A short-term risk scheduling method for water, wind and solar power taking into account the utilization of water resources in the remaining period

Abstract

The present invention discloses a short-term risk scheduling method for water, wind and solar power taking into account the utilization of water resources in the remaining period. The method constructs a response function between the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period. Under the condition of uncertainty in wind and photovoltaic output, the method considers the risk of power abandonment and load loss and the peak-shaving target of the power grid in the short-term operation of the water, wind and solar power complementary system, while taking into account the stability demand of the system output, and constructs a day-ahead risk scheduling model for the water, wind and solar power complementary system taking into account the comprehensive utilization of water resources in the remaining period. The model is used to prepare the day-ahead power generation plan of the complementary system, which can realize the coupling of medium- and long-term scheduling and short-term scheduling of the water, wind and solar power complementary system. At the same time, it can also take into account the comprehensive utilization of water resources in the basin and the consumption of new energy, reduce unnecessary energy waste of the power generation system, improve the consumption of new energy while ensuring economy, and effectively improve the management and operation level of the water, wind and solar power complementary system in the basin.

Description

Technical Field

[0001] The present invention relates to the field of power system optimization and dispatching, and in particular to a short-term risk dispatching method for water, wind and solar power taking into account the utilization of water resources in the remaining period. Background Art

[0002] In recent years, new energy power generation technologies, mainly wind power and photovoltaic power generation, have developed rapidly around the world. However, wind and solar power outputs have strong volatility and forecast uncertainty, making them difficult to directly connect to the grid for consumption. Increasing the grid penetration rate of new energy sources such as wind power and photovoltaic power requires providing additional flexible resources to cope with the volatility and uncertainty of wind and solar power outputs. Making full use of the flexible regulation capacity of hydropower and implementing the multi-energy complementarity of water, wind and solar power is one of the effective ways to achieve efficient consumption of new energy.

[0003] Connecting new energy sources such as wind and solar to cascade hydropower in the basin has changed the original operation mode of cascade hydropower. Existing research has conducted a lot of research on the real-time economic operation of water-wind-solar complementary systems, the preparation of short-term power generation plans, and medium- and long-term dispatching and operation rules, and developed a theoretical system for water-wind-solar multi-energy complementary dispatching. In addition, the operation characteristics of water-wind-solar complementary operations are mainly reflected in the short term, and the demand for comprehensive utilization of water resources in the basin usually needs to be met by cascade reservoirs in medium- and long-term dispatching and operation. The existing technology aims at the short-term and medium- and long-term coupling problems of water-wind-solar complementary systems. On the basis of extracting short-term power abandonment characteristics and hydropower output response functions, it constructs a medium- and long-term dispatching model that takes into account short-term operation characteristics, realizes the long- and short-term nesting of the dispatching model, and formulates medium- and long-term dispatching rules.

[0004] However, in actual operation, even if a medium- and long-term scheduling plan is formulated to adapt to the short-term consumption of new energy, due to the uncertainty of wind and solar output forecasts, the water level drawdown of the short-term scheduling of the water-wind-solar complementary system is often difficult to meet expectations, that is, the residual period benefits of short-term scheduling are difficult to be effectively guaranteed. Summary of the invention

[0005] In order to solve the above-mentioned problems existing in the prior art, the present invention provides a short-term risk scheduling method for water, wind and solar power that takes into account the utilization of water resources in the remaining period, so as to solve the technical problems existing in the existing short-term scheduling technology of water, wind and solar power that the water level drawdown is difficult to reach the expected level and the remaining period benefits of short-term scheduling are difficult to guarantee.

[0006] In order to achieve the above object, the technical solution of the embodiment of the present invention is:

[0007] A first aspect of the present invention provides a short-term risk scheduling method for water, wind and solar power taking into account the utilization of water resources in the remaining period, the method comprising:

[0008] With the goal of maximizing the guaranteed power generation rate of the water-wind-solar complementary system and minimizing the water shortage index downstream of the reservoir, a medium- and long-term optimization scheduling model for water-wind-solar multi-energy complementarity is constructed; wherein, the first objective function for maximizing the guaranteed power generation rate of the water-wind-solar complementary system is: , the second objective function with the minimum water shortage index downstream of the reservoir is: , where: represents the power generation guarantee rate of the water-wind-solar hybrid system; t and T represent the mid- and long-term dispatch period number and the total dispatch period respectively; , , They represent the actual average output of hydropower, the average output of photovoltaic power stations and the average output of wind farms in period t respectively; It indicates the guaranteed output of the water-wind-solar complementary system; It indicates the number of times the net output of the hydro-wind-solar hybrid system is higher than the guaranteed output during the entire dispatch period; It represents the water shortage index downstream of the reservoir; and They represent the downstream water demand and discharge flow in period t respectively;

[0009] Solve the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity to obtain the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity;

[0010] Based on the medium- and long-term dispatching function of water-wind-solar multi-energy complementarity, a medium- and long-term simulation model of water-wind-solar multi-energy complementarity is constructed;

[0011] The obtained long series of runoff, wind power output, and photovoltaic output are used as inputs of the medium- and long-term simulation model of water-wind-solar multi-energy complementarity, and the medium- and long-term long series of simulation dispatching and operation processes of water-wind-solar complementarity are simulated;

[0012] Based on the medium- and long-term series of simulated dispatching and operation processes of the water-wind-solar complementary system, a response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period is constructed; the response function includes a first response function between the power generation guarantee rate of the water-wind-solar complementary system and the water level of the Longtou Reservoir at the end of the month and the natural average flow in the next year, and a second response function between the water shortage index downstream of the reservoir and the water level of the Longtou Reservoir at the end of the month and the natural average flow in the next year;

[0013] Based on the first response function and the second response function, under the condition of uncertainty of wind and photovoltaic output, considering the risks of power abandonment and load loss in short-term operation of the hydro-wind-solar complementary system and the peak-shaving target of the power grid, while taking into account the stability demand of the system output, a day-ahead risk scheduling model of the hydro-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period is constructed, and the model is used to prepare the day-ahead power generation plan of the hydro-wind-solar complementary system.

[0014] A second aspect of the present invention provides a short-term risk scheduling device for water, wind and solar power taking into account the utilization of water resources in the remaining period, the device comprising:

[0015] A construction module is used to construct a medium- and long-term optimization scheduling model for water-wind-solar multi-energy complementarity with the goal of maximizing the power generation guarantee rate of the water-wind-solar complementary system and minimizing the water shortage index downstream of the reservoir; wherein the first objective function for the highest power generation guarantee rate of the water-wind-solar complementary system is: , the second objective function with the minimum water shortage index downstream of the reservoir is: , where: is the power generation guarantee rate of the complementary system; t and T represent the mid- and long-term dispatch period number and the total dispatch period respectively; , , They represent the actual average output of hydropower, the average output of photovoltaic power stations and the average output of wind farms in period t respectively; It indicates the guaranteed output of the water-wind-solar complementary system; It indicates the number of times the net output of the complementary system is higher than the guaranteed output during the entire dispatch period; It represents the water shortage index downstream of the reservoir; and They represent the downstream water demand and discharge flow in period t respectively;

[0016] A solution module, used to solve the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity, and obtain the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity;

[0017] The construction module is also used to construct a medium- and long-term simulation model of water-wind-solar multi-energy complementarity based on the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity;

[0018] A simulation module is used to use the obtained long series of runoff, wind power output, and photovoltaic output as inputs of the medium- and long-term simulation model of water-wind-solar multi-energy complementarity, and simulate the medium- and long-term long series simulation scheduling operation process of water-wind-solar complementarity;

[0019] The construction module is also used to construct a response function between the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period based on the medium- and long-term series of simulated scheduling and operation processes of the water-wind-solar complementary system; the response function includes a first response function between the power generation guarantee rate of the water-wind-solar complementary system and the water level of the Longtou Reservoir at the end of the month and the natural average flow in the next year, and a second response function between the water shortage index downstream of the reservoir and the water level of the Longtou Reservoir at the end of the month and the natural average flow in the next year;

[0020] The construction module is also used to build a day-ahead risk scheduling model for the water-wind-solar complementary system that takes into account the comprehensive utilization of water resources in the remaining period, based on the first response function and the second response function, under the condition of uncertainty in wind and photovoltaic output, taking into account the risks of power abandonment and load loss in the short-term operation of the water-wind-solar complementary system and the peak-shaving target of the power grid, while taking into account the stability requirements of the system output, and using the model to prepare a day-ahead power generation plan for the water-wind-solar complementary system.

[0021] In some embodiments, the solution module is further used to determine the basic form and parameters of the medium- and long-term dispatching rules of water-wind-solar multi-energy complementarity, and use an implicit random optimization method to solve the medium- and long-term optimization dispatching model of water-wind-solar multi-energy complementarity to extract the medium- and long-term dispatching rules of water-wind-solar multi-energy complementarity;

[0022] Construct an implicit stochastic optimization model for the parameters of the medium- and long-term dispatching rules for the complementary energy of water, wind and solar power;

[0023] The preset multi-objective cuckoo algorithm is used to solve the implicit stochastic optimization model based on the basic form to obtain the medium- and long-term scheduling function of the water-wind-solar multi-energy complementarity.

[0024] In some embodiments, the medium- and long-term series simulation scheduling operation process of the water-wind-solar complementary system includes: the discharge flow of the cascade reservoirs, the drawdown water level of the cascade reservoirs at the end of the month, the power generation head and the output of the cascade hydropower station; the construction module is also used to determine the drawdown water level of the Dragon Head Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system and the water shortage index downstream of the reservoir based on the discharge flow of the cascade reservoirs, the drawdown water level of the cascade reservoirs at the end of the month, the power generation head and the output of the cascade hydropower station;

[0025] The preset local weighted scatter point smoothing regression method is adopted to fit the first response function and the second response function respectively based on the water level drawdown of Longtou Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system and the water shortage index downstream of the reservoir.

[0026] In some embodiments, the day-ahead risk scheduling model for the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period includes the following objective function:

[0027] The comprehensive risk rate of power generation plan is the lowest:

[0028] ,

[0029] ,

[0030] ,

[0031] The peak-to-valley difference of the grid residual load is minimal:

[0032] ,

[0033] The expected power generation rate of the hydro-wind-solar complementary system in the remaining period is the highest:

[0034] ,

[0035] The expected minimum water shortage index downstream of the reservoir during the remaining period is:

[0036] ,

[0037] Where: I represents the number of the representative scenario; T represents the number of scheduling periods; and They represent the power abandonment rate of wind and solar energy and the system load loss rate of the hydro-wind-solar hybrid system in period t under the representative scenario i; It represents the difference between the total system output and the power generation plan during period t; and They represent the wind power output and photovoltaic output of the representative scenario i respectively; , and They represent the wind power output, photovoltaic output and their occurrence probability of the representative scenario i respectively; represents the actual output of the cascade hydropower station in period t under the representative scenario i; It represents the day-ahead power generation plan of the hydro-wind-solar hybrid system in period t; Indicates the grid load; represents the grid load during period t; represents the drawdown water level of Longtou Reservoir at the end of the dispatch period under the representative scenario i; represents the first response function under the representative scenario i; represents the second response function under the representative scenario i.

[0038] In some embodiments, the construction module is also used to construct the constraint conditions of the medium- and long-term optimization scheduling model of water, wind and solar multi-energy complementarity, including:

[0039] (1) Water balance constraints:

[0040] ,

[0041] (2) Storage capacity constraints:

[0042] ,

[0043] (3) Downflow flow constraints:

[0044] ,

[0045] (4) Hydropower station output constraints:

[0046] ,

[0047] (5) Reservoir characteristic constraints:

[0048] ,

[0049] (6) Parameter optimization interval constraints:

[0050] ,

[0051] Where: Indicates that the scheduling period is long; represents the storage capacity of the mth hydropower station at the end of the tth period; represents the storage capacity of the mth hydropower station at the end of the t+1th period; and They represent the inflow and outflow of the mth hydropower station in the tth period respectively; and They represent the lower and upper limits of the storage capacity of the mth hydropower station respectively; and They represent the minimum and maximum discharge flow of the mth hydropower station respectively; represents the discharge flow of the hydropower station in the mth period of time; and They represent the lower and upper limits of the output of the mth hydropower station respectively; represents the output of the hydropower station in the mth period of time; represents the water level at the end of the tth period at the mth hydropower station; represents the tailwater level of the mth hydropower station at the end of the tth period; , It represents the fitting parameters of the linear dispatch function in the day-ahead risk dispatch model of the hydro-wind-solar hybrid system; , represents the fitted parameters of the linear scheduling function in the implicit stochastic optimization model.

[0052] In some embodiments, the constraints of the day-ahead risk scheduling model of the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period include: (1) to (5) of the constraints of the medium- and long-term optimal scheduling model of the water-wind-solar multi-energy complementarity, and the following constraints:

[0053] Output stability constraints of water-wind-solar hybrid system:

[0054] ,

[0055] Where: represents the output power of the sth stable operation period in the transmission curve of the hydro-wind-solar hybrid system; s represents the number of the stable operation period of the transmission curve; tc represents the time point when the daily transmission plan power changes; tc s Indicates the end point time of the sth stable operation period; tc s-1 represents the end point of the s-1th stable operation period; the value range of t is (0, 24); based on this, the derived day-ahead power generation plan can be expressed as:

[0056] ,

[0057] Where: S is the number of steps of the transmission curve, that is, the number of stable operation periods; It represents the system day-ahead power generation plan in the first stable operation period;

[0058] The upper and lower limits of the output of the water-wind-solar hybrid system are as follows:

[0059] ,

[0060] Where: and They represent the upper and lower limits of the output of the water-wind-solar hybrid system respectively; It represents the day-ahead power generation plan of the hydro-wind-solar hybrid system during period t.

[0061] In some embodiments, the device further comprises: a calculation module for step S1: The fourth objective function of determining the day-ahead power generation plan of the wind-solar hybrid system and tc is used to minimize the peak-to-valley difference of the remaining load of the power grid; S2: Calculate the load process of cascade hydropower under the representative scenario i ; S3: The load distribution process of cascade hydropower stations under representative scenario i is determined by combining the discrimination coefficient and relative water demand rate, and the actual output process of cascade hydropower under representative scenario i is determined by considering various constraints on the operation of cascade reservoirs and hydropower stations. ; S4: loop S2 and S3 until the actual output process of cascade hydropower under all representative scenarios is obtained; S5: based on the load distribution results under each representative scenario and the corresponding probability of each scenario, calculate the third objective function with the minimum comprehensive risk rate of the power generation plan, the fifth objective function with the highest expected power generation guarantee rate of the water-wind-solar complementary system in the remaining period, and the sixth objective function with the minimum expected water shortage index downstream of the reservoir in the remaining period; S6: guided by the above objective function values, iterative calculation is performed through the multi-objective optimization algorithm until the preset number of times is reached, and the model solution set is output to obtain the day-ahead power generation plan of the water-wind-solar complementary system that takes into account the comprehensive utilization of water resources in the remaining period.

[0062] An embodiment of the present invention provides an electronic device, including: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement the above-mentioned water, wind and solar short-term risk scheduling method that takes into account the utilization of water resources in the remaining period.

[0063] An embodiment of the present invention provides a computer-readable storage medium that stores executable instructions for causing a processor to execute the executable instructions to implement the above-mentioned water, wind and solar short-term risk scheduling method that takes into account the utilization of water resources in the remaining period.

[0064] The method provided by the present invention, on the one hand, by taking the highest power generation guarantee rate of the water-wind-solar complementary system and the minimum water shortage index downstream of the reservoir as the goal, constructs a medium- and long-term implicit random optimization scheduling model for water-wind-solar multi-energy complementarity, extracts scheduling rules, and can achieve optimization of the medium- and long-term operation of multi-energy complementarity; on the other hand, by constructing a medium- and long-term simulation model of the water-wind-solar multi-energy complementarity system, it can achieve medium- and long-term efficient and refined scheduling simulation of water-wind-solar multi-energy complementarity; thirdly, through the constructed response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period, under the condition of uncertainty of wind and photovoltaic output, the risks of power abandonment and load loss in the short-term operation of the water-wind-solar complementary system and the peak-shaving target of the power grid are considered, while taking into account the stability demand of the system output, to construct a model considering the residual A day-ahead risk scheduling model for a water-wind-solar complementary system with comprehensive utilization of water resources in the retention period is developed. The model is used to prepare a day-ahead power generation plan for the complementary system, which can take into account the medium- and long-term scheduling benefits in the short-term scheduling of water-wind-solar complementary systems, thereby achieving the coupled coordination of medium- and long-term and short-term scheduling of the water-wind-solar complementary systems. At the same time, it can also take into account the comprehensive utilization of water resources in the basin and the consumption of new energy, reduce unnecessary energy waste in the power generation system, improve the consumption of new energy while ensuring economy, and effectively improve the management and operation level of the water-wind-solar complementary systems in the basin. It solves the problems faced in the current short-term scheduling of water-wind-solar multi-energy complementarity, that is, the water level drawdown is difficult to reach the expected level and the residual period benefits are difficult to guarantee, and realizes the long- and short-term coupled coordination of the water-wind-solar complementary systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 2 is a schematic diagram of the structure of a water-wind-solar short-term risk scheduling system that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention;

[0066] Figure 2 It is a flow chart of a method for short-term risk scheduling of water, wind and solar power taking into account the utilization of water resources in the remaining period provided by an embodiment of the present invention;

[0067] Figure 3 It is a flow chart of another method for short-term risk scheduling of water, wind and solar power taking into account the utilization of water resources in the remaining period provided by an embodiment of the present invention;

[0068] Figure 4It is a schematic diagram of the composition structure of a water-wind-solar short-term risk scheduling device that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention;

[0069] Figure 5 It is a schematic diagram of the composition structure of a water, wind and solar short-term risk scheduling device that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present invention. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present invention.

[0071] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict. Unless otherwise defined, all technical and scientific terms used in the embodiments of the present invention have the same meaning as those commonly understood by those skilled in the art to which the embodiments of the present invention pertain. The terms used in the embodiments of the present invention are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

[0072] The following describes an exemplary application of a short-term risk scheduling device for water, wind and light that takes into account the utilization of water resources in the remaining period according to an embodiment of the present invention. The short-term risk scheduling device for water, wind and light that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention can be implemented as a terminal or a server. In one implementation, the short-term risk scheduling device for water, wind and light that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention can be implemented as various types of terminals such as laptops, tablet computers, desktop computers, and mobile devices; in another implementation, the short-term risk scheduling device for water, wind and light that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention can also be implemented as a server, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks (CDNs), and big data and artificial intelligence platforms. The terminal and the server can be directly or indirectly connected by wired or wireless communication, which is not limited in the embodiment of the present invention. Below, an exemplary application of the water, wind and solar short-term risk scheduling device that takes into account the utilization of water resources in the remaining period as a server will be described.

[0073] See also Figure 1 , Figure 1 1 is a schematic diagram of the structure of a water-wind-solar short-term risk scheduling system 10 that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention. In order to realize the scheduling of the complementary short-term risks of water, wind and solar that take into account the comprehensive utilization of water resources in the remaining period, an embodiment of the present invention can provide a water-wind-solar short-term risk scheduling platform that takes into account the utilization of water resources in the remaining period, and the water-wind-solar short-term risk scheduling platform that takes into account the utilization of water resources in the remaining period can be implemented as a water-wind-solar short-term risk scheduling application that takes into account the utilization of water resources in the remaining period. The water-wind-solar short-term risk scheduling system 10 that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention includes a terminal 110, a network 120 and a server 130, wherein the server 130 is a server of the water-wind-solar short-term risk scheduling application that takes into account the utilization of water resources in the remaining period. The server 130 can constitute a water-wind-solar short-term risk scheduling device that takes into account the utilization of water resources in the remaining period of the present invention. The terminal 110 is connected to the server 130 through the network 120, and the network 120 can be a wide area network or a local area network, or a combination of the two.

[0074] In some embodiments, please refer to Figure 1 When the hydropower-photovoltaic complementary system is short-term dispatched, the terminal 110 sends the hydropower-wind-solar complementary short-term risk dispatching task to the server 130 through the network 120. The server 130 responds to the hydropower-wind-solar complementary short-term risk dispatching task initiated by the terminal 110, and takes the highest power generation guarantee rate of the hydropower-wind-solar complementary system and the lowest water shortage index downstream of the reservoir as the goal, and constructs a medium- and long-term optimal dispatching model for hydropower-wind-solar multi-energy complementarity; solves the medium- and long-term optimal dispatching model for hydropower-wind-solar multi-energy complementarity, and obtains the medium- and long-term dispatching function for hydropower-wind-solar multi-energy complementarity; constructs a medium- and long-term simulation model for hydropower-wind-solar multi-energy complementarity based on the medium- and long-term dispatching function for hydropower-wind-solar multi-energy complementarity; takes the long series of runoff, wind power output, and photovoltaic output as the medium- and long-term optimal dispatching function for hydropower-wind-solar multi-energy complementarity The simulation model is input to simulate the medium- and long-term series of simulated dispatching and operation processes of water-wind-solar complementarity; based on the medium- and long-term series of simulated dispatching and operation processes of water-wind-solar complementarity, a response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period is constructed; based on the first response function and the second response function, under the conditions of uncertainty of wind and photovoltaic output, the risks of power abandonment and load loss in the short-term operation of the water-wind-solar complementarity system and the peak load regulation target of the power grid are considered, while taking into account the stability requirements of the system output, a day-ahead risk dispatching model of the water-wind-solar complementarity system considering the comprehensive utilization of water resources in the remaining period is constructed, and the model is used to prepare the day-ahead power generation plan of the water-wind-solar complementarity system to obtain the short-term risk dispatching result of the water-wind-solar complementarity system. After obtaining the short-term risk dispatching result of the water-wind-solar complementarity system, the server 130 sends the short-term risk dispatching result of the water-wind-solar complementarity system to the terminal 110 through the network 120.

[0075] The embodiment of the present invention provides a short-term risk scheduling method for water, wind and solar power taking into account the utilization of water resources in the remaining period, see Figure 2 , Figure 2 This is a flow chart of a method for short-term risk scheduling of water, wind and solar power taking into account the utilization of water resources in the remaining period provided by an embodiment of the present invention. Figure 2 The steps shown are explained.

[0076] Step S210, with the goal of maximizing the power generation guarantee rate of the water-wind-solar complementary system and minimizing the water shortage index downstream of the reservoir, construct a medium- and long-term optimization scheduling model for the water-wind-solar multi-energy complementarity.

[0077] In some embodiments, the highest guaranteed power generation rate of the water-wind-solar hybrid system means that within a specific time frame (such as one year, one quarter or one month, etc.), the system's ability to stably and reliably provide power supply reaches the highest level. This highest level is not only reflected in the maximization of power generation, but also in the stability and predictability of the power generation process. The first objective function of the highest guaranteed power generation rate of the water-wind-solar hybrid system is:

[0078] (1),

[0079] Where: Indicates the power generation guarantee rate of the water-wind-solar complementary system; represents the guaranteed output of the water-wind-solar hybrid system; t and T represent the mid- and long-term dispatch period number and the total dispatch period respectively; , , They represent the actual average output of hydropower, the average output of photovoltaic power stations and the average output of wind farms in period t respectively; It indicates the number of times the net output of the complementary system is higher than the guaranteed output during the entire dispatch period.

[0080] In some embodiments, the minimum water shortage index downstream of the reservoir means that within a specific time period (such as one year, one quarter or one month, etc.), through reasonable reservoir scheduling and management measures, the water shortage level in the downstream area of ​​the reservoir reaches the lowest level. This level is quantified by calculating the water shortage index. The smaller the water shortage index, the lower the water shortage level and the more balanced the water supply and demand situation. The second objective function of the water shortage index downstream of the reservoir is:

[0081] (2),

[0082] Where: represents the water shortage index downstream of the reservoir; t and T represent the mid- and long-term dispatch period number and the total dispatch period respectively; and They represent the downstream water demand and discharge flow in period t respectively.

[0083] Step S220, solving the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity to obtain the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity.

[0084] In some embodiments, an implicit random scheduling method is used to extract the medium- and long-term scheduling rules for water, wind and solar multi-energy complementarity, and determine the basic form and parameters of the scheduling rules, such as linear scheduling functions, nonlinear scheduling functions, etc. Taking the linear scheduling function as an example, its basic form is as follows:

[0085] (3),

[0086] Where: k and K represent the number and total number of scheduling functions respectively; and Respectively represent the input variables and output variables of the scheduling function; and Represents the parameters of the linear scheduling function.

[0087] In this application, available energy is used as the input variable, and the output variables can be selected from the storage capacity at the end of the month, hydropower output, downstream flow, etc. The basic form of the scheduling function for each month is determined on a monthly time scale, and the idea of ​​parameter-simulation-optimization is adopted to construct an implicit stochastic optimization model for fitting the scheduling rule parameters. The multi-objective Cuckoo Search Algorithm (MOCS) is used to solve the model to obtain the optimal medium- and long-term scheduling function for water, wind, and solar multi-energy complementarity.

[0088] Step S230: constructing a medium- and long-term simulation model of water-wind-solar multi-energy complementarity based on the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity.

[0089] In some embodiments, the medium- and long-term dispatching function of water-wind-solar multi-energy complementarity is a dispatching rule, under which the medium- and long-term operation process of water-wind-solar multi-energy complementarity is simulated, that is, a medium- and long-term simulation model of water-wind-solar multi-energy complementarity is constructed. In other words, the core of constructing the medium- and long-term simulation model of water-wind-solar multi-energy complementarity is the medium- and long-term dispatching function of water-wind-solar multi-energy complementarity.

[0090] Step S240, using the obtained long series of runoff, wind power output, and photovoltaic output as inputs of the medium- and long-term simulation model of water-wind-solar multi-energy complementarity, and simulating the medium- and long-term long series simulation scheduling operation process of water-wind-solar complementarity.

[0091] In some embodiments, based on the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity obtained in each month in the above step S230, a medium- and long-term simulation model of water-wind-solar multi-energy complementarity is established, and the obtained long series runoff, wind power output, and photovoltaic output are used as the input of the medium- and long-term simulation model of water-wind-solar multi-energy complementarity. The long series scheduling process of water-wind-solar multi-energy complementarity is simulated to obtain the operation process of each reservoir in each month, including the discharge flow of cascade reservoirs, the water level drawdown of cascade reservoirs at the end of the month, the power generation head of each month, the output of cascade hydropower stations of each month, etc.

[0092] Step S250, based on the medium- and long-term series of simulated scheduling and operation processes of the water-wind-solar complementarity, a response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period is constructed.

[0093] It should be noted that the response function includes the first response function between the power generation guarantee rate of the water-wind-solar complementary system and the water level drawdown of the Longtou Reservoir at the end of the month and the natural average flow in the next year, and the second response function between the water shortage index downstream of the reservoir and the water level drawdown of the Longtou Reservoir at the end of the month and the natural average flow in the next year.

[0094] In some embodiments, the medium- and long-term operation of cascade reservoirs is related to the natural water supply situation. The power generation and water supply guarantee rate in the flood season are usually higher than those in the dry season. In addition, due to the significant seasonal characteristics of runoff, the operation cycle of large cascade hydropower station reservoirs in the basin is usually 1 year. Therefore, at a certain moment, the reservoir scheduling operation in the next year is also related to the water storage situation of the leading reservoir with current regulation ability. The seasonal characteristics of runoff are significant. In the field of water situation forecasting, the forecast period is at least 1 year on a monthly scale. Therefore, in practical applications, the water supply situation in the next year can often be quantitatively judged and known. Based on this, the present invention intends to construct a response function of the current state of cascade reservoirs and the comprehensive utilization target of water resources in the remaining period. Here, the remaining period refers to the scheduling cycle of the next year based on the end of the current period.

[0095] First, based on the medium- and long-term simulation scheduling process of water-wind-solar complementary operation, the water level of Longtou Reservoir at the end of each month was counted. 、The average natural flow in the next year , and the guaranteed power generation rate of the water-wind-solar complementary system in the next year and water shortage index downstream of the reservoir , where: represents the natural water flow of Longtou Reservoir during period t, Indicates the duration of period t.

[0096] In some embodiments, the Locally Weighted Scatterplot Smoothing Regression (LOWESS) method is used to fit the functional relationship between the power generation guarantee rate of the water-wind-solar hybrid system, the water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year, as well as the functional relationship between the water shortage index downstream of the reservoir, the water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year, which are respectively recorded as and .

[0097] In practical applications, LOWESS is a non-parametric regression method. Different from traditional linear regression and polynomial regression, LOWESS performs fitting calculations on the local area of ​​each sample point and smoothes the results. It can effectively adapt to different sample distributions and eliminate the influence of outliers. The specific process is as follows:

[0098] (1) Calculate the distance D from the sample point to the specified point:

[0099] (4),

[0100] (2) Set the window range rspan and calculate the weight values ​​of all sample points within the window width:

[0101] (5),

[0102] (3) Using the above sample points for weighted regression, the loss function can be expressed as:

[0103] (6),

[0104] (4) Repeat the above steps until the fitting surface is obtained using local weighted scattered point smoothing regression.

[0105] Where: X, Y are the coordinates of the specified point; , is the coordinate of the sample point; is the weight value of sample point n; is the distance from sample point n to the specified point; Indicates the farthest distance between the sample point in the window and the specified point; N is the number of sample points in the window; is the weight matrix of all sample points in the window; and They are the function value matrix and position matrix of all sample points in the window respectively; is a parameter matrix, which is usually estimated by the least squares method.

[0106] Step S260, based on the first response function and the second response function, under the condition of uncertainty of wind and photovoltaic output, considering the risks of power abandonment and load loss in short-term operation of the water-wind-solar complementary system and the peak-shaving target of the power grid, while taking into account the stability demand of the system output, construct a day-ahead risk scheduling model for the water-wind-solar complementary system that considers the comprehensive utilization of water resources in the remaining period, and use the model to prepare the day-ahead power generation plan for the water-wind-solar complementary system.

[0107] In some embodiments, the functional relationship between the power generation guarantee rate of the water-wind-solar complementary system and the water shortage index downstream of the reservoir obtained in step S250 above, the drawdown water level of the Longtou Reservoir at the end of the month, and the natural average flow in the next year and Under the condition of uncertainty in the output of wind and solar energy, the risks of power abandonment and load loss in the short-term operation of the water-wind-solar complementary system and the peak-shaving target of the power grid are considered, while taking into account the stability demand of the system output, a day-ahead risk scheduling model for the water-wind-solar complementary system is constructed considering the comprehensive utilization of water resources in the remaining period.

[0108] The method provided by the present invention, on the one hand, by taking the highest power generation guarantee rate of the water-wind-solar complementary system and the minimum water shortage index downstream of the reservoir as the goal, constructs a medium- and long-term implicit random optimization scheduling model for water-wind-solar multi-energy complementarity, extracts scheduling rules, and can achieve optimization of the medium- and long-term operation of multi-energy complementarity; on the other hand, by constructing a medium- and long-term simulation model of the water-wind-solar multi-energy complementarity system, it can achieve medium- and long-term efficient and refined scheduling simulation of water-wind-solar multi-energy complementarity; thirdly, through the constructed response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period, under the condition of uncertainty of wind and photovoltaic output, the risks of power abandonment and load loss in the short-term operation of the water-wind-solar complementary system and the peak-shaving target of the power grid are considered, while taking into account the stability demand of the system output, to construct a model considering the residual A day-ahead risk scheduling model for a water-wind-solar complementary system with comprehensive utilization of water resources in the retention period is developed. The model is used to prepare a day-ahead power generation plan for the complementary system, which can take into account the medium- and long-term scheduling benefits in the short-term scheduling of water-wind-solar complementary systems, thereby achieving the coupled coordination of medium- and long-term and short-term scheduling of the water-wind-solar complementary systems. At the same time, it can also take into account the comprehensive utilization of water resources in the basin and the consumption of new energy, reduce unnecessary energy waste in the power generation system, improve the consumption of new energy while ensuring economy, and effectively improve the management and operation level of the water-wind-solar complementary systems in the basin. It solves the problems faced in the current short-term scheduling of water-wind-solar multi-energy complementarity, that is, the water level drawdown is difficult to reach the expected level and the residual period benefits are difficult to guarantee, and realizes the long- and short-term coupled coordination of the water-wind-solar complementary systems.

[0109] In some embodiments, the above step S220 can be implemented by following the steps S221 to S223:

[0110] Step S221, determine the basic form and parameters of the medium- and long-term scheduling rules for water-wind-solar multi-energy complementarity, use the implicit stochastic optimization method to solve the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity, and extract the medium- and long-term scheduling rules for water-wind-solar multi-energy complementarity.

[0111] Step S222, construct an implicit stochastic optimization model for the parameters of the medium- and long-term dispatching rules for the water-wind-solar multi-energy complementarity.

[0112] Step S223, using a preset multi-objective cuckoo algorithm, based on the basic form, solve the implicit stochastic optimization model to obtain the medium- and long-term scheduling function of the water-wind-solar multi-energy complementarity.

[0113] In some embodiments, the medium- and long-term series simulation scheduling operation process of water-wind-solar complementary includes: discharge flow of cascade reservoirs, water level drawdown of cascade reservoirs at the end of the month, power generation head and output of cascade hydropower stations; the above step S250 can be implemented by the following steps S251 to S252:

[0114] Step S251, based on the discharge flow of the cascade reservoirs, the water level drawdown of the cascade reservoirs at the end of the month, the generating head and the output of the cascade hydropower stations, determine the water level drawdown of the Longtou Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system and the water shortage index downstream of the reservoir.

[0115] Step S252, using a preset local weighted scatter point smoothing regression method, based on the drawdown water level of the Longtou Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system and the water shortage index downstream of the reservoir, respectively fit the first response function and the second response function.

[0116] In some embodiments, a representative scenario set of wind and solar output and its probability are obtained through scenario simulation and scenario reduction methods as the input of the day-ahead power generation plan compilation model to effectively characterize the uncertainty of wind and solar output. In addition, in order to achieve dimensionality reduction of the day-ahead power generation plan compilation model and ensure the stability of system output, a two-dimensional coding strategy is used to describe the total output of the water-wind-solar complementary system, that is, the power generation plan of the water-wind-solar complementary system is used. The time point tc at which the power generation plan changes is used as the model decision variable, and the objective function is as follows:

[0117] (1) The comprehensive risk rate of power generation plan is the lowest:

[0118] (7),

[0119] (8),

[0120] (9),

[0121] (2) The peak-to-valley difference of the grid residual load is minimal:

[0122] (10),

[0123] (3) The expected power generation rate of the hydro-wind-solar complementary system in the remaining period is the highest:

[0124] (11),

[0125] (4) The expected minimum water shortage index downstream of the reservoir during the remaining period:

[0126] (12),

[0127] Where: I represents the number of the representative scenario; T represents the number of scheduling periods; and They represent the power abandonment rate of wind and solar energy and the system load loss rate of the hydro-wind-solar hybrid system in period t under the representative scenario i; It represents the difference between the total system output and the power generation plan during period t; and They represent the wind power output and photovoltaic output of the representative scenario i respectively; , and They represent the wind power output, photovoltaic output and their occurrence probability of the representative scenario i respectively; represents the actual output of the cascade hydropower station in period t under the representative scenario i; It represents the day-ahead power generation plan of the hydro-wind-solar hybrid system in period t; Indicates the grid load; represents the grid load during period t; represents the drawdown water level of Longtou Reservoir at the end of the dispatch period under the representative scenario i; represents the first response function under the representative scenario i; represents the second response function under the representative scenario i.

[0128] In some embodiments, the constraints of the medium- and long-term optimization scheduling model for the water, wind and solar multi-energy complementarity include:

[0129] (1) Water balance constraints:

[0130] (13),

[0131] (2) Storage capacity constraints:

[0132] (14),

[0133] (3) Downflow flow constraints:

[0134] (15),

[0135] (4) Hydropower station output constraints:

[0136] (16),

[0137] (5) Reservoir characteristic constraints:

[0138] (17),

[0139] (6) Parameter optimization interval constraints:

[0140] (18),

[0141] Where: Indicates that the scheduling period is long; represents the storage capacity of the mth hydropower station at the end of the tth period; represents the storage capacity of the mth hydropower station at the end of the t+1th period; and They represent the inflow and outflow of the mth hydropower station in the tth period respectively; and They represent the lower and upper limits of the storage capacity of the mth hydropower station respectively; and They represent the minimum and maximum discharge flow of the mth hydropower station respectively; represents the discharge flow of the hydropower station in the mth period of time; and They represent the lower and upper limits of the output of the mth hydropower station respectively; represents the output of the hydropower station in the mth period of time; represents the water level at the end of the tth period at the mth hydropower station; represents the tailwater level of the mth hydropower station at the end of the tth period; , It represents the fitting parameters of the linear dispatch function in the day-ahead risk dispatch model of the hydro-wind-solar hybrid system; , represents the fitted parameters of the linear scheduling function in the implicit stochastic optimization model.

[0142] In some embodiments, the constraints of the day-ahead risk scheduling model of the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period include: (1) to (5) of the constraints of the medium- and long-term optimal scheduling model of the water-wind-solar multi-energy complementarity, and the following constraints:

[0143] Output stability constraints of water-wind-solar hybrid system:

[0144] (19),

[0145] Where: represents the output power of the sth stable operation period in the transmission curve of the hydro-wind-solar hybrid system; s represents the number of the stable operation period of the transmission curve; tc represents the time point when the daily transmission plan power changes; tc s Indicates the end point time of the sth stable operation period; tc s-1 represents the end point of the s-1th stable operation period; the value range of t is (0, 24); based on this, the derived day-ahead power generation plan can be expressed as:

[0146] (20),

[0147] Where: S is the number of steps of the transmission curve, that is, the number of stable operation periods; It represents the system day-ahead power generation plan in the first stable operation period;

[0148] The upper and lower limits of the output of the water-wind-solar hybrid system are as follows:

[0149] (twenty one),

[0150] Where: and They represent the upper and lower limits of the output of the water-wind-solar hybrid system respectively; It represents the day-ahead power generation plan of the hydro-wind-solar hybrid system during period t.

[0151] In some embodiments, the day-ahead risk scheduling model of the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period can still be solved by the multi-objective cuckoo algorithm (MOCS), and the model solving process is as follows:

[0152] S1: by decision variables The day-ahead power generation plan of the hydro-wind-solar hybrid system is derived from tc. At this time, the fourth objective function can be calculated: the peak-to-valley difference of the grid residual load is minimized;

[0153] S2: Under the representative scenario i, the load process that the cascade hydropower should bear is calculated ;

[0154] S3: The load distribution process of cascade hydropower stations under representative scenario i is determined by combining the discriminant coefficient and the relative water demand rate. In this process, various constraints on the operation of cascade reservoirs and hydropower stations are considered to obtain the actual output process of cascade hydropower under representative scenario i. ;

[0155] S4: loop S2 and S3 until the actual output process of cascade hydropower under all representative scenarios is obtained;

[0156] S5: Based on the load distribution results under each representative scenario and the corresponding probability of each scenario, the third objective function is calculated respectively: the minimum comprehensive risk rate of the power generation plan, the fifth objective function: the maximum expected power generation guarantee rate of the water-wind-solar complementary system in the remaining period, and the sixth objective function: the minimum expected water shortage index downstream of the reservoir in the remaining period;

[0157] S6: Guided by the objective function value, iterative calculation is performed through the multi-objective optimization algorithm until the preset number of times is reached, and the model solution set is output to obtain the day-ahead power generation plan of the water-wind-solar complementary system that takes into account the comprehensive utilization of water resources in the remaining period.

[0158] The technical flow chart of the short-term risk scheduling method of the water-wind-solar complementary system taking into account the comprehensive utilization of water resources in the remaining period proposed by the present invention is as follows Figure 3 shown.

[0159] Figure 4 is a schematic diagram of the composition structure of a water-wind-solar short-term risk scheduling device that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention, such as Figure 4 As shown, the short-term risk scheduling device 400 for water, wind and solar power taking into account the utilization of water resources in the remaining period includes: a construction module 401, which is used to construct a medium- and long-term optimization scheduling model for water, wind and solar power multi-energy complementarity with the highest power generation guarantee rate of the water, wind and solar power complementary system and the minimum water shortage index downstream of the reservoir as the goal; wherein the first objective function for the highest power generation guarantee rate of the water, wind and solar power complementary system is: , the second objective function with the minimum water shortage index downstream of the reservoir is: , where: represents the power generation guarantee rate of the water-wind-solar hybrid system; t and T represent the mid- and long-term dispatch period number and the total dispatch period respectively; , , They represent the actual average output of hydropower, the average output of photovoltaic power stations and the average output of wind farms in period t respectively; It indicates the guaranteed output of the water-wind-solar complementary system; It indicates the number of times the net output of the complementary system is higher than the guaranteed output during the entire dispatch period; It represents the water shortage index downstream of the reservoir; and They respectively represent the water demand and downstream flow in the downstream during time period t; the solution module 402 is used to solve the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity to obtain the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity; the construction module 10 is also used to construct a medium- and long-term simulation model of water-wind-solar multi-energy complementarity based on the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity; the simulation module 403 is used to use the obtained long series of runoff, wind power output, and photovoltaic output as the input of the medium- and long-term simulation model of water-wind-solar multi-energy complementarity to simulate the medium- and long-term long-series simulation scheduling operation process of water-wind-solar complementarity; the construction module 401 is also used to construct the current state of the cascade reservoirs and the comprehensive utilization of water resources in the remaining period based on the medium- and long-term long-series simulation scheduling operation process of water-wind-solar complementarity. The response function of the target; the response function includes a first response function between the power generation guarantee rate of the water-wind-solar complementary system and the water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year, and a second response function between the water shortage index downstream of the reservoir and the water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year; the construction module 401 is also used to consider the power abandonment and load loss risks and grid peak regulation targets of the short-term operation of the water-wind-solar complementary system based on the first response function and the second response function, under the condition of uncertainty of wind and photovoltaic output, while taking into account the stability requirements of the system output, to construct a day-ahead risk scheduling model for the water-wind-solar complementary system that considers the comprehensive utilization of water resources in the remaining period, and use the model to prepare the day-ahead power generation plan of the water-wind-solar complementary system.

[0160] In some embodiments, the solution module is further used to determine the basic form and parameters of the medium- and long-term dispatching rules of water-wind-solar multi-energy complementarity, and use an implicit random optimization method to solve the medium- and long-term optimization dispatching model of water-wind-solar multi-energy complementarity to extract the medium- and long-term dispatching rules of water-wind-solar multi-energy complementarity;

[0161] Construct an implicit stochastic optimization model for the parameters of the medium- and long-term dispatching rules for the complementary energy of water, wind and solar power;

[0162] The preset multi-objective cuckoo algorithm is used to solve the implicit stochastic optimization model based on the basic form to obtain the medium- and long-term scheduling function of the water-wind-solar multi-energy complementarity.

[0163] In some embodiments, the medium- and long-term series simulation scheduling results of the water-wind-solar complementary system include: the discharge flow of the cascade reservoirs, the drawdown water level of the cascade reservoirs at the end of the month, the power generation head and the output of the cascade hydropower station; the construction module is also used to determine the drawdown water level of the Dragon Head Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system and the water shortage index downstream of the reservoir based on the discharge flow of the cascade reservoirs, the drawdown water level of the cascade reservoirs at the end of the month, the power generation head and the output of the cascade hydropower station;

[0164] The preset local weighted scatter point smoothing regression method is adopted to fit the first response function and the second response function respectively based on the water level drawdown of Longtou Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system and the water shortage index downstream of the reservoir.

[0165] In some embodiments, the pre-normal risk scheduling model of the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period includes the following objective function:

[0166] The comprehensive risk rate of power generation plan is the lowest:

[0167] ,

[0168] ,

[0169] ,

[0170] The peak-to-valley difference of the grid residual load is minimal:

[0171] ,

[0172] The expected power generation rate of the hydro-wind-solar complementary system in the remaining period is the highest:

[0173] ,

[0174] The expected minimum water shortage index downstream of the reservoir during the remaining period is:

[0175] ,

[0176] Where: I represents the number of the representative scenario; T represents the number of scheduling periods; and They represent the power abandonment rate of wind and solar energy and the system load loss rate of the hydro-wind-solar hybrid system in period t under the representative scenario i; It represents the difference between the total system output and the power generation plan during period t; and They represent the wind power output and photovoltaic output of the representative scenario i respectively; , and They represent the wind power output, photovoltaic output and their occurrence probability of the representative scenario i respectively; represents the actual output of the cascade hydropower station in period t under the representative scenario i; It represents the day-ahead power generation plan of the hydro-wind-solar hybrid system in period t; Indicates the grid load; represents the grid load during period t; represents the drawdown water level of Longtou Reservoir at the end of the dispatch period under the representative scenario i; represents the first response function under the representative scenario i; represents the second response function under the representative scenario i.

[0177] In some embodiments, the construction module is also used to construct the constraint conditions of the medium- and long-term optimization scheduling model of water, wind and solar multi-energy complementarity, including:

[0178] (1) Water balance constraints:

[0179] ,

[0180] (2) Storage capacity constraints:

[0181] ,

[0182] (3) Downflow flow constraints:

[0183] ,

[0184] (4) Hydropower station output constraints:

[0185] ,

[0186] (5) Reservoir characteristic constraints:

[0187] ,

[0188] (6) Parameter optimization interval constraints:

[0189] ,

[0190] Where: Indicates that the scheduling period is long; represents the storage capacity of the mth hydropower station at the end of the tth period; represents the storage capacity of the mth hydropower station at the end of the t+1th period; and They represent the inflow and outflow of the mth hydropower station in the tth period respectively; and They represent the lower and upper limits of the storage capacity of the mth hydropower station respectively; and They represent the minimum and maximum discharge flow of the mth hydropower station respectively; represents the discharge flow of the hydropower station in the mth period of time; and They represent the lower and upper limits of the output of the mth hydropower station respectively; represents the output of the hydropower station in the mth period of time; represents the water level at the end of the tth period at the mth hydropower station; represents the tailwater level of the mth hydropower station at the end of the tth period; , It represents the fitting parameters of the linear dispatch function in the day-ahead risk dispatch model of the hydro-wind-solar hybrid system; , represents the fitted parameters of the linear scheduling function in the implicit stochastic optimization model.

[0191] In some embodiments, the constraints of the day-ahead risk scheduling model of the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period include: (1) to (5) of the constraints of the medium- and long-term optimal scheduling model of the water-wind-solar multi-energy complementarity, and the following constraints:

[0192] Output stability constraints of water-wind-solar hybrid system:

[0193] ,

[0194] Where: represents the output power of the sth stable operation period in the transmission curve of the hydro-wind-solar hybrid system; s represents the number of the stable operation period of the transmission curve; tc represents the time point when the daily transmission plan power changes; tc s Indicates the end point time of the sth stable operation period; tc s-1 represents the end point of the s-1th stable operation period; the value range of t is (0, 24); based on this, the derived day-ahead power generation plan can be expressed as:

[0195] ,

[0196] Where: S is the number of steps of the transmission curve, that is, the number of stable operation periods; It represents the system day-ahead power generation plan in the first stable operation period;

[0197] The upper and lower limits of the output of the water-wind-solar hybrid system are as follows:

[0198] ,

[0199] Where: and They represent the upper and lower limits of the output of the water-wind-solar hybrid system respectively; It represents the day-ahead power generation plan of the hydro-wind-solar hybrid system during period t.

[0200] In some embodiments, the device further comprises: a calculation module for step S1: The fourth objective function of determining the day-ahead power generation plan of the wind-solar hybrid system and tc is used to minimize the peak-to-valley difference of the remaining load of the power grid; S2: Calculate the load process of cascade hydropower under the representative scenario i ; S3: The load distribution process of cascade hydropower stations under representative scenario i is determined by combining the discrimination coefficient and relative water demand rate, and the actual output process of cascade hydropower under representative scenario i is determined by considering various constraints on the operation of cascade reservoirs and hydropower stations. ; S4: loop S2 and S3 until the actual output process of cascade hydropower under all representative scenarios is obtained; S5: based on the load distribution results under each representative scenario and the corresponding probability of each scenario, calculate the third objective function with the minimum comprehensive risk rate of the power generation plan, the fifth objective function with the highest expected power generation guarantee rate of the water-wind-solar complementary system in the remaining period, and the sixth objective function with the minimum expected water shortage index downstream of the reservoir in the remaining period; S6: guided by the above objective function values, iterative calculation is performed through the multi-objective optimization algorithm until the preset number of times is reached, and the model solution set is output to obtain the day-ahead power generation plan of the water-wind-solar complementary system that takes into account the comprehensive utilization of water resources in the remaining period.

[0201] It should be noted that the description of the device of the embodiment of the present invention is similar to the description of the above method embodiment, and has similar beneficial effects as the same method embodiment, so it will not be repeated. For technical details not disclosed in the embodiment of the device, please refer to the description of the method embodiment of the present invention for understanding.

[0202] It should be noted that in the embodiments of the present invention, if the above-mentioned water, wind and light short-term risk scheduling method that takes into account the utilization of water resources in the remaining period is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention, or the part that contributes to the relevant technology, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions for a terminal to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read Only Memory), disk or optical disk, and other media that can store program codes. In this way, the embodiments of the present invention are not limited to any specific combination of hardware and software.

[0203] Correspondingly, the embodiment of the present invention provides a short-term risk scheduling device for water, wind and solar power that takes into account the utilization of water resources in the remaining period. Figure 5 is a schematic diagram of the composition structure of a water, wind and solar short-term risk scheduling device that takes into account the utilization of water resources in the remaining period provided by an embodiment of the present invention, such as Figure 5As shown, the short-term risk scheduling device 500 for water, wind and solar power taking into account the utilization of water resources in the remaining period includes at least: a processor 501 and a computer-readable storage medium 502 configured to store executable instructions, wherein the processor 501 generally controls the overall operation of the short-term risk scheduling device for water, wind and solar power taking into account the utilization of water resources in the remaining period. The computer-readable storage medium 502 is configured to store instructions and applications executable by the processor 501, and can also cache data to be processed or processed by each module in the processor 501 and the short-term risk scheduling device for water, wind and solar power taking into account the utilization of water resources in the remaining period 500, which can be implemented through flash memory (FLASH) or random access memory (RAM, Random Access Memory).

[0204] An embodiment of the present invention provides a storage medium storing executable instructions, wherein the executable instructions are stored. When the executable instructions are executed by a processor, the processor will be caused to execute the method provided by the embodiment of the present invention, for example, Figure 2 The method shown.

[0205] In some embodiments, the storage medium can be a computer-readable storage medium, for example, a ferroelectric random access memory (FRAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a magnetic surface memory, an optical disk, or a compact disk read-only memory (CD-ROM); it can also be various devices including one or any combination of the above memories.

[0206] In some embodiments, executable instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0207] As an example, executable instructions may, but need not correspond to, a file in a file system, may be stored as part of a file storing other programs or data, such as one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions). As an example, executable instructions may be deployed to be executed on one electronic device, or on multiple electronic devices located at one location, or on multiple electronic devices distributed at multiple locations and interconnected by a communication network.

[0208] The above description is only an embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement and improvement made within the spirit and scope of the present invention are included in the protection scope of the present invention.

[0209] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present invention, the size of the serial number of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. The serial numbers of the above-mentioned embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0210] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method or device. In the absence of further restrictions, an element defined by the statement "comprises one..." does not exclude the presence of other identical elements in the process, method, article or device including the element. In several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed.

[0211] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A short-term risk scheduling method for water, wind and solar power that takes into account the utilization of water resources in the remaining period, characterized in that: The method comprises: With the goal of maximizing the guaranteed power generation rate of the water-wind-solar complementary system and minimizing the water shortage index downstream of the reservoir, a medium- and long-term optimization scheduling model for water-wind-solar multi-energy complementarity is constructed; wherein, the first objective function for maximizing the guaranteed power generation rate of the water-wind-solar complementary system is: , the second objective function of minimizing the water shortage index downstream of the reservoir is: , where: Indicates the power generation guarantee rate of the water-wind-solar complementary system; t and T Respectively represent the mid- to long-term dispatch period number and the total dispatch period; , , Respectively represent t The actual average output of hydropower, the average output of photovoltaic power stations and the average output of wind farms during the period; It indicates the guaranteed output of the water-wind-solar complementary system; It indicates the number of times the net output of the hydro-wind-solar hybrid system is higher than the guaranteed output during the entire dispatch period; It represents the water shortage index downstream of the reservoir; and Respectively t Downstream water demand and discharge flow during the time period; Solve the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity to obtain the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity; Based on the medium- and long-term dispatching function of water-wind-solar multi-energy complementarity, a medium- and long-term simulation model of water-wind-solar multi-energy complementarity is constructed; The obtained long series of runoff, wind power output, and photovoltaic output are used as inputs of the medium- and long-term simulation model of water-wind-solar multi-energy complementarity to simulate the medium- and long-term long series scheduling and operation process of water-wind-solar complementarity; Based on the medium- and long-term series of simulated dispatching and operation processes of water-wind-solar complementarity, a response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period is constructed; the response function includes a first response function between the power generation guarantee rate of the water-wind-solar complementarity system and the drawdown water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year, and a second response function between the water shortage index downstream of the reservoir and the drawdown water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year; the medium- and long-term series of simulated dispatching and operation processes of water-wind-solar complementarity include: the discharge flow of the cascade reservoirs, the drawdown water level of the cascade reservoirs at the end of the month, the power generation head and the output of the cascade hydropower stations; based on the medium- and long-term series of simulated dispatching and operation processes of water-wind-solar complementarity The process constructs a response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period, including: determining the drawdown level of the Longtou Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system, and the water shortage index downstream of the reservoir based on the discharge flow of the cascade reservoirs, the drawdown level of the cascade reservoirs at the end of the month, the power generation head, and the output of the cascade hydropower station; using a preset local weighted scattered point smoothing regression method, based on the drawdown level of the Longtou Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system, and the water shortage index downstream of the reservoir, respectively fitting the first response function and the second response function; Based on the first response function and the second response function, under the condition of uncertainty of wind and photovoltaic output, considering the risks of power abandonment and load loss in short-term operation of the hydro-wind-solar complementary system and the peak-shaving target of the power grid, while taking into account the stability demand of the system output, a day-ahead risk scheduling model of the hydro-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period is constructed, and the model is used to prepare the day-ahead power generation plan of the hydro-wind-solar complementary system.

2. The method according to claim 1, characterized in that The method of solving the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity to obtain the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity includes: Determine the basic form and parameters of the medium- and long-term dispatching rules of the water-wind-solar multi-energy complementarity, use the implicit stochastic optimization method to solve the medium- and long-term optimization dispatching model of the water-wind-solar multi-energy complementarity, and extract the medium- and long-term dispatching rules of the water-wind-solar multi-energy complementarity; Construct an implicit stochastic optimization model for the parameters of the mid- and long-term dispatching rules of the water, wind and solar multi-energy complementarity; The preset multi-objective cuckoo algorithm is used to solve the implicit stochastic optimization model based on the basic form to obtain the medium- and long-term scheduling function of the water-wind-solar multi-energy complementarity.

3. The method according to claim 1, characterized in that The day-ahead risk scheduling model of the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period includes the following objective functions: The comprehensive risk rate of power generation plan is the lowest: ； ； The peak-to-valley difference of the grid residual load is minimal: ； The expected power generation rate of the hydro-wind-solar complementary system in the remaining period is the highest: ； The expected water shortage index downstream of the reservoir during the remaining period is minimal: ； Where: I The number indicating the representative scene; T Indicates the number of scheduling periods; and They represent the representative scenarios of water-wind-solar hybrid system. i Down t The power abandonment rate and system load loss rate of wind and solar energy in each period; express t The difference between the total system output and the power generation plan during the period; , and Represent representative scenes respectively i wind power output, photovoltaic output and their probability of occurrence; Represents cascade hydropower stations in representative scenarios i Down t The actual output during the time period; express t The day-ahead power generation plan of the water-wind-solar hybrid system in each period; Indicates the grid load; express t Grid load during the period; Indicates Longtou Reservoir in representative scenes i The drawdown water level at the end of the next dispatch period; In representative scenes i The first response function under ; In representative scenes i The second response function below.

4. The method according to claim 1, characterized in that: The method further comprises: The constraints for constructing the medium- and long-term optimization scheduling model of water, wind and solar multi-energy complementarity include: (1) Water balance constraints: ； (2) Storage capacity constraints: ； (3) Downflow flow constraints: ； (4) Hydropower station output constraints: ； (5) Reservoir characteristic constraints: ； (6) Parameter optimization interval constraints: ； Where: Indicates that the scheduling period is long; Indicates m Hydropower Station No. t Storage capacity at the end of the period; Indicates m Hydropower Station No. t +1 Storage capacity at the end of the period; and Respectively represent m Hydropower Station No. t Inflow and outflow of the reservoir during the period; and Respectively represent m The lower and upper limits of the storage capacity of each hydropower station; and Respectively represent m The minimum and maximum discharge flow of each hydropower station; Indicates m No. t The discharge flow of hydropower station during the period; and Respectively represent m The lower and upper limits of the output of each hydropower station; Indicates m No. t Output of hydropower station during the period; Indicates m Hydropower Station No. t The water level at the end of the period; Indicates m Hydropower Station No. t tailwater level at the end of the period; is the relationship function between the water level and storage capacity of the reservoir; is the relationship function between the tailwater level and flow rate of the reservoir; , represents the fitted parameters of the linear scheduling function.

5. The method according to claim 1, characterized in that The constraints of the day-ahead risk scheduling model of the water-wind-solar complementary system considering the comprehensive utilization of water resources in the remaining period include: (1) to (5) of the constraints of the medium- and long-term optimal scheduling model of the water-wind-solar multi-energy complementarity, as well as the following constraints: Output stability constraints of water-wind-solar hybrid system: ； Where: It represents the output power of the hydro-wind-solar hybrid system in the sth stable operation period; The upper and lower limits of the output of the water-wind-solar hybrid system are as follows: ； Where: and They respectively represent the upper and lower limits of the output of the water-wind-solar hybrid system.

6. The method according to claim 1, characterized in that The method further comprises: S1: by decision variables and tc to determine the day-ahead power generation plan of the wind-water hybrid system, and calculate the fourth objective function of minimizing the peak-to-valley difference of the remaining load of the power grid; S2: In representative scenarios i Calculate the load process of cascade hydropower ; S3: Use the method combining the discriminant coefficient and relative water demand rate to determine the representative scenario i The load distribution process of the next cascade hydropower station, taking into account various constraints on the operation of cascade reservoirs and hydropower stations, and determining representative scenarios i Actual output process of lower cascade hydropower ; S4: loop S2 and S3 until the actual output process of cascade hydropower under all representative scenarios is obtained; S5: Based on the load distribution results under each representative scenario and the corresponding probability of each scenario, the third objective function with the minimum comprehensive risk rate of the power generation plan, the fifth objective function with the highest expected power generation guarantee rate of the water-wind-solar complementary system in the remaining period, and the sixth objective function with the minimum expected water shortage index downstream of the reservoir in the remaining period are calculated respectively; S6: Guided by the value of the above objective function, iterative calculation is performed through a multi-objective optimization algorithm until the preset number of times is reached, and the model solution set is output to obtain the day-ahead power generation plan of the water-wind-solar complementary system that takes into account the comprehensive utilization of water resources in the remaining period.

7. A short-term risk scheduling device for water, wind and solar power that takes into account the utilization of water resources in the remaining period, characterized in that: The device comprises: A construction module is used to construct a medium- and long-term optimization scheduling model for water-wind-solar multi-energy complementarity with the goal of maximizing the power generation guarantee rate of the water-wind-solar complementary system and minimizing the water shortage index downstream of the reservoir; wherein the first objective function for the highest power generation guarantee rate of the water-wind-solar complementary system is: , the second objective function of minimizing the water shortage index downstream of the reservoir is: , where: Indicates the power generation guarantee rate of the water-wind-solar complementary system; t and T Respectively represent the mid- to long-term dispatch period number and the total dispatch period; , , Respectively represent t The actual average output of hydropower, the average output of photovoltaic power stations and the average output of wind farms during the period; It indicates the guaranteed output of the water-wind-solar complementary system; It indicates the number of times the net output of the complementary system is higher than the guaranteed output during the entire dispatch period; It represents the water shortage index downstream of the reservoir; and Respectively t Downstream water demand and discharge flow during the time period; A solution module, used to solve the medium- and long-term optimization scheduling model of water-wind-solar multi-energy complementarity, and obtain the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity; The construction module is also used to construct a medium- and long-term simulation model of water-wind-solar multi-energy complementarity based on the medium- and long-term scheduling function of water-wind-solar multi-energy complementarity; A simulation module is used to use the obtained long series of runoff, wind power output, and photovoltaic output as inputs of the medium- and long-term simulation model of water-wind-solar multi-energy complementarity to simulate the medium- and long-term long series scheduling and operation process of water-wind-solar complementarity; The construction module is also used to construct a response function between the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period based on the medium- and long-term series of simulation scheduling and operation processes of the water-wind-solar complementary system; the response function includes a first response function between the power generation guarantee rate of the water-wind-solar complementary system and the water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year, and a second response function between the water shortage index downstream of the reservoir and the water level of the Dragon Head Reservoir at the end of the month and the natural average flow in the next year; the medium- and long-term simulation scheduling and operation process of the water-wind-solar complementary system includes: the discharge flow of the cascade reservoirs, the water level of the cascade reservoirs at the end of the month, the power generation head and the output of the cascade hydropower station; based on the medium- and long-term series of simulation scheduling and operation processes of the water-wind-solar complementary system The proposed dispatching operation process constructs a response function of the current state of the cascade reservoirs and the comprehensive utilization target of water resources in the remaining period, including: determining the drawdown level of the Leading Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system, and the water shortage index downstream of the reservoir based on the discharge flow of the cascade reservoirs, the drawdown level of the cascade reservoirs at the end of the month, the power generation head, and the output of the cascade hydropower stations; using a preset local weighted scattered point smoothing regression method, based on the drawdown level of the Leading Reservoir at the end of the month, the natural average flow in the next year, the power generation guarantee rate of the water-wind-solar complementary system, and the water shortage index downstream of the reservoir, respectively fitting the first response function and the second response function; The construction module is also used to build a day-ahead risk scheduling model for the water-wind-solar complementary system that takes into account the comprehensive utilization of water resources in the remaining period, based on the first response function and the second response function, under the condition of uncertainty in wind and photovoltaic output, taking into account the risks of power abandonment and load loss in the short-term operation of the water-wind-solar complementary system and the peak-shaving target of the power grid, while taking into account the stability requirements of the system output, and using the model to prepare a day-ahead power generation plan for the water-wind-solar complementary system.

8. An electronic device, characterized in that: include: A memory for storing executable instructions; The processor is used to implement the water, wind and solar short-term risk scheduling method taking into account the remaining period water resource utilization as described in any one of claims 1 to 6 when executing the executable instructions stored in the memory.

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