CN114498625A - Income prediction method and system of wind-solar-storage integrated power supply - Google Patents

The invention provides a method and a system for predicting profits of a wind-solar-energy storage integrated power supply, wherein the method comprises the steps of acquiring operation plan data of wind power, photovoltaic and energy storage devices in the wind-solar-energy storage integrated system; calculating system expected revenue and system expected cost according to the operation plan data, and outputting the difference between the system expected revenue and the system expected cost as system expected income; and judging whether the system expected income meets a preset constraint standard or not through a preset constraint model, and if so, outputting the system expected income as an income prediction result of the wind-solar-energy-storage integrated power supply. According to the method, the influence of the new energy prediction deviation on the expected transaction income and the expected transaction risk is fully considered, and the transaction risk constraint under the new energy prediction deviation based on the condition value risk is constructed, so that the declaration strategy is adaptive to the new energy prediction deviation requirement.

一种风光储一体化电源的收益预测方法及系统A revenue prediction method and system for integrated wind-solar-storage power supply

技术领域technical field

本发明涉及电力调度运行技术领域，特别是涉及一种风光储一体化电源的收益预测方法及系统。The invention relates to the technical field of power dispatching and operation, in particular to a method and system for predicting revenue of an integrated power source of wind, solar and storage.

背景技术Background technique

为促进新能源消纳，不断加快风光水火储、源网荷储两个一体化系统建设，以挖掘多类型电源互补调节潜力。风光储一体化系统就是上述两个一体化系统的典型形态，其特点在于通过将风电、光伏、储能等三类电源整合，形成一体化系统，一体化系统运营商通过挖掘三类电源运行调节潜力，参与大电网响应调节，提升其运营收益，并促进全网新能源消纳。In order to promote the consumption of new energy, we will continue to speed up the construction of two integrated systems of wind-solar, water-fired storage and source-grid-load storage, so as to tap the potential for complementary regulation of multiple types of power sources. The wind-solar-storage integrated system is a typical form of the above two integrated systems. It is characterized by integrating three types of power sources such as wind power, photovoltaics, and energy storage to form an integrated system. potential, participate in the response adjustment of the large power grid, improve its operating income, and promote the consumption of new energy in the whole network.

与水电、火电等常规电源相比，风光储一体化系统因新能源占比较高，受新能源预测偏差影响，现货市场交易竞价面临更大的挑战。特别是在日前现货市场交易中，风电、光伏等新能源预测偏差较日内现货市场更大，若申报策略制定不合理，当出现较大预测偏差时，不仅可能不利于一体化系统新能源消纳，而且可能造成一体化系统运营商承受较大经济损失。Compared with conventional power sources such as hydropower and thermal power, the wind-solar-storage integrated system has a higher proportion of new energy sources and is affected by the forecast deviation of new energy sources, so the spot market transaction bidding faces greater challenges. Especially in the spot market transactions a day ago, the forecast deviation of new energy such as wind power and photovoltaics is larger than that of the spot market in the day. If the declaration strategy is unreasonable, when there is a large forecast deviation, it may not only be detrimental to the new energy consumption of the integrated system , and may cause the integrated system operator to suffer greater economic losses.

目前的风光储一体化系统日前市场申报策略制定主要考虑预期交易收益最大化作为申报决策目标，在此基础上综合考虑一体化系统自身各类电源运行特性约束等构建申报决策模型，作为一体化系统运营商决策依据。目前研究中预期交易收益测算中主要考虑现货市场交易价格的不确定性影响，以多场景日前市场交易价格下交易收益期望最大化为目标，适应市场交易价格波动对交易结果的影响。The current day-ahead market declaration strategy formulation of the integrated wind-solar-storage system mainly considers the maximization of expected transaction revenue as the declaration decision-making goal. Operator decision-making basis. The current study mainly considers the uncertainty of the spot market transaction price in the calculation of the expected transaction income, aiming at maximizing the expected transaction income under the multi-scenario day-ahead market transaction price, and adapting to the impact of market transaction price fluctuations on the transaction results.

现有的研究仅考虑了风光储一体化系统所面临的现货市场价格波动影响，且仅考虑价格波动对预期收益的影响，对可能存在的交易风险考虑不全面。此外，与火电、水电等常规电源相比，风光储一体化系统中风电、光伏等新能源装机规模较高，新能源预测偏差对交易结果的影响显著。现有的预测方法对上述问题考虑不充分，可能造成新能源预测偏差产生的较大风险。The existing research only considers the impact of spot market price fluctuations faced by the integrated wind-solar storage system, and only considers the impact of price fluctuations on expected returns, and does not fully consider the possible transaction risks. In addition, compared with conventional power sources such as thermal power and hydropower, the installed capacity of wind power, photovoltaics and other new energy sources in the wind-solar-storage integrated system is relatively high, and the forecast deviation of new energy sources has a significant impact on the transaction results. Existing forecasting methods do not fully consider the above issues, which may lead to a greater risk of deviations in new energy forecasts.

发明内容SUMMARY OF THE INVENTION

本发明的目的在于，提出一种风光储一体化电源的收益预测方法及系统，解决现有方法对印象因素考虑不充分，造成新能源预测偏差较大的技术问题。The purpose of the present invention is to propose a method and system for forecasting revenue of integrated wind-solar-storage power supply, so as to solve the technical problem that the existing method does not fully consider the impression factor, resulting in a large deviation of the new energy forecast.

一方面，提供一种风光储一体化电源的收益预测方法，包括：On the one hand, a revenue forecasting method for integrated wind-solar-storage power supply is provided, including:

获取风光储一体化系统中风电、光伏、储能装置的运行计划数据；Obtain the operation plan data of wind power, photovoltaic and energy storage devices in the wind-solar-storage integrated system;

根据所述运行计划数据计算系统预期营收和系统预期成本，并将所述系统预期营收与所述系统预期成本之差输出为系统预期收益；Calculate the expected revenue of the system and the expected cost of the system according to the operation plan data, and output the difference between the expected revenue of the system and the expected cost of the system as the expected revenue of the system;

通过预设的约束模型判断所述系统预期收益是否满足预设的约束标准，若满足，则输出所述系统预期收益为风光储一体化电源的收益预测结果。It is judged by a preset constraint model whether the expected revenue of the system meets the preset constraint criteria, and if so, the expected revenue of the system is output as the revenue prediction result of the integrated wind-solar-storage power supply.

优选地，所述风电、光伏、储能装置的运行计划数据至少包括：日前现货预测场景下的市场价格，日前现货市场价格预测场景数，一体化系统时段交换功率，风电预期成本，光伏预期成本，储能预期成本，风电多场景预测的场景数，场景发生概率，场景下风电的发电功率，风电预期成本函数的二次项系数，风电预期成本函数的一次项系数，风电预期成本函数的常数项系数，光伏多场景预测的场景数，场景光伏的发电功率，光伏预期成本函数的二次项系数，光伏预期成本函数的一次项系数，光伏预期成本函数的常数项系数；储能装置时段净交换功率，储能预期成本函数的二次项系数，储能预期成本函数的一次项系数，储能预期成本函数的常数项系数。Preferably, the operation plan data of the wind power, photovoltaic and energy storage devices includes at least: market price under the spot forecast scenario a day before, the number of spot market price forecast scenarios a day ago, the exchange power of the integrated system during the period, the expected cost of wind power, and the expected cost of photovoltaics , the expected cost of energy storage, the number of scenarios predicted by multiple scenarios of wind power, the probability of occurrence of the scenario, the generated power of the wind power in the scenario, the quadratic coefficient of the expected cost function of wind power, the coefficient of the first order of the expected cost function of wind power, the constant of the expected cost function of wind power term coefficient, the number of scenarios predicted by PV multi-scenarios, the generated power of PV in the scenario, the quadratic term coefficient of the PV expected cost function, the linear term coefficient of the PV expected cost function, the constant term coefficient of the PV expected cost function; Exchange power, quadratic term coefficient of energy storage expected cost function, first-order term coefficient of energy storage expected cost function, constant term coefficient of energy storage expected cost function.

优选地，根据以下公式计算系统预期营收：Preferably, the expected revenue of the system is calculated according to the following formula:

其中，I^IS表示一体化系统预期营收，ΔT表示时段间隔，NT表示时段数，

表示日前现货预测场景ps下时段t的市场价格，NPS表示日前现货市场价格预测场景数，P_t ^IS表示一体化系统时段交换功率。Among them, I ^IS is the expected revenue of the integrated system, ΔT is the time interval, NT is the number of time periods,

Represents the market price in the period t under the spot forecast scenario ps a day ago, NPS represents the number of forecast scenarios for the spot market price a day ago, and P _t ^IS represents the exchange power of the integrated system during the period.

优选地，根据以下公式计算系统预期成本：Preferably, the expected cost of the system is calculated according to the following formula:

C^IS＝C_w+C_p+C_s C ^IS =C _w +C _p +C _s

其中，C^IS表示一体化系统预期成本，C_w表示风电预期成本，C_p表示光伏预期成本，C_s表示储能预期成本，NWS表示风电多场景预测的场景数，ρ_ws表示场景ws发生概率，

表示场景ws下风电时段t的发电功率，a_w表示风电预期成本函数的二次项系数，b_w表示风电预期成本函数的一次项系数，c_w表示风电预期成本函数的常数项系数；NPS 表示光伏多场景预测的场景数，ρ_ps表示场景ps发生概率，

表示场景ps下光伏时段t的发电功率，a_p表示光伏预期成本函数的二次项系数，b_p表示光伏预期成本函数的一次项系数，c_p表示光伏预期成本函数的常数项系数；P_t ^S表示储能装置时段净交换功率，a_s储能预期成本函数的二次项系数，b_s储能预期成本函数的一次项系数，c_s表示储能预期成本函数的常数项系数。Among them, C ^IS is the expected cost of the integrated system, C _w is the expected cost of wind power, C _p is the expected cost of photovoltaics, C _s is the expected cost of energy storage, NWS is the number of scenarios predicted by multiple scenarios of wind power, ρ _ws is the probability of occurrence of scenario ws ,

Represents the generation power of wind power in the wind power period t under the scenario ws, a _w represents the quadratic term coefficient of the expected wind power cost function, b _w represents the first-order term coefficient of the wind power expected cost function, c _w represents the constant term coefficient of the wind power expected cost function; NPS represents Number of scenarios predicted by PV multi-scenarios, ρ _ps represents the occurrence probability of scenario ps,

Represents the generated power of the photovoltaic period t under the scene ps, a _p represents the quadratic term coefficient of the photovoltaic expected cost function, b _p represents the first order term coefficient of the photovoltaic expected cost function, c _p represents the constant term coefficient of the photovoltaic expected cost function; P _t ^S represents the net exchange power of the energy storage device during the period, a _s is the quadratic coefficient of the expected cost function of energy storage, b _s is the first-order coefficient of the expected cost function of energy storage, and c _s represents the constant term coefficient of the expected cost function of energy storage.

优选地，所述预设的约束模型具体包括：Preferably, the preset constraint model specifically includes:

Max I^NIS Max I ^NIS

其中，max表示最大化规划问题，s.t.表示约束条件，P_t ^W,S表示风电时段t计划发电出力，P_t ^W,A表示风电时段t计划弃风出力，P_t ^P,S表示光伏时段t计划发电出力，P_t ^P,A表示光伏时段t计划弃光出力，P_t ^S,D表示储能装置时段t放电功率，P_t ^S,C表示储能装置时段t充电功率，P^SDmax表示该储能装置最大放电功率，P^SCmax表示该储能装置最大充电功率，

表示储能装置时段t放电状态变量，

表示储能装置时段t充电状态变量，

表示储能装置初始储电量，E^Smax表示储能装置最大储电量，E^Smin表示储能装置最小储电量，η_S表示折算至充电侧的损耗系数，E^Aset表示弃风弃光电量限值，

表示风电、光伏新能源整体场景wps下的发电功率，ρ_wps表示新能源随机变量场景wps发生概率， NWPS表示新能源随机变量场景数，[]⁺表示取正函数。Among them, max represents the maximization planning problem, st represents the constraint condition, P _t ^{W, S} represents the planned power generation output of the wind power period t, P _t ^{W, A} represents the planned wind curtailment output of the wind power period t, and P _t ^{P, S} represents the photovoltaic period t Planned power generation output, P _t ^{P, A} represents the planned output of photovoltaic power generation during the period t, P _t ^{S, D} represents the discharge power of the energy storage device during the period t, P _t ^{S, C} represents the charging power of the energy storage device during the period t, and P ^SDmax represents the The maximum discharge power of the energy storage device, P ^SCmax represents the maximum charging power of the energy storage device,

represents the discharge state variable of the energy storage device during the period t,

represents the state variable of the charging state of the energy storage device during the period t,

Represents the initial storage capacity of the energy storage device, E ^Smax denotes the maximum storage capacity of the energy storage device, E ^Smin denotes the minimum storage capacity of the energy storage device, η _S denotes the loss coefficient converted to the charging side, E ^Aset denotes the curtailment of wind and photovoltaic capacity,

Represents the power generation under the overall scenario of wind power and photovoltaic new energy, ρ _wps represents the probability of occurrence of wps in the new energy random variable scenario, NWPS represents the number of new energy random variable scenarios, [] ⁺ represents a positive function.

另一方面，还提供一种风光储一体化电源的收益预测系统，用以实现所述的风光储一体化电源的收益预测方法，包括：On the other hand, it also provides a revenue forecasting system of wind-solar-storage integrated power supply, which is used to realize the revenue forecasting method of wind-solar-storage integrated power supply, including:

数据获取模块，用以获取风光储一体化系统中风电、光伏、储能装置的运行计划数据；The data acquisition module is used to acquire the operation plan data of wind power, photovoltaic and energy storage devices in the wind-solar-storage integrated system;

预期收益模块，用以根据所述运行计划数据计算系统预期营收和系统预期成本，并将所述系统预期营收与所述系统预期成本之差输出为系统预期收益；an expected revenue module, configured to calculate the expected revenue of the system and the expected cost of the system according to the operation plan data, and output the difference between the expected revenue of the system and the expected cost of the system as the expected revenue of the system;

约束模块，用以通过预设的约束模型判断所述系统预期收益是否满足预设的约束标准，若满足，则输出所述系统预期收益为风光储一体化电源的收益预测结果。The constraint module is used to judge whether the expected revenue of the system meets the preset constraint standard through a preset constraint model, and if so, output the expected revenue of the system as the revenue prediction result of the integrated wind-solar-storage power supply.

优选地，所述数据获取模块获取风电、光伏、储能装置的运行计划数据至少包括：日前现货预测场景下的市场价格，日前现货市场价格预测场景数，一体化系统时段交换功率，风电预期成本，光伏预期成本，储能预期成本，风电多场景预测的场景数，场景发生概率，场景下风电的发电功率，风电预期成本函数的二次项系数，风电预期成本函数的一次项系数，风电预期成本函数的常数项系数，光伏多场景预测的场景数，场景光伏的发电功率，光伏预期成本函数的二次项系数，光伏预期成本函数的一次项系数，光伏预期成本函数的常数项系数；储能装置时段净交换功率，储能预期成本函数的二次项系数，储能预期成本函数的一次项系数，储能预期成本函数的常数项系数。Preferably, the data acquisition module acquires the operation plan data of wind power, photovoltaic and energy storage devices including at least: market price under the spot forecast scenario a day ago, the number of spot market price forecast scenarios a day ago, the exchange power of the integrated system during the period, and the expected cost of wind power , the expected cost of photovoltaics, the expected cost of energy storage, the number of scenarios predicted by wind power in multiple scenarios, the probability of occurrence of the scenario, the power generated by the wind power in the scenario, the quadratic coefficient of the expected cost function of wind power, the coefficient of the first order of the expected cost function of wind power, the expected wind power The coefficient of the constant term of the cost function, the number of scenarios predicted by the PV multi-scenario, the generated power of the PV in the scenario, the coefficient of the quadratic term of the PV expected cost function, the coefficient of the linear term of the PV expected cost function, the constant term coefficient of the PV expected cost function; The net exchange power of the energy storage period, the quadratic term coefficient of the expected cost function of energy storage, the coefficient of the first term of the expected cost function of energy storage, and the coefficient of the constant term of the expected cost function of energy storage.

优选地，所述预期收益模块还用于根据以下公式计算系统预期营收：Preferably, the expected revenue module is also used to calculate the expected revenue of the system according to the following formula:

其中，I^IS表示一体化系统预期营收，ΔT表示时段间隔，NT表示时段数，

表示日前现货预测场景ps下时段t的市场价格，NPS表示日前现货市场价格预测场景数，P_t ^IS表示一体化系统时段交换功率。Among them, I ^IS is the expected revenue of the integrated system, ΔT is the time interval, NT is the number of time periods,

Represents the market price in the period t under the spot forecast scenario ps a day ago, NPS represents the number of forecast scenarios for the spot market price a day ago, and P _t ^IS represents the exchange power of the integrated system during the period.

优选地，所述预期收益模块还用于根据以下公式计算系统预期成本：Preferably, the expected benefit module is also used to calculate the expected cost of the system according to the following formula:

C^IS＝C_w+C_p+C_s C ^IS =C _w +C _p +C _s

其中，C^IS表示一体化系统预期成本，C_w表示风电预期成本，C_p表示光伏预期成本，C_s表示储能预期成本，NWS表示风电多场景预测的场景数，ρ_ws表示场景ws发生概率，

表示场景ws下风电时段t的发电功率，a_w表示风电预期成本函数的二次项系数，b_w表示风电预期成本函数的一次项系数，c_w表示风电预期成本函数的常数项系数；NPS 表示光伏多场景预测的场景数，ρ_ps表示场景ps发生概率，

表示场景ps下光伏时段t的发电功率，a_p表示光伏预期成本函数的二次项系数，b_p表示光伏预期成本函数的一次项系数，c_p表示光伏预期成本函数的常数项系数；P_t ^S表示储能装置时段净交换功率，a_s储能预期成本函数的二次项系数，b_s储能预期成本函数的一次项系数，c_s表示储能预期成本函数的常数项系数。Among them, C ^IS is the expected cost of the integrated system, C _w is the expected cost of wind power, C _p is the expected cost of photovoltaics, C _s is the expected cost of energy storage, NWS is the number of scenarios predicted by multiple scenarios of wind power, ρ _ws is the probability of occurrence of scenario ws ,

Represents the generation power of wind power in the wind power period t under the scenario ws, a _w represents the quadratic term coefficient of the expected wind power cost function, b _w represents the first-order term coefficient of the wind power expected cost function, c _w represents the constant term coefficient of the wind power expected cost function; NPS represents Number of scenarios predicted by PV multi-scenarios, ρ _ps represents the occurrence probability of scenario ps,

Represents the generated power of the photovoltaic period t under the scene ps, a _p represents the quadratic term coefficient of the photovoltaic expected cost function, b _p represents the first order term coefficient of the photovoltaic expected cost function, c _p represents the constant term coefficient of the photovoltaic expected cost function; P _t ^S represents the net exchange power of the energy storage device during the period, a _s is the quadratic coefficient of the expected cost function of energy storage, b _s is the first-order coefficient of the expected cost function of energy storage, and c _s represents the constant term coefficient of the expected cost function of energy storage.

优选地，所述预设的约束模型具体包括：Preferably, the preset constraint model specifically includes:

Max I^NIS Max I ^NIS

其中，P_t ^W,S表示风电时段t计划发电出力，P_t ^W,A表示风电时段t计划弃风出力，P_t ^P,S表示光伏时段t计划发电出力，P_t ^P,A表示光伏时段t计划弃光出力，P_t ^S,D表示储能装置时段t放电功率，P_t ^S,C表示储能装置时段t充电功率，P^SDmax表示该储能装置最大放电功率，P^SCmax表示该储能装置最大充电功率，

表示储能装置时段t放电状态变量，

表示储能装置时段t充电状态变量，

表示储能装置初始储电量，E^Smax表示储能装置最大储电量，E^Smin表示储能装置最小储电量，η_S表示折算至充电侧的损耗系数，E^Aset表示弃风弃光电量限值，

表示风电、光伏新能源整体场景wps下的发电功率，ρ_wps表示新能源随机变量场景wps发生概率，NWPS表示新能源随机变量场景数，[]⁺表示取正函数。Among them, P _t ^W,S represents the planned power generation output during the wind power period t, P _t ^W,A represents the planned wind curtailment output during the wind power period t, P _t ^P,S represents the planned power generation output during the photovoltaic period t, and P _t ^P,A represents the photovoltaic period. t planned solar power output, P _t ^{S, D} represents the discharge power of the energy storage device in the period t, P _t ^{S, C} represents the charging power of the energy storage device in the period t, P ^SDmax represents the maximum discharge power of the energy storage device, and P ^SCmax represents the energy storage device’s maximum discharge power. The maximum charging power of the device can be

represents the discharge state variable of the energy storage device during the period t,

represents the state variable of the charging state of the energy storage device during the period t,

Represents the initial storage capacity of the energy storage device, E ^Smax denotes the maximum storage capacity of the energy storage device, E ^Smin denotes the minimum storage capacity of the energy storage device, η _S denotes the loss coefficient converted to the charging side, E ^Aset denotes the curtailment of wind and photovoltaic capacity,

Represents the power generation under the overall scenario of wind power and photovoltaic new energy, ρ _wps represents the probability of occurrence of wps in the new energy random variable scenario, NWPS represents the number of new energy random variable scenarios, [] ⁺ represents a positive function.

综上，实施本发明的实施例，具有如下的有益效果：To sum up, implementing the embodiments of the present invention has the following beneficial effects:

本发明提供的风光储一体化电源的收益预测方法及系统，在当前一体化系统申报策略设计基础上，充分考虑了新能源预测偏差对预期交易收益和预期交易风险的影响，构建了基于条件价值风险的新能源预测偏差下交易风险约束，以使申报策略适应新能源预测偏差要求。充分考虑风光储一体化系统中风电、光伏等新能源装机规模较高，新能源预测偏差对交易结果的影响，可降低新能源预测偏差产生的风险。The income forecasting method and system of the integrated wind-solar-storage power supply provided by the present invention, on the basis of the design of the current integrated system declaration strategy, fully considers the influence of the forecast deviation of new energy on the expected transaction income and expected transaction risk, and constructs a conditional value-based Trading risk constraints under the risk of new energy forecast deviation, so that the declaration strategy can adapt to the new energy forecast deviation requirements. Taking full account of the high installed capacity of wind power, photovoltaics and other new energy sources in the wind-solar-storage integrated system, the impact of new energy forecast deviations on transaction results can reduce the risk of new energy forecast deviations.

附图说明Description of drawings

为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，根据这些附图获得其他的附图仍属于本发明的范畴。In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention, and for those of ordinary skill in the art, obtaining other drawings according to these drawings still belongs to the scope of the present invention without any creative effort.

图1为本发明实施例中一种风光储一体化电源的收益预测方法的主流程示意图。FIG. 1 is a schematic diagram of the main flow of a method for predicting revenue of an integrated wind-solar-storage power supply in an embodiment of the present invention.

图2为本发明实施例中一种风光储一体化电源的收益预测系统的示意图。FIG. 2 is a schematic diagram of a revenue prediction system for an integrated wind-solar-storage power supply in an embodiment of the present invention.

具体实施方式Detailed ways

为使本发明的目的、技术方案和优点更加清楚，下面将结合附图对本发明作进一步地详细描述。In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings.

如图1所示，为本发明提供的一种风光储一体化电源的收益预测方法的一个实施例的示意图。在该实施例中，所述方法包括以下步骤：As shown in FIG. 1 , it is a schematic diagram of an embodiment of a method for predicting revenue of an integrated wind-solar-storage power supply provided by the present invention. In this embodiment, the method includes the following steps:

获取风光储一体化系统中风电、光伏、储能装置的运行计划数据；也就是，考虑新能源预测偏差、日前现货价格波动等因素，以及一体化系统中风电、光伏、储能装置运行计划，为以后的计算预测过程提供数据基础。具体地，所述风电、光伏、储能装置的运行计划数据至少包括：日前现货预测场景下的市场价格，日前现货市场价格预测场景数，一体化系统时段交换功率，风电预期成本，光伏预期成本，储能预期成本，风电多场景预测的场景数，场景发生概率，场景下风电的发电功率，风电预期成本函数的二次项系数，风电预期成本函数的一次项系数，风电预期成本函数的常数项系数，光伏多场景预测的场景数，场景光伏的发电功率，光伏预期成本函数的二次项系数，光伏预期成本函数的一次项系数，光伏预期成本函数的常数项系数；储能装置时段净交换功率，储能预期成本函数的二次项系数，储能预期成本函数的一次项系数，储能预期成本函数的常数项系数。Obtain the operation plan data of wind power, photovoltaic, and energy storage devices in the wind-solar-storage integrated system; that is, considering factors such as new energy forecast deviation, fluctuations in spot prices, and the operation plan of wind power, photovoltaic, and energy storage devices in the integrated system, Provide a data basis for the future calculation and prediction process. Specifically, the operation plan data of the wind power, photovoltaic and energy storage devices includes at least: market price under the spot forecast scenario a day ago, the number of spot market price forecast scenarios a day ago, the exchange power of the integrated system during the period, the expected cost of wind power, and the expected cost of photovoltaics , the expected cost of energy storage, the number of scenarios predicted by multiple scenarios of wind power, the probability of occurrence of the scenario, the generated power of the wind power in the scenario, the quadratic coefficient of the expected cost function of wind power, the coefficient of the first order of the expected cost function of wind power, the constant of the expected cost function of wind power term coefficient, the number of scenarios predicted by PV multi-scenarios, the generated power of PV in the scenario, the quadratic term coefficient of the PV expected cost function, the linear term coefficient of the PV expected cost function, the constant term coefficient of the PV expected cost function; Exchange power, quadratic term coefficient of energy storage expected cost function, first-order term coefficient of energy storage expected cost function, constant term coefficient of energy storage expected cost function.

进一步的，根据所述运行计划数据计算系统预期营收和系统预期成本，并将所述系统预期营收与所述系统预期成本之差输出为系统预期收益；也就是，考虑新能源预测偏差、日前现货价格波动等因素，计算一体化系统申报策略下预期营收；根据一体化系统中风电、光伏、储能装置运行计划，计算预期成本。Further, according to the operation plan data, the expected revenue of the system and the expected cost of the system are calculated, and the difference between the expected revenue of the system and the expected cost of the system is output as the expected revenue of the system; that is, considering the new energy forecast deviation, Calculate the expected revenue under the integrated system declaration strategy based on factors such as the fluctuation of spot price a few days ago; calculate the expected cost according to the operation plan of wind power, photovoltaic and energy storage devices in the integrated system.

具体实施例中，采用多场景预测模型来评估新能源预测偏差、日前现货市场价格波动。上述多场景预测模型属于当前较为成熟的技术方法，不影响本发明主要创新，不赘述其具体实施过程。一体化系统预期营收为基于多场景预测模型下的营收期望值，根据以下公式计算系统预期营收：In a specific embodiment, a multi-scenario prediction model is used to evaluate the forecast deviation of new energy and the price fluctuation of the spot market in the day-ahead. The above-mentioned multi-scenario prediction model belongs to a relatively mature technical method at present, and does not affect the main innovation of the present invention, and the specific implementation process thereof will not be repeated. The expected revenue of the integrated system is the expected revenue value based on the multi-scenario forecast model, and the expected revenue of the system is calculated according to the following formula:

其中，I^IS表示一体化系统预期营收，ΔT表示时段间隔，NT表示时段数，

表示日前现货预测场景ps下时段t的市场价格，NPS表示日前现货市场价格预测场景数，P_t ^IS表示一体化系统时段交换功率。Among them, I ^IS is the expected revenue of the integrated system, ΔT is the time interval, NT is the number of time periods,

Represents the market price in the period t under the spot forecast scenario ps a day ago, NPS represents the number of forecast scenarios for the spot market price a day ago, and P _t ^IS represents the exchange power of the integrated system during the period.

具体地，风电、光伏、储能装置成本可分为与运行计划关系较低的固定成本和与运行计划关系较高的变动成本。一体化系统的预期成本为风电、光伏、储能装置预期成本之和，根据以下公式计算系统预期成本：Specifically, the costs of wind power, photovoltaics, and energy storage devices can be divided into fixed costs that have a lower relationship with the operation plan and variable costs that have a higher relationship with the operation plan. The expected cost of the integrated system is the sum of the expected costs of wind power, photovoltaics and energy storage devices, and the expected cost of the system is calculated according to the following formula:

C^IS＝C_w+C_p+C_s C ^IS =C _w +C _p +C _s

其中，C^IS表示一体化系统预期成本，C_w表示风电预期成本，C_p表示光伏预期成本，C_s表示储能预期成本，NWS表示风电多场景预测的场景数，ρ_ws表示场景ws发生概率，

表示场景ws下风电时段t的发电功率，a_w表示风电预期成本函数的二次项系数，b_w表示风电预期成本函数的一次项系数，c_w表示风电预期成本函数的常数项系数；NPS 表示光伏多场景预测的场景数，ρ_ps表示场景ps发生概率，

表示场景ps下光伏时段t的发电功率，a_p表示光伏预期成本函数的二次项系数，b_p表示光伏预期成本函数的一次项系数，c_p表示光伏预期成本函数的常数项系数；P_t ^S表示储能装置时段净交换功率，a_s储能预期成本函数的二次项系数，b_s储能预期成本函数的一次项系数，c_s表示储能预期成本函数的常数项系数。Among them, C ^IS is the expected cost of the integrated system, C _w is the expected cost of wind power, C _p is the expected cost of photovoltaics, C _s is the expected cost of energy storage, NWS is the number of scenarios predicted by multiple scenarios of wind power, ρ _ws is the probability of occurrence of scenario ws ,

Represents the generation power of wind power in the wind power period t under the scenario ws, a _w represents the quadratic term coefficient of the expected wind power cost function, b _w represents the first-order term coefficient of the wind power expected cost function, c _w represents the constant term coefficient of the wind power expected cost function; NPS represents Number of scenarios predicted by PV multi-scenarios, ρ _ps represents the occurrence probability of scenario ps,

Represents the generated power of the photovoltaic period t under the scene ps, a _p represents the quadratic term coefficient of the photovoltaic expected cost function, b _p represents the first order term coefficient of the photovoltaic expected cost function, c _p represents the constant term coefficient of the photovoltaic expected cost function; P _t ^S represents the net exchange power of the energy storage device during the period, a _s is the quadratic coefficient of the expected cost function of energy storage, b _s is the first-order coefficient of the expected cost function of energy storage, and c _s represents the constant term coefficient of the expected cost function of energy storage.

再具体地，综合考虑一体化系统预期营收、预期成本，构建基于预期收益最大化的决策目标。More specifically, comprehensively consider the expected revenue and expected cost of the integrated system, and build a decision-making goal based on maximizing expected revenue.

预期收益可表示为预期营收与预期成本之差，可表示为：Expected revenue can be expressed as the difference between expected revenue and expected cost, which can be expressed as:

I^NIS＝I^IS-C^IS I ^NIS =I ^IS -C ^IS

式中，I^NIS为一体化系统预期收益。In the formula, I ^NIS is the expected income of the integrated system.

进一步的，通过预设的约束模型判断所述系统预期收益是否满足预设的约束标准，若满足，则输出所述系统预期收益为风光储一体化电源的收益预测结果。也就是，构建以预期收益最大化为决策目标，可调电源运行约束、风险控制约束作为约束条件的约束模型，求解得到预测结果，即申报策略。Further, it is judged by a preset constraint model whether the expected revenue of the system meets the preset constraint criteria, and if so, the expected revenue of the system is output as the revenue prediction result of the integrated wind-solar-storage power supply. That is to say, construct a constraint model with the maximization of expected revenue as the decision-making goal, the operation constraints of adjustable power supply and the constraints of risk control as constraints, and solve the prediction results, that is, the declaration strategy.

具体实施例中，所述预设的约束模型具体包括：In a specific embodiment, the preset constraint model specifically includes:

Max I^NIS Max I ^NIS

其中，max表示最大化规划问题，s.t.表示约束条件，P_t ^W,S表示风电时段t计划发电出力，P_t ^W,A表示风电时段t计划弃风出力，P_t ^P,S表示光伏时段t计划发电出力，P_t ^P,A表示光伏时段t计划弃光出力，P_t ^S,D表示储能装置时段t放电功率，P_t ^S,C表示储能装置时段t充电功率，P^SDmax表示该储能装置最大放电功率，P^SCmax表示该储能装置最大充电功率，

表示储能装置时段t放电状态变量，

表示储能装置时段t充电状态变量，

表示储能装置初始储电量，E^Smax表示储能装置最大储电量，E^Smin表示储能装置最小储电量，η_S表示折算至充电侧的损耗系数，E^Aset表示弃风弃光电量限值，

表示风电、光伏新能源整体场景wps下的发电功率，ρ_wps表示新能源随机变量场景wps发生概率， NWPS表示新能源随机变量场景数，[]⁺表示取正函数。Among them, max represents the maximization planning problem, st represents the constraint condition, P _t ^{W, S} represents the planned power generation output of the wind power period t, P _t ^{W, A} represents the planned wind curtailment output of the wind power period t, and P _t ^{P, S} represents the photovoltaic period t Planned power generation output, P _t ^{P, A} represents the planned output of photovoltaic power generation during the period t, P _t ^{S, D} represents the discharge power of the energy storage device during the period t, P _t ^{S, C} represents the charging power of the energy storage device during the period t, and P ^SDmax represents the The maximum discharge power of the energy storage device, P ^SCmax represents the maximum charging power of the energy storage device,

represents the discharge state variable of the energy storage device during the period t,

represents the state variable of the charging state of the energy storage device during the period t,

Represents the initial storage capacity of the energy storage device, E ^Smax denotes the maximum storage capacity of the energy storage device, E ^Smin denotes the minimum storage capacity of the energy storage device, η _S denotes the loss coefficient converted to the charging side, E ^Aset denotes the curtailment of wind and photovoltaic capacity,

Represents the power generation under the overall scenario of wind power and photovoltaic new energy, ρ _wps represents the probability of occurrence of wps in the new energy random variable scenario, NWPS represents the number of new energy random variable scenarios, [] ⁺ represents a positive function.

其中，根据风电、光伏、储能装置运行特性，构建其运行约束，具体地，电运行约束为发电功率平衡约束，可表示为：Among them, according to the operating characteristics of wind power, photovoltaic, and energy storage devices, the operating constraints are constructed. Specifically, the electrical operating constraints are the power generation power balance constraints, which can be expressed as:

式中，P_t ^W,S、P_t ^W,A分别为风电时段t计划发电出力和弃风出力。In the formula, P _t ^W,S and P _t ^W,A are the planned power generation output and abandoned wind output respectively during the wind power period t.

光伏运行约束为发电功率平衡约束，可表示为：The photovoltaic operation constraint is the power generation power balance constraint, which can be expressed as:

式中，P_t ^P,S、P_t ^P,A分别为光伏时段t计划发电出力和弃光出力。In the formula, P _t ^P,S and P _t ^P,A are the planned power generation output and the abandoned photovoltaic output of the photovoltaic period t, respectively.

具体地，储能装置运行特性约束包括交换功率约束、放电能力约束、充电能力约束、充放电状态约束、储电量约束、储电量不变约束，可表示为：Specifically, the operating characteristic constraints of the energy storage device include exchange power constraints, discharge capacity constraints, charging capacity constraints, charge and discharge state constraints, storage capacity constraints, and storage capacity constant constraints, which can be expressed as:

P_t ^S＝P_t ^S,D-P_t ^S,C P _t ^S =P _t ^S,D -P _t ^S,C

式中，P_t ^S,D、P_t ^S,C分别为储能装置时段t放电功率、充电功率，P^SDmax、 P^SCmax分别为该储能装置最大放电功率、最大充电功率，

分别为储能装置时段t放电状态变量、充电状态变量，

为该储能装置初始储电量，E^Smax、E^Smin分别为储能装置最大、最小储电量，η_S为折算至充电侧的损耗系数。一体化系统还需要满足整体送出平衡约束，可表示为：In the formula, P _t ^S,D and P _t ^S,C are the discharge power and charging power of the energy storage device during the period t, respectively, P ^SDmax and P ^SCmax are the maximum discharge power and maximum charging power of the energy storage device, respectively,

are the discharge state variable and the charge state variable of the energy storage device during the period t, respectively,

is the initial storage capacity of the energy storage device, ^ESmax and ^ESmin are the maximum and minimum storage capacity of the energy storage device, respectively, and _ηS is the loss coefficient converted to the charging side. The integrated system also needs to satisfy the overall sending balance constraint, which can be expressed as:

P_t ^W,S+P_t ^P,S+P_t ^S＝P_t ^IS P _t ^W,S +P _t ^P,S +P _t ^S =P _t ^IS

具体地，充分考虑新能源预测偏差对运行的影响，构建风险控制约束。新能源预测偏差的影响包括两个方面。一方面为实际新能源发电出力高于计划安排，可能造成弃风弃光损失，另一方面是实际新能源发电出力低于计划安排，一体化系统整体送出低于计划所需要承担的处罚。弃风弃光损失风险约束要求预期弃风弃光电量不超过限值，可表示为：Specifically, the impact of new energy forecast deviations on operation is fully considered, and risk control constraints are constructed. The impact of new energy forecast bias includes two aspects. On the one hand, the actual new energy power generation output is higher than the planned arrangement, which may result in the loss of wind and light abandonment. The risk constraint of curtailment of wind and solar power loss requires that the expected amount of curtailed wind and solar power should not exceed the limit, which can be expressed as:

式中，E^Aset为弃风弃光电量限值，

为风电、光伏新能源整体场景wps下的发电功率，ρ_wps为新能源随机变量场景wps发生概率， NWPS为新能源随机变量场景数。[]⁺为取正函数，当函数结果为正时，输出其本身数值，否则输出0，可表示为：In the formula, E ^Aset is the limit value of abandoned wind and photovoltaic power,

is the power generation under the overall scenario wps of wind power and photovoltaic new energy, ρ _wps is the probability of occurrence of wps in the new energy random variable scenario, and NWPS is the number of new energy random variable scenarios. [] ⁺ is a positive function. When the result of the function is positive, it outputs its own value, otherwise it outputs 0, which can be expressed as:

新能源整体多场景预测发电功率是风电、光伏多场景预测的随机变量叠加，可表示为：The overall multi-scenario forecasted power generation of new energy is the superposition of random variables of wind power and photovoltaic multi-scenario forecasts, which can be expressed as:

式中，

表示随机变量相加。In the formula,

represents the addition of random variables.

一体化系统处罚风险约束要求一体化系统计划偏离所承受的处罚不超过限值，可表示为：The integrated system penalty risk constraint requires that the penalty for the integrated system plan deviation does not exceed the limit, which can be expressed as:

式中，C^Aset为计划偏离处罚限值，

为时段t计划偏离处罚电价， []^-为取负函数，当函数结果为负时，输出其本身数值的相反数，否则输出0，可表示为：where C ^Aset is the planned deviation penalty limit,

For the time period t plan deviation penalty electricity price, [] ^- is a negative function, when the function result is negative, output the opposite number of its own value, otherwise output 0, which can be expressed as:

如图2所示，为本发明提供的一种风光储一体化电源的收益预测系统的一个实施例的示意图。在该实施例中，包括：As shown in FIG. 2 , it is a schematic diagram of an embodiment of a revenue prediction system for an integrated wind-solar-storage power supply provided by the present invention. In this embodiment, including:

数据获取模块，用以获取风光储一体化系统中风电、光伏、储能装置的运行计划数据；具体地，所述数据获取模块获取风电、光伏、储能装置的运行计划数据至少包括：日前现货预测场景下的市场价格，日前现货市场价格预测场景数，一体化系统时段交换功率，风电预期成本，光伏预期成本，储能预期成本，风电多场景预测的场景数，场景发生概率，场景下风电的发电功率，风电预期成本函数的二次项系数，风电预期成本函数的一次项系数，风电预期成本函数的常数项系数，光伏多场景预测的场景数，场景光伏的发电功率，光伏预期成本函数的二次项系数，光伏预期成本函数的一次项系数，光伏预期成本函数的常数项系数；储能装置时段净交换功率，储能预期成本函数的二次项系数，储能预期成本函数的一次项系数，储能预期成本函数的常数项系数。The data acquisition module is used to acquire the operation plan data of the wind power, photovoltaic and energy storage devices in the wind-solar-storage integrated system; specifically, the data acquisition module obtains the operation plan data of the wind power, photovoltaic and energy storage devices, including at least: spot before the day The market price under the forecast scenario, the number of scenarios predicted by the spot market price a day ago, the exchange power of the integrated system during the period, the expected cost of wind power, the expected cost of photovoltaics, the expected cost of energy storage, the number of scenarios for wind power multi-scenario forecast, the probability of occurrence of the scenario, the wind power under the scenario power generation, quadratic coefficient of wind power expected cost function, linear coefficient of wind power expected cost function, constant coefficient of wind power expected cost function, number of scenarios predicted by PV multi-scenarios, scenario PV power generation, PV expected cost function The quadratic term coefficient of the photovoltaic expected cost function, the constant term coefficient of the photovoltaic expected cost function; the net exchange power of the energy storage device period, the quadratic term coefficient of the energy storage expected cost function, the first order term coefficient, the constant term coefficient of the expected cost function of energy storage.

预期收益模块，用以根据所述运行计划数据计算系统预期营收和系统预期成本，并将所述系统预期营收与所述系统预期成本之差输出为系统预期收益；具体地，所述预期收益模块还用于根据以下公式计算系统预期营收：The expected benefit module is used to calculate the expected revenue of the system and the expected cost of the system according to the operation plan data, and output the difference between the expected revenue of the system and the expected cost of the system as the expected revenue of the system; specifically, the expected revenue The revenue module is also used to calculate the expected revenue of the system according to the following formula:

其中，I^IS表示一体化系统预期营收，ΔT表示时段间隔，NT表示时段数，

表示日前现货预测场景ps下时段t的市场价格，NPS表示日前现货市场价格预测场景数，P_t ^IS表示一体化系统时段交换功率。Among them, I ^IS is the expected revenue of the integrated system, ΔT is the time interval, NT is the number of time periods,

Represents the market price in the period t under the spot forecast scenario ps a day ago, NPS represents the number of forecast scenarios for the spot market price a day ago, and P _t ^IS represents the exchange power of the integrated system during the period.

所述预期收益模块还用于根据以下公式计算系统预期成本：The expected benefit module is also used to calculate the expected cost of the system according to the following formula:

C^IS＝C_w+C_p+C_s C ^IS =C _w +C _p +C _s

其中，C^IS表示一体化系统预期成本，C_w表示风电预期成本，C_p表示光伏预期成本，C_s表示储能预期成本，NWS表示风电多场景预测的场景数，ρ_ws表示场景ws发生概率，

表示场景ws下风电时段t的发电功率，a_w表示风电预期成本函数的二次项系数，b_w表示风电预期成本函数的一次项系数，c_w表示风电预期成本函数的常数项系数；NPS 表示光伏多场景预测的场景数，ρ_ps表示场景ps发生概率，

表示场景ps下光伏时段t的发电功率，a_p表示光伏预期成本函数的二次项系数，b_p表示光伏预期成本函数的一次项系数，c_p表示光伏预期成本函数的常数项系数；P_t ^S表示储能装置时段净交换功率，a_s储能预期成本函数的二次项系数，b_s储能预期成本函数的一次项系数，c_s表示储能预期成本函数的常数项系数。Among them, C ^IS is the expected cost of the integrated system, C _w is the expected cost of wind power, C _p is the expected cost of photovoltaics, C _s is the expected cost of energy storage, NWS is the number of scenarios predicted by multiple scenarios of wind power, and ρ _ws is the probability of occurrence of scenario ws ,

Represents the generated power of the wind power period t under the scenario ws, a _w represents the quadratic term coefficient of the wind power expected cost function, b _w represents the primary term coefficient of the wind power expected cost function, c _w represents the constant term coefficient of the wind power expected cost function; NPS represents Number of scenarios predicted by PV multi-scenarios, ρ _ps represents the probability of occurrence of scenario ps,

Represents the generated power of the photovoltaic period t under the scenario ps, a _p represents the quadratic term coefficient of the photovoltaic expected cost function, b _p represents the linear term coefficient of the photovoltaic expected cost function, c _p represents the constant term coefficient of the photovoltaic expected cost function; P _t ^S represents the net exchange power of the energy storage device during the period, a _s is the quadratic coefficient of the expected cost function of energy storage, b _s is the first-order coefficient of the expected cost function of energy storage, and c _s represents the constant term coefficient of the expected cost function of energy storage.

约束模块，用以通过预设的约束模型判断所述系统预期收益是否满足预设的约束标准，若满足，则输出所述系统预期收益为风光储一体化电源的收益预测结果。The constraint module is used to judge whether the expected revenue of the system meets the preset constraint standard through a preset constraint model, and if so, output the expected revenue of the system as the revenue prediction result of the integrated wind-solar-storage power supply.

具体地，所述预设的约束模型具体包括：Specifically, the preset constraint model specifically includes:

Max I^NIS Max I ^NIS

其中，P_t ^W,S表示风电时段t计划发电出力，P_t ^W,A表示风电时段t计划弃风出力，P_t ^P,S表示光伏时段t计划发电出力，P_t ^P,A表示光伏时段t计划弃光出力，P_t ^S,D表示储能装置时段t放电功率，P_t ^S,C表示储能装置时段t充电功率，P^SDmax表示该储能装置最大放电功率，P^SCmax表示该储能装置最大充电功率，

表示储能装置时段t放电状态变量，

表示储能装置时段t充电状态变量，

表示储能装置初始储电量，E^Smax表示储能装置最大储电量，E^Smin表示储能装置最小储电量，η_S表示折算至充电侧的损耗系数，E^Aset表示弃风弃光电量限值，

表示风电、光伏新能源整体场景wps下的发电功率，ρ_wps表示新能源随机变量场景wps发生概率，NWPS表示新能源随机变量场景数，[]⁺表示取正函数。Among them, P _t ^W,S represents the planned power generation output during the wind power period t, P _t ^W,A represents the planned wind curtailment output during the wind power period t, P _t ^P,S represents the planned power generation output during the photovoltaic period t, and P _t ^P,A represents the photovoltaic period. t planned solar power output, P _t ^{S, D} represents the discharge power of the energy storage device in the period t, P _t ^{S, C} represents the charging power of the energy storage device in the period t, P ^SDmax represents the maximum discharge power of the energy storage device, and P ^SCmax represents the energy storage device’s maximum discharge power. The maximum charging power of the device can be

represents the discharge state variable of the energy storage device during the period t,

represents the state variable of the charging state of the energy storage device during the period t,

Represents the initial storage capacity of the energy storage device, E ^Smax denotes the maximum storage capacity of the energy storage device, E ^Smin denotes the minimum storage capacity of the energy storage device, η _S denotes the loss coefficient converted to the charging side, E ^Aset denotes the curtailment of wind and photovoltaic capacity,

Represents the power generation under the overall scenario of wind power and photovoltaic new energy, ρ _wps represents the probability of occurrence of wps in the new energy random variable scenario, NWPS represents the number of new energy random variable scenarios, [] ⁺ represents a positive function.

以上所描述的系统实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。The system embodiments described above are only illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed over multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

需说明的是，上述实施例所述系统与上述实施例所述方法对应，因此，上述实施例所述系统未详述部分可以参阅上述实施例所述方法的内容得到，此处不再赘述。It should be noted that the system described in the foregoing embodiment corresponds to the method described in the foregoing embodiment. Therefore, the undescribed part of the system described in the foregoing embodiment can be obtained by referring to the content of the method described in the foregoing embodiment, which will not be repeated here.

综上，实施本发明的实施例，具有如下的有益效果：To sum up, implementing the embodiments of the present invention has the following beneficial effects:

本发明提供的风光储一体化电源的收益预测方法及系统，在当前一体化系统申报策略设计基础上，充分考虑了新能源预测偏差对预期交易收益和预期交易风险的影响，构建了基于条件价值风险的新能源预测偏差下交易风险约束，以使申报策略适应新能源预测偏差要求。充分考虑风光储一体化系统中风电、光伏等新能源装机规模较高，新能源预测偏差对交易结果的影响，可降低新能源预测偏差产生的风险。以上所揭露的仅为本发明较佳实施例而已，当然不能以此来限定本发明之权利范围，因此依本发明权利要求所作的等同变化，仍属本发明所涵盖的范围。The income forecasting method and system of the integrated wind-solar-storage power supply provided by the present invention, on the basis of the design of the current integrated system declaration strategy, fully considers the influence of the forecast deviation of new energy on the expected transaction income and expected transaction risk, and constructs a conditional value-based Trading risk constraints under the risk of new energy forecast deviation, so that the declaration strategy can adapt to the new energy forecast deviation requirements. Taking full account of the high installed capacity of wind power, photovoltaics and other new energy sources in the wind-solar-storage integrated system, the impact of new energy forecast deviations on transaction results can reduce the risk of new energy forecast deviations. The above disclosures are only preferred embodiments of the present invention, and of course, the scope of the rights of the present invention cannot be limited by this. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.