Optimized scheduling method and device for participation of water-wind-light complementary system in electricity market

Abstract

The invention relates to the technical field of water-wind-light dispatching, and discloses an optimal dispatching method and device for a water-wind-light complementary system to participate in an electricity market, which can reflect the price fluctuation of the electricity market and the potential generating capacity of water-wind-light energy by acquiring various forecast information in a forecast period. Furthermore, a benefit risk index system is constructed, and economic benefits and faced risks of the system in different operation states can be quantitatively evaluated. Furthermore, a forecast information set and a benefit risk index system are combined to construct a two-step optimization scheduling model of the water-wind-light complementary system and solve the model, the water-wind-light complementary system can be optimized from different time scales, various factors of system operation are comprehensively considered, a clearing plan of the water-wind-light complementary system can be formulated more scientifically, and the method is suitable for popularization and application. The operation stability and the resource utilization efficiency of the water-wind-light complementary system are improved, powerful technical support is provided for the quotation strategy of water-wind-light participating in the electricity market, and then complex changes of the electricity market can be better coped with.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated scheduling of hydropower, wind power and photovoltaic power, and particularly to an optimal scheduling method and device for a hydropower-wind power-photovoltaic power complementary system to participate in the electricity market. Background Art

[0002] When renewable energy enters the spot market, short-term scheduling is no longer determined according to the previously formulated generation plan, but according to the predicted clearing price and bidding scheme. When wind power and photovoltaic power participate in the spot market alone, considering their uncertainty, non-adjustability and randomness, it is difficult to bid. However, after the integration of hydropower, wind power and photovoltaic power, the bidding space can be further increased under the regulation ability of hydropower. Due to the flexibility of hydropower, it can suppress the fluctuations of wind power and photovoltaic power. After entering the spot market, due to the uncertainty of electricity prices, hydropower units will also face regulation problems. Coupled with the role of regulating wind power and photovoltaic power, the regulation pressure faced by hydropower is increasing. How to construct an integrated scheduling of hydropower, wind power and photovoltaic power has become a key scientific issue in the context of the electricity market.

[0003] Currently, most of the research on the integrated scheduling of hydropower, wind power and photovoltaic power focuses on meeting load demand or maximizing generation benefits, lacking an integrated scheduling method for participating in the electricity market and also lacking application analysis of engineering actual cases. Summary of the Invention

[0004] In view of this, the present invention provides an optimal scheduling method and device for a hydropower-wind power-photovoltaic power complementary system to participate in the electricity market, so as to solve the problems that the current research on the integrated scheduling of hydropower, wind power and photovoltaic power lacks an integrated scheduling method for participating in the electricity market and also lacks application analysis of engineering actual cases.

[0005] In a first aspect, the present invention provides an optimal scheduling method for a hydropower-wind power-photovoltaic power complementary system to participate in the electricity market, and the method includes:

[0006] Obtain the forecast information set, settlement revenue method and multiple first operation risks of the hydropower-wind power-photovoltaic power complementary system, where the forecast information set includes the forecast multi-time scale electricity price sequence, reservoir inflow sequence, wind speed sequence and photovoltaic sequence; based on the forecast information set, settlement revenue method and multiple first operation risks, construct a benefit-risk index system; based on the forecast information set and the benefit-risk index system, construct a two-step optimal scheduling model for the hydropower-wind power-photovoltaic power complementary system; solve the two-step optimal scheduling model for the hydropower-wind power-photovoltaic power complementary system to obtain the target clearing value of each time period within the forecast period in the predicted market for the hydropower-wind power-photovoltaic power complementary system.

[0007] The optimal dispatching method for a water-wind-solar complementary system provided by the present invention to participate in the electricity market can reflect the electricity market price fluctuations and the potential power generation of water-wind-solar energy by obtaining various forecast information within the forecast period. Furthermore, by understanding the market environment and energy supply situation in advance, it provides accurate data support for subsequent dispatching decisions, enabling the dispatching plan to better adapt to the uncertainties of electricity prices and wind-solar power generation in the spot market and improving the competitiveness of the system in the market. Further, by constructing a benefit-risk index system using the obtained forecast information, it can quantitatively evaluate the economic benefits and risks faced by the system under different operating states, facilitating the analysis of the performance of the water-wind-solar complementary system under different working conditions. Further, by constructing and solving a two-step optimal dispatching model for the water-wind-solar complementary system in combination with the forecast information set and the benefit-risk index system, it can optimize the water-wind-solar complementary system from different time scales, comprehensively consider various factors in the system operation, can more scientifically formulate the clearing plan for water-wind-solar, improve the operation stability and resource utilization efficiency of the water-wind-solar complementary system, provide strong technical support for the bidding strategy of water-wind-solar to participate in the electricity market, and thus can better cope with the complex changes in the electricity market. Further, the obtained target clearing values for each period within a day provide specific operation guidance for the actual operation of the water-wind-solar complementary system, effectively suppress the fluctuations of wind-solar power generation by hydropower, reduce the regulation pressure of hydropower, improve the power generation efficiency, and at the same time provide a basis for the bidding strategy of the water-wind-solar complementary system, enabling the water-wind-solar complementary system to obtain better economic benefits and competitive advantages in the electricity market.

[0008] In an alternative embodiment, a benefit-risk index system is constructed based on a forecast information set, a settlement revenue method, and multiple first operating risks, including:

[0009] Based on the forecast information set and the settlement revenue method, determine the power generation benefit, wind power generation, photovoltaic power generation, and hydropower generation; according to the wind power generation, photovoltaic power generation, and hydropower generation, determine the curtailment rate, which is used to reflect the curtailment risk; according to the hydropower generation, calculate the reservoir discharge flow and determine the water abandonment risk; construct a benefit-risk index system based on the power generation benefit, curtailment rate, water abandonment risk, and multiple first operating risks.

[0010] The optimal dispatching method for a water-wind-solar complementary system provided by the present invention can quantitatively evaluate the revenue and risk status of the water-wind-solar complementary system under different operating conditions by combining the forecast information set and the settlement revenue method to determine indicators such as power generation benefit and water abandonment risk. At the same time, by determining the curtailment rate to reflect the curtailment risk, it can intuitively reflect the accommodation situation of wind-solar power generation, facilitate timely adjustment of the dispatching strategy, reduce the phenomena of wind and light curtailment caused by the uncertainties of wind and light, improve the utilization efficiency of renewable energy, and give full play to the advantages of the water-wind-solar complementary system.

[0011] In an alternative embodiment, based on the forecast information set and the benefit-risk index system, a two-step optimal scheduling model for the water-wind-solar complementary system is constructed, including:

[0012] Based on the benefit-risk index system, the first objective function and the second objective function are respectively determined. Among them, the first objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the entire foreseeable period within the forecast cycle, and the second objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the day-ahead period within the forecast cycle. Based on the forecast information set, the first objective function and the second objective function, a two-step optimal scheduling model for the water-wind-solar complementary system is constructed.

[0013] The optimal scheduling method for the water-wind-solar complementary system participating in the power market provided by the present invention can optimize the water-wind-solar complementary system from two perspectives of economic benefit and risk control by respectively determining the objective functions characterizing the total power generation revenue and curtailment risk in different stages. While the system pursues power generation benefits, it effectively reduces the risks brought by market uncertainties and improves the stability and sustainability of the system in the spot market. Further, an optimal scheduling model is constructed with the objective function as the core, which can provide a scientific mathematical framework for the scheduling decisions of the water-wind-solar complementary system at different time scales (the entire foreseeable period, the day-ahead period), and then can more reasonably allocate the outputs of hydropower, wind power and photovoltaic power, balancing the benefits and risks of system operation.

[0014] In an alternative embodiment, based on the forecast information set, the first objective function and the second objective function, a two-step optimal scheduling model for the water-wind-solar complementary system is constructed, including:

[0015] Obtain the first constraint condition set and the second constraint condition set; based on the first constraint condition set, use the forecast information set and the first objective function to construct the first optimal scheduling model for the water-wind-solar complementary system during the entire foreseeable period; based on the first constraint condition set and the second constraint condition set, use the forecast information set and the second objective function to construct the second optimal scheduling model for the water-wind-solar complementary system during the day-ahead period; according to the first optimal scheduling model for the water-wind-solar complementary system and the second optimal scheduling model for the water-wind-solar complementary system, determine the two-step optimal scheduling model for the water-wind-solar complementary system.

[0016] The optimal scheduling method for a water-wind-solar complementary system to participate in the electricity market provided by the present invention obtains different sets of constraint conditions, and constructs optimal scheduling models for different stages by combining the forecast information set and the objective function. It fully considers various actual limiting factors in the operation process of the water-wind-solar complementary system, thereby making the constructed model closer to the engineering reality and improving the feasibility and operability of the scheduling plan. Further, the model is constructed in stages. First, the overall operation framework is determined from the macroscopic perspective of the entire forecast period, and then it is refined and optimized in the day-ahead stage, which can more accurately respond to market changes and uncertainties within the system, and improve the scheduling efficiency and resource allocation effect of the water-wind-solar complementary system.

[0017] In an alternative embodiment, the two-step optimal scheduling model of the water-wind-solar complementary system is solved to obtain the target clearing values of each time period within the day in the forecast period of the water-wind-solar complementary system in the forecast market, including:

[0018] Taking the water level at each moment as the decision variable, the two-step optimal scheduling model of the water-wind-solar complementary system is solved on a daily scale to obtain the initial clearing value of the water-wind-solar complementary system within the forecast period; taking the hydropower output of each time period within the day as the decision variable and using the initial clearing value as a constraint, the two-step optimal scheduling model of the water-wind-solar complementary system is solved to obtain the target clearing values of each time period within the day in the forecast period of the water-wind-solar complementary system in the forecast market.

[0019] The optimal scheduling method for a water-wind-solar complementary system to participate in the electricity market provided by the present invention takes the water level at each moment as the decision variable and solves the model on a daily scale to obtain the initial clearing value, which can plan the power generation capacity and regulation role of hydropower from a long-term perspective. Furthermore, it can reasonably arrange the water storage and release strategies of the reservoir, relieve the regulation pressure of hydropower in regulating wind-solar fluctuations and its own situation, and improve the utilization efficiency of hydropower resources. Further, taking the hydropower output of each time period within the day as the decision variable and using the obtained initial clearing value as a constraint for further solution, it can flexibly adjust the hydropower output according to the real-time market electricity price and wind-solar power generation situation on a daily scale, realizing the real-time complementarity of water-wind-solar, and improving the response speed and power generation benefit of the water-wind-solar complementary system in the spot market.

[0020] In an alternative embodiment, the first set of constraint conditions includes water volume balance constraint conditions, power balance constraint conditions, flow constraint conditions, water level constraint conditions, water level amplitude constraint conditions, head constraint conditions, and output constraint conditions; the second set of constraint conditions includes unit ramp constraint conditions, vibration zone constraint conditions, and unit start-stop constraint conditions.

[0021] The optimal scheduling method for a water-wind-solar complementary system provided by the present invention to participate in the electricity market can make the scheduling plan more scientific and reasonable by defining different constraint condition sets, avoiding equipment damage or unstable system operation caused by unreasonable scheduling, and thus ensuring the safe and efficient operation of the entire water-wind-solar complementary system in the electricity market environment.

[0022] In a second aspect, the present invention provides an optimal scheduling device for a water-wind-solar complementary system to participate in the electricity market, the device comprising:

[0023] An acquisition module, configured to acquire a forecast information set, a settlement revenue method, and multiple first operation risks of the water-wind-solar complementary system, wherein the forecast information set includes a forecast multi-time scale electricity price sequence, an inflow sequence, a wind speed sequence, and a photovoltaic sequence; a first construction module, configured to construct a benefit-risk index system based on the forecast information set, the settlement revenue method, and the multiple first operation risks; a second construction module, configured to construct a two-step optimal scheduling model for the water-wind-solar complementary system based on the forecast information set and the benefit-risk index system; and a solution module, configured to solve the two-step optimal scheduling model for the water-wind-solar complementary system to obtain the target clearing value of each time period within the forecast period in the prediction market for the water-wind-solar complementary system.

[0024] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, which are communicatively connected to each other, wherein the memory stores computer instructions, and the processor executes the computer instructions to execute the optimal scheduling method for the water-wind-solar complementary system to participate in the electricity market according to the first aspect or any corresponding embodiment thereof.

[0025] In a fourth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the optimal scheduling method for the water-wind-solar complementary system to participate in the electricity market according to the first aspect or any corresponding embodiment thereof.

[0026] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, and the computer instructions are used to cause a computer to execute the optimal scheduling method for the water-wind-solar complementary system to participate in the electricity market according to the first aspect or any corresponding embodiment thereof. Description of the Drawings

[0027] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0028] Figure 1 It is a schematic flowchart of an optimal scheduling method for a water-wind-solar complementary system participating in the electricity market according to an embodiment of the present invention;

[0029] Figure 2 It is a schematic flowchart of another optimal scheduling method for a water-wind-solar complementary system participating in the electricity market according to an embodiment of the present invention;

[0030] Figure 3 It is a schematic flowchart of yet another optimal scheduling method for a water-wind-solar complementary system participating in the electricity market according to an embodiment of the present invention;

[0031] Figure 4 It is a schematic logic diagram of an integrated water-wind-solar scheduling method under the background of the electricity market according to an embodiment of the present invention;

[0032] Figure 5 It is a structural block diagram of an optimal scheduling device for a water-wind-solar complementary system participating in the electricity market according to an embodiment of the present invention;

[0033] Figure 6 It is a schematic hardware structure diagram of a computer device according to an embodiment of the present invention. Specific Embodiments

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] The embodiments of the present invention provide an optimal scheduling method for a water-wind-solar complementary system participating in the electricity market. By constructing and solving a two-step optimal scheduling model for the water-wind-solar complementary system by combining a forecast information set and a benefit-risk index system, it is possible to optimize the water-wind-solar complementary system from different time scales, comprehensively consider various factors in system operation, more scientifically plan the output allocation of water, wind, and solar, improve the stability of the operation of the water-wind-solar complementary system and the resource utilization efficiency, and thus better cope with the complex changes in the electricity market.

[0036] According to an embodiment of the present invention, an embodiment of an optimal scheduling method for a water-wind-solar complementary system participating in the electricity market is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0037] In this embodiment, an optimized scheduling method for a water-wind-solar complementary system to participate in the electricity market is provided, which can be used in electronic devices such as computers, mobile phones, and tablet computers. Figure 1 It is a flowchart of the optimized scheduling method for a water-wind-solar complementary system to participate in the electricity market according to an embodiment of the present invention, as Figure 1 shown. The process includes the following steps:

[0038] Step S101, obtain the forecast information set, settlement revenue method, and multiple first operating risks of the water-wind-solar complementary system.

[0039] Among them, the water-wind-solar complementary system refers to an energy system that combines three renewable energy generation methods: hydropower generation, wind power generation, and photovoltaic power generation. By integrating three different types of power generation methods and utilizing their respective characteristics and advantages, the complementary and collaborative utilization of energy can be achieved.

[0040] The forecast period represents a specific time range for forecasting relevant information of the water-wind-solar complementary system, which can be determined according to actual needs and system operation characteristics.

[0041] The forecast information set represents a set containing various relevant forecast information of the water-wind-solar complementary system within the corresponding forecast period, which can include forecast multi-time scale electricity price sequences, reservoir inflow sequences, wind speed sequences, and photovoltaic sequences.

[0042] Furthermore, the forecast multi-time scale electricity price sequence is used to reflect the electricity price prediction situation in different periods within the forecast period of the electricity market; the reservoir inflow sequence represents the prediction of the reservoir inflow volume in each period within the forecast period, which can be used to evaluate the power generation potential of hydropower; the wind speed sequence and the photovoltaic sequence respectively represent the prediction of the wind speed and photovoltaic power generation volume in different periods within the forecast period, which can help understand the output of wind power and photovoltaic power.

[0043] Specifically, the forecast information set is shown in the following relational expressions (1) and (2):

[0044]

[0045] Furthermore:

[0046]

[0047] Among them, EP represents the forecast electricity price, EP M and EP spotrespectively represent the medium- and long-term electricity price and the spot electricity price; Q represents the forecasted reservoir inflow; NW represents the forecasted wind power output; NS represents the forecasted photovoltaic power output; D represents the forecast period, generally 3 to 7 days. Further, the relational expression (1) represents the forecast information set for the entire forecast period D; the relational expression (2) represents the forecast information set for the entire day-ahead stage, T represents the number of day-ahead time periods, for example, if hourly forecast data is used, T = 24; if 15-minute data is used, T = 96.

[0048] Further, multiple first operating risks are used to characterize risk phenomena occurring during the operation process such as operation in the vibration area and blocked unit ramping, and may include unit ramping risk, vibration area risk, etc.

[0049] Step S102, based on the forecast information set, the settlement revenue method, and multiple first operating risks, construct a benefit-risk index system.

[0050] Among them, the benefit-risk index system represents a comprehensive index set for measuring the benefits and risks of a water-wind-solar complementary system during the operation process, and can comprehensively and systematically reflect the status of the water-wind-solar complementary system in terms of power generation benefits and faced risks through multiple specific indexes.

[0051] Specifically, by analyzing the forecasted multi-time scale electricity price sequence, the electricity market price fluctuation situation can be understood, and then combined with the settlement revenue method, the power generation benefits of the system under different electricity prices can be evaluated. At the same time, by combining information such as the reservoir inflow sequence, wind speed sequence, and photovoltaic sequence, various risks faced by the water-wind-solar complementary system can be evaluated.

[0052] Further, according to the obtained power generation benefits, various risk indexes, and multiple first operating risks such as unit ramping risk and vibration area risk, the corresponding benefit-risk index system can be constructed.

[0053] Step S103, based on the forecast information set and the benefit-risk index system, construct a two-step optimal scheduling model for the water-wind-solar complementary system.

[0054] Among them, the two-step optimal scheduling model for the water-wind-solar complementary system represents a scheduling strategy model for the water-wind-solar complementary system.

[0055] Specifically, the forecast information set provides the basic data for the operation of the water-wind-solar complementary system, and can determine the operation status and deployable resources of the water-wind-solar complementary system under different conditions. At the same time, the benefit-risk index system can provide the goal and measurement standard for the optimization of the model.

[0056] Furthermore, by combining the forecast information set with the benefit-risk index system to construct a corresponding two-step optimal scheduling model for the water-wind-solar complementary system, the optimization of the water-wind-solar complementary system can be carried out from different time scales. Considering various factors in the system operation comprehensively, it can plan the output allocation of water, wind and solar more scientifically, improve the operation stability of the water-wind-solar complementary system and the resource utilization efficiency, and thus better cope with the complex changes in the power market.

[0057] Step S104: Solve the two-step optimal scheduling model for the water-wind-solar complementary system to obtain the target clearing values of each time period within the day in the forecast period of the water-wind-solar complementary system in the prediction market.

[0058] Specifically, by solving the two-step optimal scheduling model for the water-wind-solar complementary system in stages, the optimal clearing values of each time period within the day in the forecast period of the water-wind-solar complementary system, that is, the target clearing values, can be obtained.

[0059] The optimal scheduling method for the water-wind-solar complementary system participating in the power market provided in this embodiment can reflect the price fluctuations in the power market and the potential power generation of water, wind and solar energy by obtaining various forecast information within the forecast period. Furthermore, by understanding the market environment and energy supply situation in advance, it provides accurate data support for subsequent scheduling decisions, enabling the scheduling plan to better adapt to the uncertainties of electricity prices and wind-solar power generation in the spot market and improving the competitiveness of the system in the market. Further, by using the obtained forecast information to construct a benefit-risk index system, the economic benefits and risks faced by the system in different operating states can be quantitatively evaluated, facilitating the analysis of the performance of the water-wind-solar complementary system under different working conditions. Further, by combining the forecast information set with the benefit-risk index system to construct and solve the two-step optimal scheduling model for the water-wind-solar complementary system, the optimization of the water-wind-solar complementary system can be carried out from different time scales. Considering various factors in the system operation comprehensively, it can formulate the clearing plan of water, wind and solar more scientifically, improve the operation stability of the water-wind-solar complementary system and the resource utilization efficiency, provide strong technical support for the bidding strategy of water, wind and solar participating in the power market, and thus better cope with the complex changes in the power market. Further, the obtained target clearing values of each time period within the day provide specific operation guidance for the actual operation of the water-wind-solar complementary system, effectively suppress the fluctuations of wind-solar power generation by hydropower, reduce the regulation pressure of hydropower, improve the power generation efficiency, and at the same time provide a basis for the bidding strategy of the water-wind-solar complementary system, enabling the water-wind-solar complementary system to obtain better economic benefits and competitive advantages in the power market.

[0060] In this embodiment, an optimal scheduling method for a water-wind-solar complementary system participating in the power market is provided, which can be used in electronic devices such as computers, mobile phones, and tablet computers. Figure 2 It is a flowchart of the optimal scheduling method for the water-wind-solar complementary system participating in the power market according to the embodiment of the present invention, as Figure 2As shown in the figure, the process includes the following steps:

[0061] Step S201: Obtain the forecast information set, settlement revenue method, and multiple first operating risks of the water-wind-solar complementary system. For details, please refer to Figure 1 Step S101 of the embodiment shown, which will not be elaborated here.

[0062] Step S202: Based on the forecast information set, settlement revenue method, and multiple first operating risks, construct a benefit-risk index system.

[0063] Specifically, the above step S202 includes:

[0064] Step S2021: Based on the forecast information set and settlement revenue method, determine the power generation benefit, wind power generation, photovoltaic power generation, and hydropower generation.

[0065] Specifically, the power generation benefit is the revenue value of the water-wind-solar multi-energy complementary system. The revenue is calculated according to the two-part settlement model (settlement revenue method), considering the medium- and long-term contract electricity price and the clearing electricity price. The medium- and long-term contract electricity quantity is settled at the medium- and long-term electricity price, and the remaining electricity quantity is settled at the spot clearing electricity price, as shown in the following relational expression (4):

[0066] B(t) = ∑[E T,M (t) × EP M (t) + E T,spot (t) × EP spot (t)] (4)

[0067] In the formula: B(t) represents the power generation revenue of the water-wind-solar complementary system at time t; E T,M (t) represents the contract electricity quantity at time t; E T,spot (t) represents the spot electricity quantity exceeding the contract electricity quantity at time t; EP M (t) represents the medium- and long-term electricity price at time t; EP spot (t) represents the spot electricity price at time t.

[0068] Furthermore, the wind power generation E W (t), photovoltaic power generation E S (t), and hydropower generation E H (t) can be determined according to the forecast information set.

[0069] Among them, according to the wind speed sequence and the power characteristic curve of the wind turbine (this curve describes the relationship between the wind speed and the output power of the wind turbine), the power generation of the wind turbine under different wind speed conditions can be calculated, so as to determine the wind power generation E W (t) at each time period within the photovoltaic forecast cycle.

[0070] Further, based on the power generation characteristics of photovoltaic and photovoltaic cells, through relevant calculation formulas and models, and considering the influence of factors such as light intensity and temperature on the power generation efficiency of photovoltaic cells, the photovoltaic power generation E S (t) at different time periods can be estimated.

[0071] Further, by comprehensively considering factors such as the inflow discharge sequence, the water level change of the reservoir, and the efficiency of the water turbine, and combining the inflow discharge and the operation of the reservoir, the water volume used for power generation can be calculated. Further, by combining parameters such as the conversion efficiency of the water turbine, the corresponding hydropower generation E H (t) can be calculated.

[0072] Step S2022, determine the curtailment rate according to the wind power generation, photovoltaic power generation, and hydropower generation.

[0073] Among them, the curtailment rate is used to reflect the curtailment risk. Further, the curtailment risk refers to the curtailment of wind and light due to factors such as limited hydropower regulation capacity and blocked transmission channels, resulting in the inability to fully clear and consume wind and light.

[0074] Further, when using the curtailment rate to represent the curtailment situation, the curtailment rate is the ratio of the curtailed wind and light power to the wind and light power generation.

[0075] Specifically, by combining the wind power generation E W (t), the photovoltaic power generation E S (t), and the hydropower generation E H (t), the total power generation E T (t) of the wind-solar-hydro system at time t can be calculated, as shown in the following relational expression (5):

[0076] E T (t) = E W (t) + E S (t) + E H (t) (5)

[0077] Further, use the following relational expression (6) to calculate the cleared power E c (t) of the wind-solar-hydro system at time t:

[0078] E C (t) = E Y,M (t) + E T,spot (t) (6)

[0079] Further, use the following relational expression (7) to calculate the curtailed power E PC (t) of the wind-solar-hydro system at time t:

[0080]

[0081] Furthermore, the curtailment rate is calculated using the following relational expression (8):

[0082]

[0083] where: γ(T) represents the curtailment rate for the entire forecast period T.

[0084] Step S2023: Calculate the reservoir discharge flow rate based on the hydropower generation and determine the water abandonment risk.

[0085] Among them, the water abandonment risk refers to the phenomenon of water abandonment caused by large reservoir inflows, limited reservoir water storage conditions, or water level constraints.

[0086] Specifically, the reservoir inflow data, reservoir water storage capacity data, water level constraint data, and actual hydropower generation data for a certain operating period (such as one year, one quarter, etc.) can be collected.

[0087] Furthermore, based on data such as the reservoir inflow and head (water level difference), and combined with the efficiency of the power generation equipment, the theoretical hydropower generation without water abandonment can be calculated.

[0088] Furthermore, by subtracting the actual power generation from the theoretical power generation, the energy corresponding to the water volume that has not been converted into electrical energy due to water abandonment can be obtained. Then, through the conversion relationship between energy and water volume, the corresponding water abandonment volume can be calculated.

[0089] Furthermore, the corresponding reservoir discharge flow rate can be calculated by adding the water abandonment volume to the hydropower generation.

[0090] Finally, the corresponding water abandonment risk can be further determined based on the calculated reservoir discharge flow rate. Specifically, when the reservoir inflow is large, if the discharge flow rate can timely and fully discharge the excess water volume to keep the reservoir water level below the normal storage water level or flood limit water level, then the water abandonment risk will be reduced. On the contrary, if the discharge flow rate is limited and cannot discharge the excessive inflow in time, the reservoir water level will rise. When it exceeds the reservoir water storage capacity or water level constraint, water abandonment will occur and the water abandonment risk will increase.

[0091] Step S2024: Construct a benefit-risk index system based on the power generation benefit, curtailment rate, water abandonment risk, and multiple first operating risks.

[0092] Specifically, combining the obtained power generation benefit, curtailment rate, water abandonment risk, and multiple first operating risks such as unit ramp-up risk and vibration zone risk, the corresponding benefit-risk index system can be constructed and formed.

[0093] Step S203: Based on the forecast information set and the benefit-risk index system, construct a two-step optimal scheduling model for the water-wind-solar complementary system.

[0094] Specifically, the above step S203 includes:

[0095] Step S2031: Based on the benefit-risk index system, determine the first objective function and the second objective function respectively.

[0096] Among them, the first objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the entire forecast period within the forecast cycle; the second objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the day-ahead stage within the forecast cycle.

[0097] Specifically, the first objective function is used to maximize the total power generation revenue and minimize the curtailment risk during the day-ahead to future stage, i.e., the entire forecast period, as shown in the following relational expression (9):

[0098]

[0099] In the formula: F1 represents the total power generation revenue objective function; F2 represents the curtailment risk objective function.

[0100] Furthermore, the second objective function is used to maximize the total power generation revenue and minimize the curtailment risk during the day-ahead stage, as shown in the following relational expression (10):

[0101]

[0102] In the formula: t represents the day-ahead hour period; T represents 24 hours.

[0103] Step S2032: Based on the forecast information set, the first objective function and the second objective function, construct a two-step optimal scheduling model for the water-wind-solar complementary system.

[0104] Specifically, based on the forecast information set, constructing a two-step optimal scheduling model for the water-wind-solar complementary system in combination with the forecast information set can provide a scientific mathematical framework for the scheduling decision-making of the water-wind-solar complementary system at different time scales (the entire forecast period, the day-ahead stage), and thus can more reasonably allocate the power outputs of hydropower, wind power and photovoltaic power, balancing the benefits and risks of the operation of the water-wind-solar complementary system.

[0105] In some alternative embodiments, the above step S2032 includes:

[0106] Step a1: Obtain the first constraint condition set and the second constraint condition set.

[0107] Step a2: Based on the first constraint condition set, use the forecast information set and the first objective function to construct the first optimal scheduling model for the water-wind-solar complementary system during the entire forecast period.

[0108] Step a3: Based on the first set of constraint conditions and the second set of constraint conditions, using the prediction information set and the second objective function, construct the second optimized scheduling model of the water-wind-solar complementary system for the day-ahead stage.

[0109] Step a4: Determine the two-step optimized scheduling model of the water-wind-solar complementary system according to the first optimized scheduling model of the water-wind-solar complementary system and the second optimized scheduling model of the water-wind-solar complementary system.

[0110] Among them, the first set of constraint conditions includes water volume balance constraint conditions, power balance constraint conditions, flow constraint conditions, water level constraint conditions, water level fluctuation constraint conditions, head constraint conditions, and output constraint conditions, as shown in the following relational expression (11):

[0111]

[0112] In the formula: V(t) and V(t - 1) respectively represent the reservoir storage at time t and time t - 1; Q(t) and q(t) respectively represent the inflow and outflow of the reservoir at time t; Δt represents the time interval; q min (t) and q max (t) respectively represent the minimum and maximum values of the reservoir outflow at time t; Z(t) represents the reservoir water level at time t; Z min (t) and Z max (t) respectively represent the lowest and highest water levels of the reservoir at time t; ΔZ represents the allowable daily water level fluctuation; h(t) represents the reservoir head at time t; h min (t) and h max (t) respectively represent the minimum and maximum values of the reservoir head at time t; N H (t) represents the hydropower output at time t; and respectively represent the minimum and maximum values of the hydropower output at time t.

[0113] Furthermore, the second set of constraint conditions includes unit ramp rate constraint conditions, vibration zone constraint conditions, and unit start-stop constraint conditions, as shown in the following relational expression (12):

[0114]

[0115] In the formula: represents the output of the hydropower unit at time t; N VZ represents the upper limit of the vibration zone of the hydropower unit; N ramp represents the unit ramp rate constraint; U on represents the number of online operation periods of the hydropower unit; U off represents the number of offline periods of the hydropower unit; and respectively represent the minimum number of online operation periods of the hydropower unit and the minimum number of offline periods of the hydropower unit.

[0116] Specifically, based on the first set of constraint conditions, information such as the reservoir inflow sequence, wind speed sequence, and photovoltaic sequence in the forecast information set is combined with the first objective function to construct a corresponding optimal scheduling model for the water-wind-solar complementary system.

[0117] For example, according to the reservoir inflow sequence and the water balance constraint conditions, the water storage volume and the discharge flow of the reservoir at different time periods are determined, thereby affecting the hydropower output.

[0118] Furthermore, the wind power and photovoltaic power generation are determined by combining the wind speed and photovoltaic sequence, and then substituted into the first objective function for calculation.

[0119] In the above manner, on the premise of meeting the first set of constraint conditions, the operation of the water-wind-solar complementary system during the entire forecast period is optimized, and a corresponding optimal scheduling model for the water-wind-solar complementary system is constructed to maximize the total power generation benefit and minimize the curtailment risk of the water-wind-solar complementary system during the entire forecast period.

[0120] Furthermore, when considering the day-ahead stage, in addition to following the basic physical and equipment operation constraints, more detailed constraint conditions such as unit ramp rate, vibration area, and unit start-stop need to be satisfied. Therefore, on the basis of the first set of constraint conditions, a second set of constraint conditions is added.

[0121] Furthermore, under the constraints of the first set of constraint conditions and the second set of constraint conditions, the power generation of each energy source is determined by using the forecast information, substituted into the second objective function for optimization calculation, and a corresponding second optimal scheduling model for the water-wind-solar complementary system is constructed, realizing the maximization of the power generation benefit and the minimization of the curtailment rate of the water-wind-solar complementary system in the day-ahead stage.

[0122] Finally, the first optimal scheduling model for the water-wind-solar complementary system and the second optimal scheduling model for the water-wind-solar complementary system constructed are combined to form a two-step optimal scheduling model for the water-wind-solar complementary system. Furthermore, the two-step optimal scheduling model for the water-wind-solar complementary system optimizes the system in stages, first determining a general operation framework from the macroscopic perspective of the entire forecast period, and then making refined adjustments according to more accurate information and stricter constraints in the day-ahead stage, so as to be able to achieve comprehensive and effective scheduling of the water-wind-solar complementary system at different time scales.

[0123] Step S204: Solve the two-step optimal scheduling model for the water-wind-solar complementary system to obtain the target clearing values for each time period within the day in the forecast cycle of the water-wind-solar complementary system under the forecast market. For details, please refer to Figure 1 Step S104 of the illustrated embodiment, which will not be elaborated here.

[0124] The optimal scheduling method for a water-wind-solar complementary system to participate in the electricity market provided by this embodiment can quantify and evaluate the revenue and risk status of the water-wind-solar complementary system under different operating conditions by combining and settling the forecast information set to determine indicators such as power generation benefits and water abandonment risks. At the same time, by determining the curtailment rate to reflect the risk of curtailment, it can intuitively reflect the accommodation situation of wind and solar power generation, facilitate timely adjustment of the scheduling strategy, reduce the phenomena of wind and solar curtailment caused by the uncertainty of wind and solar, improve the utilization efficiency of renewable energy, and give full play to the advantages of the water-wind-solar complementary system. Further, by separately determining the objective functions representing the total power generation revenue and curtailment risk in different stages, the water-wind-solar complementary system can be optimized from two perspectives of economic revenue and risk control, enabling the system to effectively reduce the risks brought by market uncertainty while pursuing power generation benefits, and improving the stability and sustainability of the system in the spot market. Further, by obtaining different constraint sets and combining the forecast information set and the objective function to construct the optimal scheduling model for different stages, various actual limiting factors in the operation process of the water-wind-solar complementary system are fully considered, and thus the constructed model is closer to the engineering reality, improving the feasibility and operability of the scheduling plan. Further, by constructing the model in stages, first determining the overall operation framework from the macroscopic perspective of the entire forecasting period, and then refining and optimizing in the day-ahead stage, it can more accurately respond to market changes and internal uncertainties of the system, improving the scheduling efficiency and resource allocation effect of the water-wind-solar complementary system.

[0125] In this embodiment, an optimal scheduling method for a water-wind-solar complementary system to participate in the electricity market is provided, which can be used in electronic devices such as computers, mobile phones, and tablet computers. Figure 3 It is a flowchart of the optimal scheduling method for a water-wind-solar complementary system to participate in the electricity market according to an embodiment of the present invention, as Figure 3 shown. The process includes the following steps:

[0126] Step S301, obtain the forecast information set, settlement revenue method, and multiple first operating risks of the water-wind-solar complementary system. For details, please refer to Figure 1 step S101 of the embodiment shown, which will not be elaborated here.

[0127] Step S302, based on the forecast information set, settlement revenue method, and multiple first operating risks, construct a benefit-risk index system. For details, please refer to Figure 2 step S202 of the embodiment shown, which will not be elaborated here.

[0128] Step S303, based on the forecast information set and the benefit-risk index system, construct a two-step optimal scheduling model for the water-wind-solar complementary system. For details, please refer to Figure 2 step S203 of the embodiment shown, which will not be elaborated here.

[0129] Step S304: Solve the two-step optimal scheduling model of the water-wind-solar complementary system to obtain the target clearing values for each time period within the forecast period in the forecast market for the water-wind-solar complementary system.

[0130] Specifically, the above step S304 includes:

[0131] Step S3041: Take the water level at each moment as the decision variable, solve the two-step optimal scheduling model of the water-wind-solar complementary system on a daily scale, and obtain the initial clearing values of the water-wind-solar complementary system within the forecast period.

[0132] Specifically, in the water-wind-solar complementary system, the change of the reservoir water level directly affects the power generation of hydropower. Because the water level is related to the working head of the water turbine, and the head determines the magnitude of hydropower output. At the same time, the water level is also closely connected to the water storage capacity of the reservoir, affecting the water balance and the schedulability of hydropower.

[0133] Therefore, for optimal scheduling on a daily scale, taking the water levels at each moment {Z0, Z1, …, Z D} as the decision variables, and taking F1 and F2 in the above relation (9) as the optimization objectives, use the dynamic programming method or intelligent algorithm to solve the optimization model and obtain the initial clearing values of the water-wind-solar complementary system within the forecast period.

[0134] For example, when using the particle swarm algorithm to solve, given a set of initial decision variables {Z0, Z1, …, Z D}, calculate the reservoir discharge q(t) and hydropower output N H (t) through the water level data at each moment and the forecasted inflow sequence, as shown in the following relation (13):

[0135]

[0136] In the formula: k represents a coefficient used to comprehensively reflect relevant parameters such as the conversion efficiency of the water turbine generator set.

[0137] Furthermore, based on the predicted electricity price data, predicted wind and solar power outputs, and calculated hydropower output in the centralized prediction of forecast information, obtain the objective function F1 through the above relations (4) and (9), obtain the objective function F2 through the above relations (8) and (9), and then iterate repeatedly until the optimal objective is found.

[0138] Step S3042: Take the hydropower output for each time period within the day as the decision variable, and with the initial clearing value as the constraint, solve the two-step optimal scheduling model of the water-wind-solar complementary system to obtain the target clearing values for each time period within the day in the forecast period in the forecast market for the water-wind-solar complementary system.

[0139] Specifically, for optimal scheduling on an intra-day scale, and taking the hydropower output for each time period within the day {N H (1), NH (2), …, N H (T)} are decision variables. Constrained by the optimized initial clearing value in step S3041, a dynamic programming method or intelligent algorithm is used to solve the optimization model and obtain the target clearing values for each time period within the prediction cycle of the water-wind-solar complementary system.

[0140] For example, when using the particle swarm optimization algorithm to solve, a set of initial decision variables {N H (1), N H (2), …, N H (T)} are given. Based on the hydropower output values for each time period within the day, the predicted intra-day electricity price data, and the predicted wind and solar power output within the day, the objective function F3 is obtained through the above relationships (4) and (10), and the objective function F4 is obtained through the above relationships (8) and (10). Then, iterative calculations are performed until the optimal objective is found.

[0141] The optimized scheduling method for the water-wind-solar complementary system participating in the electricity market provided in this embodiment uses the water level at each moment as a decision variable and solves the model on a daily scale to obtain the initial clearing value. It can plan the power generation capacity and regulation effect of hydropower from a long-term perspective, and then reasonably arrange the reservoir water storage and release strategies, relieve the regulation pressure faced by hydropower in regulating wind and solar fluctuations and itself, and improve the utilization efficiency of hydropower resources. Further, using the hydropower output for each time period within the day as a decision variable and further solving with the obtained initial clearing value as a constraint, it can flexibly adjust the hydropower output according to the real-time market electricity price and wind and solar power generation conditions on an intra-day scale, realizing the real-time complementarity of water, wind, and solar, and improving the response speed and power generation efficiency of the water-wind-solar complementary system in the spot market.

[0142] In one example, as Figure 4 shown, a water-wind-solar integrated scheduling method in the context of the electricity market is provided. This method includes the following steps:

[0143] Step 1: Obtain the prediction information, including the predicted multi-time scale electricity price sequence, the incoming flow sequence, the wind speed sequence, and the photovoltaic sequence, as shown in the above relationships (1) to (3).

[0144] Step 2: Establish an index system for benefits and risks.

[0145] 1) Power generation benefit: The power generation benefit is the revenue value of the water-wind-solar multi-energy complementary system. The revenue is settled according to the two-part settlement model, considering the medium- and long-term contract electricity price and the clearing electricity price. The medium- and long-term contract electricity quantity is settled according to the medium- and long-term electricity price, and the remaining electricity quantity is settled according to the spot clearing electricity price, as shown in the above relationship (4).

[0146] 2) Risk indicators include the curtailment rate, the unit ramp-up risk, the vibration area, and the water abandonment.

[0147] Abandoned power risk: Due to factors such as limited hydropower regulation capacity and blocked transmission channels, wind and light cannot be fully cleared and absorbed, resulting in wind and light abandonment. The abandoned power rate is used to represent the situation of abandoned power, which is the ratio of the abandoned wind and light power to the wind and light power generation, and is calculated through the above relationships (5) to (8).

[0148] Abandoned water risk: When the reservoir inflow is large, and due to limited reservoir water storage conditions or water level constraints, the phenomenon of abandoned water occurs.

[0149] Step 3: Establish a two-step optimal scheduling model for the water-wind-light complementary system.

[0150] 1) Step 1: Two-stage optimization method to determine the day-ahead output value that maximizes the benefit of the complementary system from the day before the decision to the future.

[0151] Among them, the objective function is to maximize the total power generation revenue and minimize the abandoned power risk in the day-ahead to future stages, as shown in the above relationship (9).

[0152] Constraints: water balance, power balance, flow constraint, water level constraint, water level variation range, head constraint, output constraint, as shown in the above relationship (11).

[0153] 2) Step 2: Day-ahead optimization. Based on information such as day-ahead forecast electricity prices, optimize the output process of water, wind, and light with the goal of maximizing revenue.

[0154] Among them, the objective function is to maximize the power generation revenue and minimize the abandoned power rate of the day-ahead water-wind-light complementary system, as shown in the above relationship (10).

[0155] Constraints: In addition to the constraints in Step 1, it also includes unit ramp rate constraint, vibration zone constraint, unit start-stop constraint, etc., as shown in the above relationship (12).

[0156] Step 4: Model solution: Two-step optimization method.

[0157] In Step 1, optimize the scheduling on a daily scale. With the water levels at each moment {Z0, Z1, …, Z D} as decision variables, and F1 and F2 in the above relationship (9) as optimization objectives, use dynamic programming method or intelligent algorithm to solve the optimization model.

[0158] In Step 2, optimize the scheduling on an intraday scale. With the hydropower output at each intraday period {N H (1), N H (2), …, N H (T)} as decision variables, and the initial clearing value optimized in Step 1 as the constraint, use dynamic programming method or intelligent algorithm to solve the optimization model.

[0159] The integrated scheduling method of water, wind and light under the background of the power market provided in this example makes decisions on the day-ahead hydropower output by formulating the day-ahead hydropower output - hydropower benefit curve and the curtailment risk curve, analyzes the benefits and risks of the water-wind-light complementary system under different hydropower output conditions, solves the problem of unbalanced benefits and risks of the water-wind-light complementary system, improves the power generation benefits of water, wind and light under the background of the power market, reduces the risks of the complementary system, and further provides a theoretical basis for the integrated water-wind-light bidding strategy. Therefore, through this example, the obtained decision-making diagram is more effective and more adaptable to the actual integrated water-wind-light multi-energy complementary scheduling project.

[0160] This embodiment provides an optimized scheduling device for a water-wind-light complementary system to participate in the power market, as Figure 5 shown. The device includes:

[0161] An acquisition module 501, configured to acquire a forecast information set, a settlement revenue method, and multiple first operation risks of the water-wind-light complementary system, where the forecast information set includes a forecast multi-time scale electricity price sequence, an inflow sequence, a wind speed sequence, and a photovoltaic sequence.

[0162] A first construction module 502, configured to construct a benefit-risk index system based on the forecast information set, the settlement revenue method, and the multiple first operation risks.

[0163] A second construction module 503, configured to construct a two-step optimized scheduling model for the water-wind-light complementary system based on the forecast information set and the benefit-risk index system.

[0164] A solving module 504, configured to solve the two-step optimized scheduling model for the water-wind-light complementary system to obtain the target clearing values of each time period within the forecast period in the predicted market for the water-wind-light complementary system.

[0165] In some alternative embodiments, the first construction module 502 includes:

[0166] A first determination sub-module, configured to determine the power generation benefit, the wind power generation amount, the photovoltaic power generation amount, and the hydropower generation amount based on the forecast information set and the settlement revenue method.

[0167] A second determination sub-module, configured to determine the curtailment rate according to the wind power generation amount, the photovoltaic power generation amount, and the hydropower generation amount, where the curtailment rate is used to reflect the curtailment risk.

[0168] A third determination sub-module, configured to calculate the reservoir discharge flow and determine the water abandonment risk according to the hydropower generation amount.

[0169] A first construction sub-module, configured to construct a benefit-risk index system according to the power generation benefit, the curtailment rate, the water abandonment risk, and the multiple first operation risks.

[0170] In some alternative embodiments, the second construction module 503 includes:

[0171] A fourth determination sub-module, configured to respectively determine a first objective function and a second objective function based on a benefit-risk index system, where the first objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the entire foreseeable period within the forecast cycle, and the second objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the day-ahead stage within the forecast cycle.

[0172] A second construction sub-module, configured to construct a two-step optimal scheduling model for the water-wind-solar complementary system based on a forecast information set, the first objective function, and the second objective function.

[0173] In some alternative embodiments, the second construction sub-module includes:

[0174] An acquisition unit, configured to acquire a first constraint condition set and a second constraint condition set.

[0175] A first construction unit, configured to construct a first optimal scheduling model for the water-wind-solar complementary system during the entire foreseeable period based on the first constraint condition set, using the forecast information set and the first objective function.

[0176] A second construction unit, configured to construct a second optimal scheduling model for the water-wind-solar complementary system during the day-ahead stage based on the first constraint condition set and the second constraint condition set, using the forecast information set and the second objective function.

[0177] A determination unit, configured to determine a two-step optimal scheduling model for the water-wind-solar complementary system according to the first optimal scheduling model for the water-wind-solar complementary system and the second optimal scheduling model for the water-wind-solar complementary system.

[0178] In some alternative embodiments, the solution module 504 includes:

[0179] A first solution sub-module, configured to solve the two-step optimal scheduling model for the water-wind-solar complementary system on a daily scale with the water level at each moment as the decision variable, to obtain an initial clearing value of the water-wind-solar complementary system within the forecast cycle.

[0180] A second solution sub-module, configured to solve the two-step optimal scheduling model for the water-wind-solar complementary system with the hydropower output at each intra-day period as the decision variable and the initial clearing value as the constraint, to obtain the target clearing value of each intra-day period of the water-wind-solar complementary system within the forecast cycle under the prediction market.

[0181] In some alternative embodiments, the first constraint condition set includes a water volume balance constraint condition, a power balance constraint condition, a flow constraint condition, a water level constraint condition, a water level variation constraint condition, a head constraint condition, and an output constraint condition; the second constraint condition set includes a unit ramp constraint condition, a vibration zone constraint condition, and a unit start-stop constraint condition.

[0182] The further function descriptions of the above-mentioned modules and units are the same as those in the corresponding embodiments above, and will not be elaborated here.

[0183] In this embodiment, the optimal dispatching device for the water-wind-solar complementary system to participate in the electricity market is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0184] An embodiment of the present invention further provides a computer device having the above Figure 5 shown optimal dispatching device for the water-wind-solar complementary system to participate in the electricity market.

[0185] Please refer to Figure 6 , Figure 6 which is a schematic structural diagram of a computer device provided by an optional embodiment of the present invention. As Figure 6 shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways according to needs. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (such as an array of servers, a set of blade servers, or a multi-processor system). Figure 6 One processor 10 is taken as an example in

[0186] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The above programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0187] Among them, the memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiments.

[0188] The memory 20 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device and the like. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 may optionally include a memory remotely provided with respect to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above-mentioned network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0189] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, a hard disk, or a solid-state drive; the memory 20 may further include a combination of the above types of memory.

[0190] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0191] Embodiments of the present invention also provide a computer-readable storage medium. The methods according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and to be stored in a local storage medium, so that the methods described herein can be stored in such software processes on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disc, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium may further include a combination of the above types of memory. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods shown in the above embodiments are implemented.

[0192] A part of the present invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can call or provide the methods and / or technical solutions according to the present invention through the operations of the computer. Those skilled in the art should understand that the forms in which computer program instructions exist in a computer-readable medium include but are not limited to source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include but are not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0193] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An optimal scheduling method for a water-wind-solar complementary system to participate in the electricity market, characterized in that, The method includes: Obtaining a forecast information set, a settlement revenue method, and multiple first operation risks of a water-wind-solar complementary system, where the forecast information set includes a forecast multi-time scale electricity price sequence, an incoming flow sequence, a wind speed sequence, and a photovoltaic sequence; Constructing a benefit-risk index system based on the forecast information set, the settlement revenue method, and the multiple first operation risks; Constructing a two-step optimal scheduling model for the water-wind-solar complementary system based on the forecast information set and the benefit-risk index system; Solving the two-step optimal scheduling model for the water-wind-solar complementary system to obtain the target clearing value of each time period within the day during the forecast period in the forecast market for the water-wind-solar complementary system.

2. The method according to claim 1, wherein Constructing a benefit-risk index system based on the forecast information set, the settlement revenue method, and the multiple first operation risks, including: Determining the power generation benefit, wind power generation, photovoltaic power generation, and hydraulic power generation based on the forecast information set and the settlement revenue method; Determining the curtailment rate according to the wind power generation, the photovoltaic power generation, and the hydraulic power generation, where the curtailment rate is used to reflect the curtailment risk; Calculating the reservoir discharge flow and determining the water abandonment risk according to the hydraulic power generation; Constructing the benefit-risk index system according to the power generation benefit, the curtailment rate, the water abandonment risk, and the multiple first operation risks.

3. The method according to claim 1, wherein Constructing a two-step optimal scheduling model for the water-wind-solar complementary system based on the forecast information set and the benefit-risk index system, including: Respectively determining a first objective function and a second objective function based on the benefit-risk index system, where the first objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the entire foreseeable period within the forecast period, and the second objective function is used to characterize the total power generation revenue and curtailment risk of the water-wind-solar complementary system during the day-ahead stage within the forecast period; Constructing the two-step optimal scheduling model for the water-wind-solar complementary system based on the forecast information set, the first objective function, and the second objective function.

4. The method according to claim 3, characterized in that, Constructing the two-step optimal scheduling model for the water-wind-solar complementary system based on the forecast information set, the first objective function, and the second objective function, including: Obtaining a first constraint condition set and a second constraint condition set; Constructing a first optimal scheduling model for the water-wind-solar complementary system during the entire foreseeable period based on the first constraint condition set, using the forecast information set and the first objective function; Constructing a second optimal scheduling model for the water-wind-solar complementary system during the day-ahead stage based on the first constraint condition set and the second constraint condition set, using the forecast information set and the second objective function; Determining the two-step optimal scheduling model for the water-wind-solar complementary system according to the first optimal scheduling model for the water-wind-solar complementary system and the second optimal scheduling model for the water-wind-solar complementary system.

5. The method according to claim 1, wherein Solving the two-step optimal scheduling model for the water-wind-solar complementary system to obtain the target clearing value of each time period within the day during the forecast period in the forecast market for the water-wind-solar complementary system, including: Taking the water level at each moment as the decision variable, solve the two-step optimal scheduling model of the water-wind-solar complementary system on a daily scale to obtain the initial clearing value of the water-wind-solar complementary system within the forecast period; Taking the hydropower output at each time period within a day as the decision variable, and using the initial clearing value as a constraint, solve the two-step optimal scheduling model of the water-wind-solar complementary system to obtain the target clearing value of each time period within the day of the water-wind-solar complementary system within the forecast period in the prediction market.

6. The method according to claim 4, wherein the first set of constraint conditions includes a water volume balance constraint condition, a power balance constraint condition, a flow constraint condition, a water level constraint condition, a water level amplitude constraint condition, a water head constraint condition, and an output constraint condition; the second set of constraint conditions includes a unit ramp rate constraint condition, a vibration zone constraint condition, and a unit start-stop constraint condition.

7. An optimal dispatching device for a water-wind-solar complementary system to participate in the electricity market, characterized in that, The device includes: an acquisition module, configured to acquire a forecast information set, a settlement revenue method, and multiple first operation risks of a water-wind-solar complementary system, wherein the forecast information set includes a forecast multi-time scale clearing electricity price sequence, an incoming flow sequence, a wind speed sequence, and a photovoltaic sequence; a first construction module, configured to construct a benefit-risk index system based on the forecast information, the settlement revenue method, and the multiple first operation risks; a second construction module, configured to construct a two-step optimal scheduling model of the water-wind-solar complementary system based on the forecast information set and the benefit-risk index system; a solving module, configured to solve the two-step optimal scheduling model of the water-wind-solar complementary system to obtain the target clearing value of each time period within the day of the water-wind-solar complementary system within the forecast period in the prediction market.

8. A computer device, characterized in that, including: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the optimal scheduling method for the water-wind-solar complementary system to participate in the power market according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, A computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the optimal scheduling method for the water-wind-solar complementary system to participate in the power market according to any one of claims 1 to 6.

10. A computer program product, characterized in that, including computer instructions, the computer instructions are used to cause a computer to execute the optimal scheduling method for the water-wind-solar complementary system to participate in the power market according to any one of claims 1 to 6.

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