty function when calculating the objective function.

[0153] In long-term complementary scheduling, the hourly output process of photovoltaic power is obtained through a typical year Taking the water level process of cascade hydropower in the long-term operation as the decision variable, the average monthly output of hydropower is obtained through runoff calculation. Divide each month into D m A short-term complementary process, D m is the number of days in the mth month, and D is obtained according to the short-term complementary strategy of water and light. m The complementary power information of the short-term complementary process is accumulated to obtain the short-term guaranteed output power of hydropower in that month. Photovoltaic guaranteed discarded electricity Short-term maximum output of hydropower Hydropower short-term smoothing of fluctuating electricity Information, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system this month is E m The calculation formula is:

[0154]

[0155] Where Δt1 is the calculation step of long-term complementary scheduling, t = 1…T, m = 1…12, d = 1…D m , D m The number of days in the mth month.

[0156] S22. The medium- and long-term complementary scheduling of hydropower and photovoltaic power takes one year as the scheduling cycle and one day as the calculation step. The objective function of medium- and long-term complementary scheduling is consistent with that of long-term complementary scheduling. The difference is that the average monthly output of hydropower is taken as Further accurate to the average daily output of hydropower within the month Specifically include:

[0157]

[0158] In the formula, E zq The power consumption of the hydro-photovoltaic complementary power generation system throughout the year under the medium- and long-term hydro-photovoltaic complementary scheduling; E m,d The power consumed by the hydro-photovoltaic complementary power generation system on the d day of the mth month; Ph is the short-term hydropower fluctuation smoothing power on the d day of the mth month; m,d is the hydroelectric power generation on the dth day of the mth month; The short-term guaranteed hydropower output on the d day of the mth month, m = 1…12, d = 1…D m , D m is the number of days in the mth month; if the hydropower short-term fluctuation smoothing power on the dth day of the mth month is greater than the hydropower generation on that day minus the hydropower short-term guaranteed output power, it means that the hydropower generation on that day is not enough to compensate and smooth the sawtooth output caused by the random volatility of the photovoltaic short-term output on that day, while giving priority to the guaranteed output of hydropower. This process is also reflected by introducing a penalty function when calculating the objective function;

[0159] In the medium- and long-term complementary dispatching, the hourly output process of photovoltaic power is obtained through a typical year. Taking the water level process of cascade hydropower in the long-term operation as the decision variable, the average daily output of hydropower is obtained through runoff calculation. According to the short-term complementary strategy of hydropower and photovoltaic power, the complementary power information of the short-term complementary process of each day is obtained: the short-term guaranteed output power of hydropower Photovoltaic guaranteed discarded electricity Short-term maximum output of hydropower Hydropower short-term smoothing of fluctuating electricity Information, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system is E m,d The calculation formula is:

[0160]

[0161] Where Δt2 is the calculation step length of medium- and long-term complementary scheduling, t = 1…T, m = 1…12, d = 1…D m .

[0162] S23. The specific constraints of long-term and medium- and long-term complementary scheduling are as follows:

[0163] ① Output balance of cascade hydropower stations

[0164]

[0165] In the formula, is the hydropower output in period t; is the output of the ith hydropower station in the tth period, and L is the number of hydropower stations in the cascade;

[0166] ②Water balance of cascade reservoirs

[0167] V i,t+1 =V i,t +(RQ i,t -Q i,t -qs i,t )Δt

[0168] Where V i,t 、V i,t+1are the initial and final reservoir storage capacities of the ith hydropower station in the tth period; RQ i,t , Q i,t 、qs i,t are the inflow, power generation and abandoned water flow of the i-th hydropower station in the t-th period respectively;

[0169] ③Hydraulic connection of cascade reservoirs

[0170] RQ i,t =Q i-1,t +qs i-1,t +QJ i,t

[0171] In the formula, QJ i,t is the interval flow from the i-1th power station to the i-th power station;

[0172] ④ Water level restrictions of cascade reservoirs

[0173] Z i,min ≤Z i ≤Z i,max

[0174] In the formula, Z i is the operating water level of the i-th hydropower station, Z i,min , Z i,max are the lowest and highest operating water levels of the i-th hydropower station respectively;

[0175] ⑤ Cascade power station flow restrictions

[0176] Q i,t,min ≤Q i,t +qs i,t ≤Q i,t,max

[0177] In the formula, Q i,t,min , Q i,t,max are the lower and upper limits of the discharge flow of the i-th hydropower station in period t respectively;

[0178] ⑥ Limitation of cascade hydropower generation

[0179] or

[0180] In the formula, is the average monthly output of hydropower in long-term complementary scheduling, Δt1 is the calculation step length of long-term complementary scheduling; is the average daily output of hydropower in medium- and long-term complementary dispatching, Δt2 is the calculation step length of medium- and long-term complementary dispatching, m = 1…12, d = 1…D m , D mis the number of days in the mth month; the constraints on hydropower generation in each scheduling period are, on the one hand, to meet the minimum hydropower generation within the scheduling period to avoid damaging the guaranteed output of hydropower; on the other hand, to avoid excessive hydropower generation within the scheduling period, which will cause the total short-term hydropower generation to exceed the power output of the transmission channel, resulting in water abandonment or a large amount of solar abandonment.

[0181] S3. Use the improved intelligent algorithm to solve the medium- and long-term hydro-solar complementary scheduling model to obtain the medium- and long-term optimal scheduling method of the hydro-solar complementary power generation system;

[0182] According to the medium- and long-term complementary scheduling model of water and light, the optimization scheduling of cascade reservoirs has the problems of large computational complexity and easy to fall into local solutions. Combining the multi-time scale characteristics of the hierarchical scheduling model, a method combining the PSO algorithm and the DPSA algorithm is proposed to solve the model. This method uses PSO for long-term complementary scheduling and nests DPSA for medium-term complementary scheduling in a hybrid framework to achieve medium- and long-term optimal scheduling. It accelerates the optimization performance through the guidance of the short-term complementary strategy of water and light, and introduces the boundary search optimization mechanism to improve the globality. The details are as follows:

[0183] like Figure 3 As shown: An improved intelligent algorithm is used to solve the medium- and long-term optimization scheduling model of water-solar complementarity, as follows:

[0184] S31, call in the PSO algorithm, set parameters, and perform the no-level medium- and long-term complementary scheduling calculation, n=1, o=1; no means that the o-th nested medium-term complementary scheduling in the n-level long-term complementary scheduling is being performed;

[0185] S32, the water level of the cascade reservoirs is used as the decision variable, each particle is initialized, and the initial population is generated; if n=1 and o=1, it indicates the initial calculation, and the annual system power consumption is calculated directly based on the particle water level information; if n>1 and o=1, it indicates that the medium-term complementary scheduling information for months 1 to n-1 has been determined, but the medium-term complementary scheduling calculation for the nth month has not been performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37; if n>1 and o>1, it indicates that the scheduling information for months 1 to n-1 has been determined, and the medium-term complementary scheduling calculation for the nth month is being performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37, and the water level at the end of the nth month and the system power consumption call the three sets of medium-term complementary scheduling information of step S36; the water levels for months n to 12 are randomly selected within the constraint range, and the long-term complementary scheduling is completed by PSO optimization. After comparison, the particle scheduling information with the largest system power consumption for the whole year is selected, and the scheduling information includes the water level for each month and the system power consumption;

[0186] S33, if o=1, it means that the mid-term complementary scheduling has not been carried out in month n, and the process goes to step S34; if o≥O, it means that the mid-term complementary scheduling of month n is completed, and the mid-term complementary scheduling mode of month n is determined, and the process goes to step S37; O is a constant, which indicates the threshold number of times of nested mid-term complementary scheduling, and in the embodiment, O=5;

[0187] S34, call in the DPSA algorithm, set parameters, and perform mid-term complementary scheduling calculation;

[0188] S35, extracting the scheduling information of n months in step S32, including the water levels at the beginning and end of the month;

[0189] S36, taking the water level at the end of month n as the initial water level, performing the oth boundary search, obtaining three water level nodes, combining the water level at the beginning of month n and the three groups of water level nodes at the end of month n, and obtaining three groups of medium-term complementary scheduling information for n months based on the above three water level nodes through DPSA optimization, including the system power consumption in the nth month and the corresponding water level information; o=o+1;

[0190] S37. Record and store the daily water level and system power consumption information for month n. If n<12, set n=n+1, o=1, and return to step S32 to perform the next level of medium- and long-term complementary scheduling calculation; if n=12, complete the medium- and long-term optimal scheduling.

[0191] In order to reflect the long-term complementary effect of water and photovoltaic, the dispatching mode before the long-term complementarity of water and photovoltaic is introduced for comparison. The dispatching mode before the long-term complementarity of water and photovoltaic is: the cascade hydropower and photovoltaic power stations operate at their respective optimal power generation in the long-term complementary dispatching period, and carry out water and photovoltaic complementarity in the short term;

[0192] like Figures 4 to 5 As shown in the figure, the long-term hydro-solar complementary scheduling is completed through steps S31 to S32. Before the long-term hydro-solar complementary scheduling, the total hydropower generation in July and September exceeded the short-term maximum output of the hydropower by 1.088 billion kW·h. This power cannot be connected to the grid and can only be wasted in the form of abandoned water and abandoned light. On the one hand, the hydro-solar resources are not fully utilized; on the other hand, the stable operation of the complementary power generation system is adversely affected;

[0193] After the long-term complementarity between water and light, the hydropower generation in July and September decreased significantly, and the hydropower generation shifted to June and August. The hydropower generation in each month of the year did not exceed the short-term maximum output of hydropower. Compared with the dispatching method before long-term complementarity, the water level was lowered in July and September in advance, and the hydropower generation was relatively reduced by 360 million kW·h. However, the long-term complementarity process increased the system's power consumption by 720 million kW·h through reasonable allocation of hydropower generation in each month, and the gain reached 1.2%. This shows that the optimization of long-term complementary dispatching between water and light can significantly improve the power consumption level.

[0194] Through steps S31 to S32, long-term complementary scheduling information is obtained, including water level nodes at the beginning and end of the month. Here, the water level nodes at the beginning and end of June are 2815.5m and 2852.1m respectively;

[0195] like Figure 6 As shown: Through steps S35 to S36, the mid-term and long-term scheduling boundaries are searched and optimized, and the global optimization performance of the mid-term and long-term complementary nested scheduling is improved by autonomously changing the fixed water level boundaries in the long-term complementary scheduling, as follows:

[0196] At the initial water level of long-term complementary scheduling, the search step length is up and down. Take 1 search point and get the first (o=1) water level boundary control set There are three water level control points. To ensure the convergence of water level search, the o+1th up and down search step adopts the spatial search step based on dichotomy, which is expressed as:

[0197] when hour,

[0198] when hour,

[0199] when hour,

[0200] when hour,

[0201] in, is the oth upward search step length; is the oth downward search step length; is the o+1th upward search step length; is the o+1th downward search step length; Z n,o The initial water level for the oth search at the end of the nth month; Z n,o+1 The initial water level for the o+1th search at the end of the nth month.

[0202] The initial search step length is taken in the embodiment The water level boundary control set (2850.1, 2852.1, 2854.1) is obtained by searching 2m up and down according to the initial water level of 2852.1m at the end of June obtained by long-term complementary scheduling; the water level at the end of the month obtained by long-term complementary scheduling is called the initial water level;

[0203] According to the water level at the end of three months and the water level at the beginning of one month, three sets of dispatching information are obtained through the DPSA algorithm: the water level information at the end of June and the corresponding system power consumption. Here, the dispatching information obtained by optimizing the initial water level and the water level at the beginning of the month is called the initial solution;

[0204] Substitute the three groups of scheduling information into step S32. When PSO initializes particles, a total of 90 particles are set, with 30 particles randomly selected for each water level group. The fitness value in June: the monthly system power consumption is synchronized with the system power consumption corresponding to each group of water levels. The water levels of the following 11 months are randomly selected, and the annual hydro-photovoltaic power consumption is calculated. After completing the PSO optimization process, the 1-1 level operation is performed to obtain the optimal scheduling water level for each month of the year. Among them, the optimal water level at the end of June is 2854.1m. The second water level boundary control set (2853.1, 2854.1, 2856.1) is obtained. The same operation is performed to further determine that the optimal water level among the three groups of water levels is 2853.1m. The calculation results of the initial solution, the first optimization search, and the second optimization search are shown in Table 2. Compared with the initial solution, the system power consumption gain reaches 0.43%, indicating that the boundary search optimization can effectively break the boundary local optimal solution problem during medium- and long-term nested scheduling, and improve the globality of nested scheduling in different scheduling cycles.

[0205] Table 2 Optimal calculation of medium-term complementary 6-month search

[0206]

[0207] As shown in Table 2, although the hydropower generation in June decreased in the first optimization, it had a significant effect on raising the water level in the subsequent 11-month scheduling period. The second optimization lowered the water level at the end of June, indicating that the subsequent scheduling period could not use too much water according to the short-term maximum output of hydropower in each month, thereby lowering the water level. The optimization results show that the change of local information has a certain impact on the overall performance. The globality and optimization effect of the solution process are improved through the nested scheduling and boundary search optimization mechanism.

[0208] Through steps S31 to S37, the medium- and long-term optimization scheduling process of water and photovoltaic is obtained. In order to reflect the medium- and long-term complementary effect of water and photovoltaic, the scheduling method before the medium- and long-term complementarity of water and photovoltaic is introduced for comparison. The scheduling method before the medium- and long-term complementarity of water and photovoltaic is: the cascade hydropower and photovoltaic power stations operate at their respective optimal power generation in the medium- and long-term scheduling cycle, and water and photovoltaic complementarity is carried out in the short term.

[0209] like Figure 7 As shown in the figure, compared with before the long-term complementarity of hydropower and photovoltaic power, after the medium- and long-term complementarity of hydropower and photovoltaic power, the total amount of electricity absorbed by the system increased by 1.039 billion kW·h, with a gain of 1.77%. The reason for the gain is: before the medium- and long-term complementarity, due to the large inflow of water in July and September, the hydropower output increased, and the channel space occupied by hydropower generation increased. In this case, short-term complementarity cannot effectively balance the consumption of hydropower and photovoltaic power under the capacity limitation of the transmission channel. In this process, the daily hydropower generation exceeds the short-term maximum output of hydropower, that is, the power abandonment is generated, totaling 1.288 billion kW·h, resulting in a relatively serious power abandonment problem.

[0210] After the medium- and long-term complementary process, the short-term maximum output of hydropower on each day is used to guide the transfer of hydropower generation on each day, so as to achieve the reasonable spatial and temporal allocation of hydropower generation time and power generation. The daily hydropower generation throughout the year did not exceed the short-term maximum output of hydropower, which effectively avoided the abandonment of water or light, and improved the level of photovoltaic power consumption while ensuring the stable operation of the system. In addition, in this process, the hydropower generation on each day still met the short-term guaranteed output of hydropower, which can ensure the normal operation of hydropower. At the same time, by considering the short-term smoothing of hydropower fluctuations, the sawtooth output caused by the random fluctuations of photovoltaic short-term output was compensated and smoothed to a certain extent, thereby improving the comprehensive benefits of the hydropower-photovoltaic complementary power generation system and the power system.

[0211] A medium- and long-term optimization scheduling system based on a short-term water-solar complementary strategy of the present invention comprises:

[0212] Data collection module, used to collect historical operation data of the hydro-photovoltaic complementary power generation system;

[0213] The short-term hydro-photovoltaic complementary scheduling module randomly selects one day based on the historical operation data of the hydro-photovoltaic complementary power generation system, formulates a short-term hydro-photovoltaic complementary strategy, and extracts complementary power information during the short-term hydro-photovoltaic complementary process, including: short-term guaranteed hydropower output, guaranteed photovoltaic discarded power, short-term maximum hydropower output, and short-term hydropower fluctuation smoothing power;

[0214] The long-term hydro-solar complementary scheduling module further constructs a medium- and long-term hydro-solar complementary scheduling model based on the complementary power information output by the short-term hydro-solar complementary scheduling module;

[0215] The model solving module uses an improved intelligent algorithm to solve the medium- and long-term hydro-photovoltaic complementary scheduling model to obtain the medium- and long-term optimal scheduling method of the hydro-photovoltaic complementary power generation system.

[0216] In summary, the present invention provides a medium- and long-term optimization scheduling method based on the short-term complementary strategy of hydropower and photovoltaic power generation. First, according to the characteristics of hydropower and photovoltaic power generation and the capacity limitation requirements of the transmission channel, the complementary power information of the hydropower and photovoltaic complementary power generation system is analyzed through the short-term complementary strategy of hydropower and photovoltaic power generation; secondly, a medium- and long-term complementary scheduling model of hydropower and photovoltaic power generation is constructed; then, an improved intelligent algorithm is used to guide the medium- and long-term complementary scheduling of cascade reservoirs. This process introduces a boundary search optimization mechanism to globally optimize the medium- and long-term complementary scheduling boundary to obtain the medium- and long-term complementary scheduling boundary; the calculation results show that the method can further adjust the spatiotemporal characteristics of hydropower, improve the storage and complementary efficiency of cascade reservoirs, effectively avoid the risk of power abandonment in the process of hydropower and photovoltaic power generation, improve the power consumption efficiency of the medium- and long-term hydropower and photovoltaic complementary power generation system, and at the same time, it smoothes the random fluctuation amplitude of the photovoltaic short-term output process and improves the quality of power grid connection.

Claims

1. A medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy, characterized in that: The following steps are involved: S1. Collect historical operation data of the hydro-photovoltaic complementary power generation system, randomly select one day, obtain the short-term hydropower output constraints, photovoltaic short-term output characteristics, and maximum capacity of the transmission channel of the hydro-photovoltaic complementary power generation system on that day, formulate a short-term hydro-photovoltaic complementary strategy, and extract complementary power information in the short-term hydro-photovoltaic complementary process. The hydro-photovoltaic complementary power generation system includes a hydropower station and a photovoltaic power station; the complementary power information in the short-term hydro-photovoltaic complementary process includes: short-term guaranteed hydropower output, photovoltaic guaranteed discarded power, short-term maximum hydropower output, and short-term hydropower fluctuation smoothing power, specifically: S11, Short-term guaranteed hydropower output Ph min The calculation formula is: in, To ensure the output of hydropower, T is the number of time periods in the short-term complementary scheduling cycle, and △t is the calculation step length of the short-term complementary scheduling cycle; S12, photovoltaic guaranteed discarded power Ps q The calculation formula is: in, It is the short-term photovoltaic power output process; It is the short-term photovoltaic power consumption space; N g is the maximum capacity of the transmission channel, t = 1…T; S13, short-term hydropower smoothing of fluctuating electricity Ph s The calculation formula is: For the process of hydropower compensating photovoltaic power output, the mapping function relationship f1 is introduced and further expressed as: Ph s =f1(△S) Among them, △S is the PV output sawtooth depth standard; S14, short-term maximum hydropower output Ph max The calculation formula is: Among them, ST t is the maximum hydropower output space in period t, The short-term output limit of hydropower. N y Estimated contribution to hydropower; N t for hydropower installed capacity; S2. Construct a medium- and long-term complementary dispatch model for hydropower and photovoltaic power generation, including: establishing the objective function of long-term complementary dispatch for hydropower and photovoltaic power generation, establishing the objective function of medium- and long-term complementary dispatch for hydropower and photovoltaic power generation, and establishing the constraints for long-term and medium- and long-term complementary dispatch; among which, the objective function of long-term complementary dispatch for hydropower and photovoltaic power generation is the optimal power consumption of the hydropower and photovoltaic power generation system, and the objective function of medium- and long-term complementary dispatch is consistent with that of long-term complementary dispatch as a whole, except that the average monthly output of hydropower is further refined to the average daily output of hydropower within the month; including: S21. Long-term hydro-photovoltaic complementary scheduling takes one year as the scheduling cycle and one month as the calculation step. It adopts the average monthly output of hydropower and the hourly output of photovoltaic power generation, and aims to optimize the power consumption of the hydro-photovoltaic complementary power generation system. Specifically, it includes: Among them, E cq The power consumption of the hydro-photovoltaic complementary power generation system throughout the year under the long-term hydro-photovoltaic complementary scheduling; E m The amount of electricity consumed by the hydro-photovoltaic complementary power generation system in month m; Ph is the short-term hydropower fluctuation smoothing power in the mth month; m is the hydropower generation in month m; is the short-term guaranteed hydropower output in the mth month, where m is the month, m=1…12; δ is the penalty factor; S22. The medium- and long-term complementary scheduling of hydropower and photovoltaic power takes one year as the scheduling cycle and one day as the calculation step. The objective function of medium- and long-term complementary scheduling is consistent with that of long-term complementary scheduling. The difference is that the average monthly output of hydropower is taken as Further accurate to the average daily output of hydropower within the month Specifically include: Among them, E zq The electricity consumed by the hydro-photovoltaic complementary power generation system throughout the year under the medium- and long-term complementary scheduling of hydro-photovoltaic power generation; E m,d The power consumed by the hydro-photovoltaic complementary power generation system on the d day of the mth month; Ph is the short-term hydropower fluctuation smoothing power on the d day of the mth month; m,d is the hydroelectric power generation on the dth day of the mth month; The short-term guaranteed output of hydropower on the dth day of the mth month, d is the number of days, d=1…D m , D m is the number of days in the mth month; S23. Long-term and medium- and long-term complementary dispatching constraints include: output balance of cascade hydropower stations, water balance of cascade reservoirs, hydraulic connection of cascade reservoirs, water level limit of cascade reservoirs, flow limit of cascade power stations, and power generation limit of cascade hydropower stations; S3. Use the improved intelligent algorithm to solve the medium- and long-term hydro-solar complementary scheduling model and obtain the medium- and long-term optimal scheduling method of the hydro-solar complementary power generation system; use the coupled algorithm framework based on PSO and DPSA to solve the medium- and long-term hydro-solar complementary scheduling model, including: S31, call in the PSO algorithm, set parameters, and perform the no-level medium- and long-term complementary scheduling calculation, n=1, o=1; no means that the o-th nested medium-term complementary scheduling in the n-level long-term complementary scheduling is being performed; S32, the water level of the cascade reservoirs is used as the decision variable, each particle is initialized, and the initial population is generated; if n=1 and o=1, it indicates the initial calculation, and the annual system power consumption is calculated directly based on the particle water level information; if n>1 and o=1, it indicates that the medium-term complementary scheduling information for months 1 to n-1 has been determined, but the medium-term complementary scheduling calculation for the nth month has not been performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37; if n>1 and o>1, it indicates that the scheduling information for months 1 to n-1 has been determined, and the medium-term complementary scheduling calculation for the nth month is being performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37, and the water level at the end of the nth month and the system power consumption call the three sets of medium-term complementary scheduling information of step S36; the water levels for months n to 12 are randomly selected within the constraint range, and the long-term complementary scheduling is completed by PSO optimization. After comparison, the particle scheduling information with the largest system power consumption for the whole year is selected, and the scheduling information includes the water level for each month and the system power consumption; S33, if o=1, it means that the mid-term complementary scheduling has not been carried out in month n, and the process goes to step S34; if o≥O, it means that the mid-term complementary scheduling in month n is completed, and the mid-term complementary scheduling mode in month n is determined, and the process goes to step S37; O is a constant, which indicates the threshold number of times of nested mid-term complementary scheduling; S34, call in the DPSA algorithm, set parameters, and perform mid-term complementary scheduling calculation; S35, extracting the scheduling information of n months in step S32, including the water levels at the beginning and end of the month; S36, taking the water level at the end of month n as the initial water level, performing the oth boundary search, obtaining three water level nodes, combining the water level at the beginning of month n and the three groups of water level nodes at the end of month n, and obtaining three groups of medium-term complementary scheduling information for n months based on the above three water level nodes through DPSA optimization, including the system power consumption in the nth month and the corresponding water level information; o=o+1; S37. Record and store the daily water level and system power consumption information for month n. If n<12, set n=n+1, o=1, and return to step S32 to perform the next level of medium- and long-term complementary scheduling calculation; if n=12, complete the medium- and long-term optimal scheduling.

2. According to claim 1, a medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy is characterized in that: The process of hydropower compensating photovoltaic power output in step S13 The calculation method is: S131. Extracting the short-term photovoltaic power output absorption space As a photovoltaic fluctuation compensation process Initial process, the process of using hydropower to compensate photovoltaic output Further calculation of photovoltaic fluctuation compensation output process Among them, the photovoltaic fluctuation compensation output process in the nth calculation The calculation formula is: When n=1: When n>1: in, This is the process of hydropower compensating photovoltaic power output in the n-1th calculation; S132. Define the period of time when there is sawtooth output in the short-term photovoltaic output process. The calculation formula is: When there is satisfy and When t s =t, indicating the tth s There is a sawtooth output in the short-term photovoltaic output during the period, otherwise, there is no sawtooth output in the short-term photovoltaic output process; S133. Determine the depth of photovoltaic sawtooth output during short-term photovoltaic output Specifically include: First, the photovoltaic sawtooth output depth is defined as 0 in all time periods, and the calculation formula is: Then, if there exists t s , calculate the photovoltaic sawtooth output depth during this period, the calculation formula is: S134, when the PV sawtooth output depth exceeds the PV output sawtooth depth standard △S, the hydropower output is increased to compensate for the PV output. In the nth calculation, the hydropower output compensation process for the PV The calculation formula is: S135, perform loop calculation according to step S131 to step S134 until any All meet The short-term hydropower output process is completed to compensate the short-term photovoltaic output process, and the cycle calculation ends. There are n cycles in total, and the hydropower to photovoltaic compensation output process is obtained. The calculation formula is:

3. According to claim 1, a medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy is characterized in that: The amount of electricity consumed by the hydro-photovoltaic complementary power generation system in the mth month in step S21 is E m The calculation method is: In long-term complementary scheduling, the hourly output process of photovoltaic power is obtained through a typical year Taking the water level process of cascade hydropower in the long-term operation as the decision variable, the average monthly output of hydropower is obtained through runoff calculation. Divide each month into D m According to the short-term complementary strategy of water and light in step S1, D m The complementary power information of the short-term complementary process is accumulated to obtain the short-term guaranteed output power of hydropower in that month. Photovoltaic guaranteed discarded electricity Short-term maximum output of hydropower Hydropower short-term smoothing of fluctuating electricity Information, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system this month is E m The calculation formula is: Among them, △t1 is the calculation step size of long-term complementary scheduling.

4. According to claim 1, a medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy is characterized in that: In step S22, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system on the dth day of the mth month is E m,d The calculation method is: In the medium- and long-term complementary dispatching, the hourly output process of photovoltaic power is obtained through a typical year. Taking the water level process of cascade hydropower in the long-term operation as the decision variable, the average daily output of hydropower is obtained through runoff calculation. According to the short-term hydro-solar complementary strategy in step S1, the complementary power information of each day is obtained: short-term guaranteed output power of hydropower Photovoltaic guaranteed discarded electricity Short-term maximum output of hydropower Hydropower short-term smoothing of fluctuating electricity Information, the amount of electricity consumed by the hydro-photovoltaic complementary power generation system is E m,d The calculation formula is: Among them, △t2 is the calculation step size of medium- and long-term complementary scheduling.

5. According to claim 1, a medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy is characterized in that: The medium- and long-term complementary scheduling constraint conditions in step S23 are specifically: (1) Output balance of cascade hydropower stations; in, The hydropower output for the t period; is the output of the i-th hydropower station in the t-th period, and L is the number of hydropower stations in the cascade; (2) Water balance of cascade reservoirs; V i,t+1 =V i,t +(RQ i,t -Q i,t -qs i,t )△t Among them, V i,t 、V i,t+1 are the initial and final reservoir storage capacities of the ith hydropower station in the tth period; RQ i,t , Q i,t 、qs i,t are the inflow, power generation and abandoned water flow of the i-th hydropower station in the t-th period respectively; (3) Hydraulic connection of cascade reservoirs; RQ i,t =Q i-1,t +qs i-1,t +QJ i,t Among them, QJ i,t is the interval flow from the i-1th power station to the i-th power station; (4) Water level restrictions of cascade reservoirs; WITH i,min ≤Z i ≤Z i,max Among them, Z i,min , Z i,max are the lowest and highest operating water levels of the i-th hydropower station respectively; (5) Cascade power station flow restrictions; Q i,t,min ≤Q i,t +qs i,t ≤Q i,t,max Among them, Q i,t,min , Q i,t,max are the lower and upper limits of the discharge flow of the i-th hydropower station in period t respectively; (6) Restrictions on cascade hydroelectric power generation; or in, is the average monthly output of hydropower in long-term complementary scheduling, △t1 is the calculation step length of long-term complementary scheduling; is the average daily output of hydropower in medium- and long-term complementary scheduling, and △t2 is the calculation step length of medium- and long-term complementary scheduling.

6. According to claim 1, a medium- and long-term optimization scheduling method based on a short-term water-solar complementary strategy is characterized in that: In step S36, the mid-term and long-term boundary search optimization methods are specifically as follows: At the initial water level of long-term complementary scheduling, the search step length is up and down. Take 1 search point and get the first water level boundary control set There are three water level control points. The o+1th up and down search step adopts the spatial search step based on dichotomy, which is expressed as: when hour, when hour, when hour, when hour, in, is the oth upward search step length; is the oth downward search step length; is the o+1th upward search step length; is the o+1th downward search step length; Z n,o The initial water level for the oth search at the end of the nth month; Z n,o+1 The initial water level for the o+1th search at the end of the nth month.

7. A medium- and long-term optimization scheduling system based on short-term water-solar complementary strategy, characterized in that: include: Data collection module, used to collect historical operation data of the hydro-photovoltaic complementary power generation system; The short-term hydro-photovoltaic complementary scheduling module randomly selects one day based on the historical operation data of the hydro-photovoltaic complementary power generation system, formulates a short-term hydro-photovoltaic complementary strategy, and extracts the complementary power information in the short-term hydro-photovoltaic complementary process, including: short-term guaranteed hydropower output, guaranteed photovoltaic discarded power, short-term maximum hydropower output, and short-term hydropower fluctuation suppression power; specifically: S11, Short-term guaranteed hydropower output Ph min The calculation formula is: in, To ensure the output of hydropower, T is the number of time periods in the short-term complementary scheduling cycle, and △t is the calculation step length of the short-term complementary scheduling cycle; S12, photovoltaic guaranteed discarded power Ps q The calculation formula is: in, It is the short-term photovoltaic power output process; It is the short-term photovoltaic power consumption space; N g is the maximum capacity of the transmission channel, t = 1…T; S13, short-term hydropower smoothing of fluctuating electricity Ph s The calculation formula is: N t hs For the process of hydropower compensating photovoltaic power output, the mapping function relationship f1 is introduced and further expressed as: Ph s =f1(△S) Among them, △S is the PV output sawtooth depth standard; S14, short-term maximum hydropower output Ph max The calculation formula is: Among them, ST t is the maximum hydropower output space in period t, The short-term output limit of hydropower. N y Estimated contribution to hydropower; N t for hydropower installed capacity; The long-term hydro-solar complementary scheduling module further constructs a medium- and long-term hydro-solar complementary scheduling model based on the complementary power information output by the short-term hydro-solar complementary scheduling module; it includes: S21. Long-term hydro-photovoltaic complementary scheduling takes one year as the scheduling cycle and one month as the calculation step. It adopts the average monthly output of hydropower and the hourly output of photovoltaic power generation, and aims to optimize the power consumption of the hydro-photovoltaic complementary power generation system. Specifically, it includes: Among them, E cq The power consumption of the hydro-photovoltaic complementary power generation system throughout the year under the long-term hydro-photovoltaic complementary scheduling; E m The amount of electricity consumed by the hydro-photovoltaic complementary power generation system in month m; Ph is the short-term hydropower fluctuation smoothing power in the mth month; m is the hydropower generation in month m; is the short-term guaranteed hydropower output in the mth month, where m is the month, m=1…12; δ is the penalty factor; S22. The medium- and long-term complementary scheduling of hydropower and photovoltaic power takes one year as the scheduling cycle and one day as the calculation step. The objective function of medium- and long-term complementary scheduling is consistent with that of long-term complementary scheduling. The difference is that the average monthly output of hydropower is taken as Further accurate to the average daily output of hydropower within the month Specifically include: Among them, E zq The electricity consumed by the hydro-photovoltaic complementary power generation system throughout the year under the medium- and long-term complementary scheduling of hydro-photovoltaic power generation; E m,d The power consumed by the hydro-photovoltaic complementary power generation system on the d day of the mth month; Ph is the short-term hydropower fluctuation smoothing power on the d day of the mth month; m,d is the hydroelectric power generation on the dth day of the mth month; The short-term guaranteed output of hydropower on the dth day of the mth month, d is the number of days, d=1…D m , D m is the number of days in the mth month; S23. Long-term and medium- and long-term complementary dispatching constraints include: output balance of cascade hydropower stations, water balance of cascade reservoirs, hydraulic connection of cascade reservoirs, water level limit of cascade reservoirs, flow limit of cascade power stations, and power generation limit of cascade hydropower stations; The model solving module uses an improved intelligent algorithm to solve the medium- and long-term hydro-solar complementary scheduling model to obtain the medium- and long-term optimal scheduling method of the hydro-solar complementary power generation system; the coupling algorithm framework based on PSO and DPSA is used to solve the medium- and long-term hydro-solar complementary scheduling model, including: S31, call in the PSO algorithm, set parameters, and perform the no-level medium- and long-term complementary scheduling calculation, n=1, o=1; no means that the o-th nested medium-term complementary scheduling in the n-level long-term complementary scheduling is being performed; S32, the water level of the cascade reservoirs is used as the decision variable, each particle is initialized, and the initial population is generated; if n=1 and o=1, it indicates the initial calculation, and the annual system power consumption is calculated directly based on the particle water level information; if n>1 and o=1, it indicates that the medium-term complementary scheduling information for months 1 to n-1 has been determined, but the medium-term complementary scheduling calculation for the nth month has not been performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37; if n>1 and o>1, it indicates that the scheduling information for months 1 to n-1 has been determined, and the medium-term complementary scheduling calculation for the nth month is being performed, wherein the water level for months 1 to n-1 and the system power consumption are replaced by the information of step S37, and the water level at the end of the nth month and the system power consumption call the three sets of medium-term complementary scheduling information of step S36; the water levels for months n to 12 are randomly selected within the constraint range, and the long-term complementary scheduling is completed by PSO optimization. After comparison, the particle scheduling information with the largest system power consumption for the whole year is selected, and the scheduling information includes the water level for each month and the system power consumption; S33, if o=1, it means that the mid-term complementary scheduling has not been carried out in month n, and the process goes to step S34; if o≥O, it means that the mid-term complementary scheduling in month n is completed, and the mid-term complementary scheduling mode in month n is determined, and the process goes to step S37; O is a constant, which indicates the threshold number of times of nested mid-term complementary scheduling; S34, call in the DPSA algorithm, set parameters, and perform mid-term complementary scheduling calculation; S35, extracting the scheduling information of n months in step S32, including the water levels at the beginning and end of the month; S36, taking the water level at the end of month n as the initial water level, performing the oth boundary search, obtaining three water level nodes, combining the water level at the beginning of month n and the three groups of water level nodes at the end of month n, and obtaining three groups of medium-term complementary scheduling information for n months based on the above three water level nodes through DPSA optimization, including the system power consumption in the nth month and the corresponding water level information; o=o+1; S37. Record and store the daily water level and system power consumption information for month n. If n<12, set n=n+1, o=1, and return to step S32 to perform the next level of medium- and long-term complementary scheduling calculation; if n=12, complete the medium- and long-term optimal scheduling.

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