Photovoltaic-photo-thermal power generation system optimization scheduling method and device

Abstract

The invention discloses a photovoltaic-photo-thermal power generation system optimization scheduling method and device in the technical field of hybrid energy system integration, and the method comprises the steps: carrying out the optimization scheduling of a photovoltaic-photo-thermal power generation system based on the real-time power generation electric power of a photo-thermal power station, the grid-connected electric power of a photovoltaic power station, and the electric power needed by a power generation system load; establishing a total objective function taking the economic benefit and the reliability level of the photovoltaic-photo-thermal power generation system as indexes; and on the premise of meeting constraint conditions, solving the total objective function through a multi-objective genetic algorithm NSGA-II to obtain a Pareto solution set, obtaining an optimal compromise solution in the Pareto solution set through a maximum satisfaction method in a fuzzy control theory, and realizing optimal scheduling of the photovoltaic-photo-thermal power generation system meeting economical efficiency and reliability based on the optimal compromise solution. The technical problem that an existing photovoltaic-photo-thermal power generation system cannot give consideration to the economic benefit of grid connection of the power generation system and the power utilization satisfaction degree of a user at the same time can be solved.

Description

Technical Field

[0001] This invention relates to the fields of hybrid energy system integration technology and intelligent optimization algorithm technology, and in particular to a method and apparatus for optimizing the scheduling of a photovoltaic-solar thermal power generation system. Background Technology

[0002] Concentrated-Solar-Power (CSP) and Photovoltaic (PV) power plants are two main methods of solar power generation. These two methods of utilizing solar energy each have their advantages and disadvantages in terms of time: PV can generate electricity in a timely manner and flexibly respond to changes in sunlight, but it loses power at night when there is no sunlight, and the large amount of electricity generated during the day may be wasted; CSP, with its molten salts, ensures continuous power generation at night and on cloudy days, providing support for the stability of power generation, but its high construction cost and large land area requirements limit its development.

[0003] In a combined photovoltaic and solar thermal system, the advantages can be maximized and the disadvantages minimized, achieving complementarity between photovoltaic and solar thermal systems. However, when electricity demand is low or the grid dispatch capacity is insufficient, the electricity generated by the photovoltaic power station cannot be fully utilized, resulting in curtailment and load shedding, which in turn affects user satisfaction with electricity use.

[0004] Therefore, there is an urgent need for an optimized scheduling method and device for photovoltaic-solar thermal power generation systems to solve the above-mentioned technical problems. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and apparatus for optimizing the scheduling of photovoltaic-solar thermal power generation systems, which can solve the technical problem that existing photovoltaic-solar thermal power generation systems cannot simultaneously take into account the economic benefits of grid connection and user satisfaction with electricity consumption.

[0006] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0007] In a first aspect, the present invention provides an optimized scheduling method for a photovoltaic-solar thermal power generation system, comprising:

[0008] To obtain the real-time electrical power generated by photovoltaic power plants and solar thermal power plants;

[0009] Calculate the sum of the real-time power output of the photovoltaic power station and the solar thermal power station based on their real-time power generation data.

[0010] When the real-time power generation exceeds the power required by the power generation system load, the difference is calculated to obtain the electric heating power, which is then stored in the thermal storage tank of the solar thermal power plant.

[0011] The grid-connected power of the photovoltaic power station is obtained based on the real-time power generation and electric heating power of the photovoltaic power station.

[0012] Based on the real-time power generation of the solar thermal power plant, the grid-connected power of the photovoltaic power plant, and the power required by the power generation system load, a general objective function is established with the economic benefits and reliability level of the photovoltaic-solar thermal power generation system as indicators.

[0013] Under the premise of satisfying the constraints, the overall objective function is solved by the multi-objective genetic algorithm NSGA-II to obtain the Pareto solution set. The optimal compromise solution is obtained from the Pareto solution set by the maximum satisfaction method in fuzzy control theory. Based on the optimal compromise solution, the photovoltaic-solar thermal power generation system is optimized to meet the requirements of economy and reliability.

[0014] Furthermore, it also includes:

[0015] When the real-time power generation of the photovoltaic power station is less than the power required by the power generation system load, the heat storage tank is controlled to release heat to generate electricity until the real-time power generation equals the power required by the power generation system load.

[0016] Furthermore, obtaining the real-time output power of the photovoltaic power station includes:

[0017] ,

[0018] in, The rated output power calculated for a photovoltaic power station represents the maximum power generation capacity of the photovoltaic power station at present. To determine the conversion efficiency of a photovoltaic power plant under standard test conditions, This is a temperature coefficient, representing the percentage decrease in efficiency for every 1 degree Celsius increase in temperature. for The ambient temperature at any given time for Sunlight intensity at any given time This refers to the nominal operating battery temperature. This refers to the total area of ​​the photovoltaic panels;

[0019] To ensure safe and stable operation of photovoltaic power plants during dispatch, the real-time output power of the photovoltaic power plants should meet the following conditions:

[0020] ,

[0021] in, ,

[0022] ,

[0023] in, for The real-time output power of the photovoltaic power station. for The minimum output power of a photovoltaic power station at any given time. for The maximum output power of the photovoltaic power station at any given time. for The predicted value, for The prediction error for The predicted value, for The prediction error.

[0024] Furthermore, the expression for obtaining the electric heating power by taking the difference includes:

[0025] ,

[0026] in, yes Electric heating power at any time for The electrical power output of the solar thermal power plant at any given time. for The load requirements of the power generation system at all times for The real-time output power of the photovoltaic power station;

[0027] Based on the aforementioned electric heating power, electrothermal energy is generated through an electric heating device, and the expression for the electrothermal energy includes:

[0028] ,

[0029] in, yes The electric heat energy generated by the electric heating device at all times Energy conversion efficiency of electric heating devices;

[0030] The amount of heat added to the thermal storage tank due to the electric heating device is:

[0031] ,

[0032] in, Because of the increased heat from the electric heating device, To improve the efficiency of thermal storage charging.

[0033] Furthermore, obtaining the real-time electrical power generated by the concentrated solar power plant includes:

[0034] The heat in the thermal storage tank also originates from the solar thermal power plant's mirror field concentrating solar collector, whose instantaneous concentrating heat power is:

[0035] ,

[0036] in, for The heat output from the constant-time mirror field focusing light, for Sunlight intensity at any given time For concentrating heat collection area, For heat collection efficiency;

[0037] The actual heat transferred to the thermal storage tank is obtained based on the instantaneous thermal power of the concentrated solar collector, and the expression includes:

[0038] ,

[0039] In the formula, for The actual amount of heat transferred to the heat storage tank at all times. for The waste solar thermal power plant's solar thermal energy;

[0040] The heat added to the thermal storage tank in a concentrated solar power plant due to the focusing effect of the mirror field is:

[0041] ,

[0042] in, The heat generated in the thermal storage tank due to the focusing of light by the mirror field. To improve the efficiency of thermal storage charging;

[0043] Obtaining thermal storage tanks The total amount of heat added at each moment :

[0044] ,

[0045] When the thermal storage tank releases heat and discharges, the amount of heat lost inside the tank is: , There are losses during the transfer of heat to the solar thermal power plant; therefore, the actual amount of heat output from the heat storage tank to the solar thermal power plant is... for:

[0046] ,

[0047] in, for The heat output of the thermal storage tank at all times for The amount of heat lost in the thermal storage tank at all times. For thermal storage discharge efficiency;

[0048] Solar thermal power plants pass The generator produces electrical energy, which is:

[0049] ,

[0050] in, for The real-time power output of a solar thermal power plant. It refers to the power generation efficiency of a solar thermal power plant.

[0051] Furthermore, the overall objective function includes:

[0052] ,

[0053] ,

[0054] in, The objective function is the economic benefit. For the scheduling period, and They are respectively The on-grid electricity price of photovoltaic and solar thermal power plants at any given time. for The grid-connected power generation of the photovoltaic power station at any time for The real-time output power of the photovoltaic power station. for Electric heating power at any time for The output power of the solar thermal power plant at any time The cost of electricity generated by a photovoltaic power plant. The cost of electricity generated by a solar thermal power plant, and Costs associated with system load shedding and light curtailment; For the reliability level objective function, To represent system reliability indicators, The probability of system load power shortage time. For system power outage time, This is the amount of load loss. for Power supply deficit at any given time for The load demand at any given moment.

[0055] Furthermore, the power generation cost of the photovoltaic power station Including operating and management costs and investment depreciation costs, expressed as:

[0056] ,

[0057] ,

[0058] ,

[0059] in, For the operation and management costs of photovoltaic power plants, This represents the unit operation and management cost coefficient for photovoltaic power plants. The investment depreciation cost of a photovoltaic power station. This refers to the service life of a photovoltaic power station. The initial investment cost per unit capacity of a photovoltaic power plant. For photovoltaic capacity factor, The discount rate;

[0060] The power generation cost of the solar thermal power plant Including thermal storage costs and power generation costs, expressed as:

[0061] ,

[0062] ,

[0063] ,

[0064] In the formula, For the heat storage cost of solar thermal power plants, The unit initial investment cost of the thermal storage tank. For the installed capacity of the thermal storage tank, The service life of the thermal storage tank. The cost of electricity generated by a solar thermal power plant, This represents the power generation cost coefficient of a solar thermal power plant. for The electrical power output of the solar thermal power plant at any given time;

[0065] The load shedding cost Represented as:

[0066] ,

[0067] ,

[0068] in, The unit compensation cost for constant load shedding for Constantly cutting off load power, for The load requirements of the power generation system at all times;

[0069] The cost of abandoned light Represented as:

[0070] ,

[0071] ,

[0072] ,

[0073] in, The unit compensation fee for the curtailed solar power generated by photovoltaic power plants. for The amount of curtailed solar power from photovoltaic power plants at all times. Compensation cost per unit for wasted solar thermal energy from solar thermal power plants. For the waste solar heat from solar thermal power plants, for The maximum output power of the photovoltaic power station at any given time. for The heat output from the constant-time mirror field focusing light, for The actual heat transferred to the heat storage tank at all times;

[0074] The probability of system load power shortage time is expressed as follows:

[0075] ,

[0076] The load loss is expressed as:

[0077] ,

[0078] The constraints of the overall objective function include

[0079] Power balance constraints:

[0080] ,

[0081] Photovoltaic power plant output constraints:

[0082] ,

[0083] Electric heating capacity constraints:

[0084] ,

[0085] Output constraints of solar thermal power plants:

[0086] ,

[0087] Climbing constraints:

[0088] ,

[0089] Thermal constraints of thermal storage systems:

[0090] ,

[0091] ,

[0092] Thermal constraint of the mirror field concentrator:

[0093] ,

[0094] in, for The predicted minimum output power of a photovoltaic power station at any given time. for Predicted maximum output power of photovoltaic power station at any given time. for The maximum electric heating power at any given time. for The minimum electrical power output of the solar thermal power plant at any given time. for The maximum electrical power output of the solar thermal power plant at any given time. for The electrical power output of the solar thermal power plant at any given time. This represents the maximum uphill power output of a solar thermal power plant. This represents the maximum downhill ramp power of the solar thermal power plant. This represents the minimum heat storage capacity of the thermal storage tank. This represents the maximum heat storage capacity of the thermal storage tank. for The amount of heat stored in the thermal storage tank at all times. for The amount of heat lost in the thermal storage tank at all times. For the thermal storage tank in The total amount of heat added at any given moment.

[0095] Furthermore, under the premise of satisfying the constraints, the overall objective function is solved using the multi-objective genetic algorithm NSGA-II to obtain the Pareto solution set. The optimal compromise solution is then obtained from the Pareto solution set using the maximum satisfaction method in fuzzy control theory, including:

[0096] Based on the optimized decision variables, an initial population of size N is randomly generated according to the constraints, serving as the parent population for the first iteration. ;

[0097] Parental population For the current population, perform a fast non-dominated sort on the solutions in the current population and calculate the virtual crowding distance of the solutions in the current population.

[0098] Based on the non-dominance level and crowding distance of individuals, genetic operations are performed according to preset selection probabilities, recombination rates, and mutation rates to generate a new offspring population of size N. ;

[0099] The parent and offspring populations are merged into a single population of size 2N. Then, a selection based on fast non-dominated sorting and virtual crowding distance is performed to generate a next-generation parent population of size N. ;

[0100] Parental population For the current population, the iteration is repeated, and the Pareto optimal solution set is obtained after a preset number of iterations.

[0101] Regarding the economic and reliability indices of the Pareto optimal solution set, the corresponding analytical expressions of the skewed fuzzy satisfaction function can be obtained by solving for them as follows:

[0102] ,

[0103] ,

[0104] in, For economical standardization of satisfaction, For the standardization of reliability satisfaction, and The x and y axes represent the values ​​in the Pareto optimal solution set, corresponding to economy and reliability, respectively. and Corresponding to minimum and maximum economic efficiency, and Corresponding to minimum and maximum reliability;

[0105] After determining the skewed fuzzy satisfaction function, the standardized satisfaction of each non-dominated solution is calculated as follows:

[0106] ,

[0107] in, For the corresponding number Standardized satisfaction of a non-dominated solution The number of non-dominated solutions. and The first Standardized satisfaction with the economy and reliability of a non-dominated solution;

[0108] By using the maximum satisfaction method in fuzzy control theory, the non-dominated solution with the highest standardized satisfaction is selected as the optimal compromise solution;

[0109] The decision vector includes: photovoltaic power generation. Electric heating converts electrical energy The energy flowing into the thermal storage tank from the mirror field concentrator The power generation of solar thermal power plants .

[0110] Secondly, the present invention provides an optimized scheduling device for a photovoltaic-solar thermal power generation system, comprising:

[0111] The power acquisition module is used to acquire the real-time electrical power generated by photovoltaic power plants and solar thermal power plants;

[0112] The power summation module is used to calculate the sum of the real-time power generated by the photovoltaic power station and the solar thermal power station based on the real-time power generated by the photovoltaic power station and the solar thermal power station.

[0113] The power difference module is used to calculate the difference between the real-time power generation and the power required by the power generation system load to obtain the electric heating power, and store the electric heating power in the heat storage tank of the solar thermal power plant.

[0114] The photovoltaic power plant grid-connected power acquisition module is used to obtain the grid-connected power of the photovoltaic power plant based on the real-time power generation and electric heating power of the photovoltaic power plant.

[0115] The overall objective function establishment module is used to establish an overall objective function with the economic benefits and reliability level of the photovoltaic-solar thermal power generation system as indicators, based on the real-time power generation of the solar thermal power plant, the grid-connected power of the photovoltaic power plant, and the power required by the power generation system load.

[0116] The solution module is used to solve the overall objective function using the multi-objective genetic algorithm NSGA-II under the premise of satisfying the constraints, obtain the Pareto solution set, obtain the optimal compromise solution in the Pareto solution set using the maximum satisfaction method in fuzzy control theory, and realize the optimal scheduling of the photovoltaic-solar thermal power generation system to meet the requirements of economy and reliability based on the optimal compromise solution.

[0117] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0118] This invention proposes an optimized scheduling method for photovoltaic-solar thermal power generation systems. By constructing a working mode for the photovoltaic-solar thermal power generation system and simultaneously measuring the utilization and output capabilities of both photovoltaic and solar thermal power plants, and using thermal storage tanks as energy storage units for energy absorption and release, the curtailment effect of traditional joint scheduling of photovoltaic and solar thermal power plants is weakened, reducing the load shedding caused by joint power generation. Furthermore, by solving the constructed overall objective function using a multi-objective genetic algorithm, an optimal trade-off solution regarding economic benefits and reliability can be obtained. This not only increases the economic benefits of grid connection for the photovoltaic-solar thermal power generation system, taking into account the impact of load shedding and curtailment rates while considering power generation costs and grid connection benefits, but also improves the system's reliability, providing a stable and reliable power supply capability and further enhancing user satisfaction with electricity usage. Attached Figure Description

[0119] Figure 1 This is a flowchart illustrating an optimized scheduling method for a photovoltaic-solar thermal power generation system provided in an embodiment of this application.

[0120] Figure 2 A structural block diagram of a photovoltaic-thermal power generation system in an optimized scheduling method for a photovoltaic-thermal power generation system provided in this application embodiment. Detailed Implementation

[0121] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0122] In this invention, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B together, or B alone. Additionally, in this invention, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0123] For ease of understanding, the following explanations are provided for the proper nouns used in this application:

[0124] The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is a multi-objective optimization algorithm proposed in 2002 by a team led by Indian scientist Kalyanmoy-Deb. It is a landmark achievement in the field of multi-objective genetic algorithms (MOGA). It made core improvements to address the problems of high computational complexity, lack of elite preservation mechanisms, and insufficient population diversity of the original NSGA (1995), and remains one of the most commonly used multi-objective optimization algorithms in industry and academia.

[0125] The Pareto solution set, also known as the Pareto set, is used in multi-objective optimization problems because there is often conflict between objectives, and there is no single "absolutely optimal solution" that allows all objectives to reach their optimal state simultaneously. In such cases, a set of non-dominated solutions needs to be selected through Pareto dominance relationships; this set of non-dominated solutions is called the Pareto solution set.

[0126] Example 1:

[0127] Figure 1 This is a flowchart of the photovoltaic-solar thermal power generation system optimization scheduling method in Embodiment 1 of the present invention. This flowchart only illustrates the logical sequence of the method described in this embodiment. Provided there are no conflicts, different methods may be used in other possible embodiments of the present invention. Figure 1 Complete the steps shown or described in the order indicated.

[0128] The photovoltaic-concentrated thermal power generation system optimization scheduling method provided in this embodiment can be applied to a terminal and can be executed by a mechanical equipment fault identification device. This device can be implemented in software and / or hardware and can be integrated into the terminal, such as any smartphone, tablet, or computer device with communication capabilities. Before executing the scheduling method, as... Figure 2 As shown, a structural block diagram of the photovoltaic-solar thermal power generation system mentioned in this application is disclosed.

[0129] The method in this embodiment specifically includes the following steps:

[0130] Step 1: Obtain the real-time power output of the photovoltaic and solar thermal power plants:

[0131] Among them, obtaining the real-time output power of the photovoltaic power station includes:

[0132] ,

[0133] in, The rated output power calculated for a photovoltaic power station represents the maximum power generation capacity of the photovoltaic power station at present. To determine the conversion efficiency of a photovoltaic power plant under standard test conditions, This is a temperature coefficient, representing the percentage decrease in efficiency for every 1 degree Celsius increase in temperature. for The ambient temperature at any given time for Sunlight intensity at any given time The nominal operating battery temperature is usually provided by the manufacturer and typically ranges from 45 to 48°C. This refers to the total area of ​​the photovoltaic panels;

[0134] Since the rated output power cannot reflect the impact of real-time environmental conditions, while the predicted value can dynamically integrate real-time weather and equipment status, the maximum output of the photovoltaic power station adopts the predicted value.

[0135] To ensure safe and stable operation of photovoltaic power plants during dispatch, the real-time output power of the photovoltaic power plants should meet the following conditions:

[0136] ,

[0137] in, ,

[0138] ,

[0139] in, for The real-time output power of the photovoltaic power station. for The minimum output power of a photovoltaic power station at any given time. for The maximum output power of the photovoltaic power station at any given time. for The predicted value, for The prediction error for The predicted value, for The prediction error.

[0140] The prediction error follows a third-order Gaussian mixture distribution, and its probability density function can be expressed as:

[0141] ,

[0142] In the formula, For prediction error, , , Let the expected value, standard deviation, and weight phasor of each Gaussian distribution be given. For the first The weights of the Gaussian distribution. For the first The expectation of a Gaussian distribution. Indicates the first The standard deviation of the Gaussian distribution.

[0143] Regarding the limitation on the real-time output power of the photovoltaic power station, the theoretical meaning is that the output power of the photovoltaic power station should be constrained between the upper and lower limits of the output capacity of the photovoltaic power station. However, if the output power of the photovoltaic power station is described according to the predicted value, there will be a prediction error. Therefore, the prediction error is used to describe the limitation here.

[0144] Step 2: Calculate the sum of the real-time power outputs of the photovoltaic power station and the solar thermal power station based on their real-time power generation data.

[0145] Step 3: When the real-time generated power exceeds the power required by the power generation system load, the difference is calculated to obtain the electric heating power, which is then stored in the thermal storage tank of the solar thermal power plant.

[0146] Under certain conditions, the power generation of a photovoltaic power station may exceed the power consumption required by the load. Therefore, an electric heating device can be added to the output side of the photovoltaic power station to charge the thermal energy storage tank of the solar thermal power station using the excess power generation of the photovoltaic power station, thereby realizing the conversion of electrical energy into thermal energy. When the solar thermal power station needs to generate electricity, it can supply power to the grid through a steam turbine and generator, thus completing the physical coupling of electrical energy and thermal energy.

[0147] Because of the presence of electric heating devices, the power generated by a photovoltaic power station is not entirely converted into grid-connected electricity. Depending on changes in load demand and power generation capacity, a portion of the photovoltaic power generation will be converted into electric heating power.

[0148] The expressions for obtaining the electric heating power by subtraction include:

[0149] ,

[0150] in, yes Electric heating power at any time for The electrical power output of the solar thermal power plant at any given time. for The load requirements of the power generation system at all times for The real-time output power of the photovoltaic power station;

[0151] Based on the aforementioned electric heating power, electrothermal energy is generated through an electric heating device, and the expression for the electrothermal energy includes:

[0152] ,

[0153] in, yes The electric heat energy generated by the electric heating device at all times Energy conversion efficiency of electric heating devices;

[0154] The electric heating device outputs heat energy, which is then transferred to the heat storage tank, resulting in heat loss. The amount of heat added to the heat storage tank due to the electric heating device is:

[0155] ,

[0156] in, Because of the increased heat from the electric heating device, This refers to the efficiency of thermal energy storage charging. This process represents the conversion of electrical energy into thermal energy by the electric heating device in a photovoltaic-thermal power generation system.

[0157] Photovoltaic power plants provide a large amount of electricity during the day, especially at midday when sunlight intensity is at its peak. While concentrated solar power (CSP) plants can also generate electricity during the day, their energy storage systems allow them to continue providing power in the evening or at night when sunlight is less intense. This effectively supplements the power output of photovoltaic power plants, ensuring uninterrupted power supply and guaranteeing power stability.

[0158] Therefore, when the real-time power generation of the photovoltaic power station is less than the power required by the power generation system load, the heat storage tank is controlled to release heat to generate electricity. At this time, the real-time power generation of the solar thermal power station can be obtained. It should be noted that this application only discloses how to obtain the real-time power generation of the solar thermal power station at this time, specifically including:

[0159] The heat in the thermal storage tank also originates from the solar thermal power plant's mirror field concentrating solar collector, whose instantaneous concentrating heat power is:

[0160] ,

[0161] in, for The heat output from the constant-time mirror field focusing light, for Sunlight intensity at any given time For concentrating heat collection area, For heat collection efficiency;

[0162] The actual heat transferred to the thermal storage tank is obtained based on the instantaneous thermal power of the concentrated solar collector, and the expression includes:

[0163] ,

[0164] In the formula, for The actual amount of heat transferred to the heat storage tank at all times. for The waste solar thermal power plant's solar thermal energy;

[0165] The heat added to the thermal storage tank in a concentrated solar power plant due to the focusing effect of the mirror field is:

[0166] ,

[0167] in, The heat generated in the thermal storage tank due to the focusing of light by the mirror field. To improve the efficiency of thermal storage charging;

[0168] Obtaining thermal storage tanks The total amount of heat added at each moment :

[0169] ,

[0170] The above formula illustrates the heat storage process in the thermal storage tank. Excess electricity generated by the photovoltaic power plant is converted into heat energy via an electric heating device and stored in the thermal storage tank. The solar thermal power plant's concentrating mirrors transfer the solar energy's heat energy to the thermal storage tank. The heat release process from the thermal storage tank is the power generation process of the solar thermal power plant. It involves the heat energy released from the storage tank driving a steam turbine, which in turn generates electricity through a generator, thus achieving the conversion of heat energy into electrical energy.

[0171] When the thermal storage tank releases heat and discharges, the amount of heat lost inside the tank is: , There are losses during the transfer of heat to the solar thermal power plant; therefore, the actual amount of heat output from the heat storage tank to the solar thermal power plant is... for:

[0172] ,

[0173] in, for The heat output of the thermal storage tank at all times for The amount of heat lost in the thermal storage tank at all times. For thermal storage discharge efficiency;

[0174] Solar thermal power plants pass It generates electricity, converting heat energy into electrical energy, thus realizing the power generation process of a solar thermal power plant, and outputting electrical energy as follows:

[0175] ,

[0176] in, for The real-time power output of a solar thermal power plant is also its actual grid-connected power. It refers to the power generation efficiency of a solar thermal power plant;

[0177] Heat released by the thermal storage tank Based on the power generation required by the solar thermal power plant The decision was made.

[0178] At this time, the required power generation of the solar thermal power plant can be determined. The heat consumed by the thermal storage tank is calculated in reverse:

[0179] ,

[0180] The electric heating system of a photovoltaic power station converts electrical energy into heat energy, increasing the heat storage tank by [amount missing]. The absorption and transfer of electrical energy by the solar thermal power plant's mirror field concentrator increases the heat output of the thermal storage tank. The heat reduction achieved by the solar thermal power plant system through the utilization of thermal energy from the thermal storage tank is: These three processes occur independently, resulting in a dynamic change in the heat stored in the thermal storage tank. The heat stored in the thermal storage tank can be expressed as:

[0181] ,

[0182] In the formula, for The amount of heat stored in the thermal storage tank at any given time indicates... The constant change in heat storage capacity due to the inflow and outflow of heat from the thermal storage tank. for The amount of heat stored in the thermal storage tank at all times.

[0183] The above can be summarized as the amount of electricity generated in the thermal storage tank according to the power generation required by the solar thermal power plant. Heat generation is carried out until the sum of the real-time generated power and the power required by the power generation system load is equal, thereby achieving dispatch balance.

[0184] Regarding how to obtain the real-time power output of the solar thermal power plant in step one, the basic logic is the same as in step three above, but the actual obtained power output... It may be different.

[0185] Step 4: Obtain the grid-connected power of the photovoltaic power station based on the real-time power generation and electric heating power of the photovoltaic power station.

[0186] Step 5: Based on the real-time power generation of the solar thermal power plant, the grid-connected power of the photovoltaic power plant, and the power required by the power generation system load, establish a general objective function with the economic benefits and reliability level of the photovoltaic-solar thermal power generation system as indicators:

[0187] Specifically, the overall objective function includes:

[0188] ,

[0189] ,

[0190] in, The objective function is the economic benefit. For the scheduling period, and They are respectively The on-grid electricity price of photovoltaic and solar thermal power plants at any given time. for The grid-connected power generation of the photovoltaic power station at any time for The real-time output power of the photovoltaic power station. for Electric heating power at any time for The output power of the solar thermal power plant at any time The cost of electricity generated by a photovoltaic power plant. The cost of electricity generated by a solar thermal power plant, and Costs associated with system load shedding and light curtailment; For the reliability level objective function, To represent system reliability indicators, The probability of system load power shortage time. For system power outage time, This is the amount of load loss. for Power supply deficit at any given time for The load demand at any given moment.

[0191] Among them, the power generation cost of the photovoltaic power station Including operating and management costs and investment depreciation costs, expressed as:

[0192] ,

[0193] ,

[0194] ,

[0195] in, For the operation and management costs of photovoltaic power plants, This represents the unit operation and management cost coefficient for photovoltaic power plants. The investment depreciation cost of a photovoltaic power station. This refers to the service life of a photovoltaic power station. The initial investment cost per unit capacity of a photovoltaic power plant. For photovoltaic capacity factor, The discount rate;

[0196] The power generation cost of the solar thermal power plant Including the cost of thermal storage and the cost of generating electricity through the steam turbine from the thermal storage system, expressed as:

[0197] ,

[0198] ,

[0199] ,

[0200] In the formula, For the heat storage cost of solar thermal power plants, The unit initial investment cost of the thermal storage tank. For the installed capacity of the thermal storage tank, The service life of the thermal storage tank. The cost of electricity generated by a solar thermal power plant, This represents the power generation cost coefficient of a solar thermal power plant. for The electrical power output of the solar thermal power plant at any given time;

[0201] In photovoltaic-solar thermal power generation systems, due to the prediction errors and inherent volatility of photovoltaics, as well as the limitations of solar thermal energy storage and power generation capacity, the system may be forced to cut off loads during certain periods to maintain stability. This can negatively impact the system's economics. The aforementioned load shedding costs... Represented as:

[0202] ,

[0203] ,

[0204] in, The unit compensation cost for constant load shedding for Constantly cutting off load power, for The load requirements of the power generation system at all times;

[0205] When electricity demand is low or the grid dispatch capacity is insufficient, the electricity generated by photovoltaic power plants cannot be fully utilized, resulting in curtailment. For concentrated solar power plants, the capacity limitations of the thermal storage tanks cause the concentrators to actively discard some of the heat energy, also resulting in curtailment.

[0206] The cost of abandoned light Represented as:

[0207] ,

[0208] ,

[0209] ,

[0210] in, The unit compensation fee for the curtailed solar power generated by photovoltaic power plants. for The amount of curtailed solar power from photovoltaic power plants at all times. Compensation cost per unit for wasted solar thermal energy from solar thermal power plants. For the waste solar heat from solar thermal power plants, for The maximum output power of the photovoltaic power station at any given time. for The heat output from the constant-time mirror field focusing light, for The actual heat transferred to the heat storage tank at all times;

[0211] Insufficient power supply to the system can cause harm to users and affect their satisfaction with electricity use. Since the output of photovoltaic power is uncertain, the output of thermal power units can be used to offset the load demand. However, there are still periods of load loss, which reduces the reliability of system operation. Therefore, it is necessary to establish power supply reliability indicators for photovoltaic-solar power generation systems, mainly considering the two factors of load power loss time and load loss amount.

[0212] To describe the time of insufficient power supply to the load, the system power outage time is... With power supply time The ratio is defined as the system load power shortage time probability. Represented as:

[0213] ,

[0214] The amount of load loss Define the power supply deficit rate as the amount of power supply deficit during the system scheduling cycle. With load demand The ratio is expressed as:

[0215] ,

[0216] Furthermore, the constraints of the overall objective function include

[0217] Power balance constraints:

[0218] ,

[0219] Photovoltaic power plant output constraints:

[0220] ,

[0221] The constraints here are based on the predicted output of the photovoltaic power station. The photovoltaic power station output constraints given above describe the relationship between the upper and lower limits of the actual output of the photovoltaic power station and the prediction deviation. These are ideal constraints. However, in actual engineering, using the predicted value as the constraint is sufficient to meet the requirements.

[0222] Electric heating capacity constraints:

[0223] ,

[0224] Output constraints of solar thermal power plants:

[0225] ,

[0226] Climbing constraints:

[0227] ,

[0228] Thermal constraints of thermal storage systems:

[0229] ,

[0230] ,

[0231] To ensure the uninterrupted operation of the solar thermal power plant, the thermal storage system needs to maintain a certain capacity for dispatch within a cycle. Therefore, the initial capacity of the thermal storage system in each dispatch cycle is set to be equal to the final capacity at the end of the cycle, i.e. ,

[0232] Thermal constraint of the mirror field concentrator:

[0233] ,

[0234] This can be understood as the heat entering the heat storage tank through the mirror field concentrator should not exceed the current thermal energy output power of the mirror field concentrator.

[0235] in, for The predicted minimum output power of a photovoltaic power station at any given time. for Predicted maximum output power of photovoltaic power station at any given time. for The maximum electric heating power at any given time. for The minimum electrical power output of the solar thermal power plant at any given time. for The maximum electrical power output of the solar thermal power plant at any given time. for The electrical power output of the solar thermal power plant at any given time. This represents the maximum uphill power output of a solar thermal power plant. This represents the maximum downhill ramp power of the solar thermal power plant. This represents the minimum heat storage capacity of the thermal storage tank. This represents the maximum heat storage capacity of the thermal storage tank. for The amount of heat stored in the thermal storage tank at any given time indicates... The heat storage capacity changes constantly due to the inflow and outflow of heat from the thermal storage tank. for The amount of heat lost in the thermal storage tank at all times. For the thermal storage tank in The total amount of heat added at any given moment.

[0236] Step Six: Under the premise of satisfying the constraints, solve the overall objective function using the multi-objective genetic algorithm NSGA-II to obtain the Pareto solution set. Then, obtain the optimal compromise solution from the Pareto solution set using the maximum satisfaction method in fuzzy control theory, including:

[0237] Based on the optimized decision variables, an initial population of size N is randomly generated according to the constraints, serving as the parent population for the first iteration. ;

[0238] The decision vector includes: photovoltaic power generation. Electric heating converts electrical energy The energy flowing into the thermal storage tank from the mirror field concentrator The power generation of solar thermal power plants :

[0239] Encoding the optimized decision variables is represented in a "chromosome," where each decision variable in the "chromosome" is... Write them as 1, 2, 3, ... ,in For the scheduling cycle, the length of the chromosome is... The "chromosome" can be mathematically represented as a 4-chromosome. A vector of size *1, representing the randomly generated initial population. It can be described as a 4 The matrix is ​​multiplied by N, and subsequent generations are selected, crossovered, and mutated based on this initial population.

[0240] Parental population For the current population, perform a fast non-dominated sort on the solutions in the current population and calculate the virtual crowding distance of the solutions in the current population.

[0241] Based on the non-dominance level and crowding distance of individuals, genetic operations are performed according to preset selection probabilities, recombination rates, and mutation rates to generate a new offspring population of size N. ;

[0242] The parent population (in the first iteration, the parent population refers to the initial population) The offspring population is merged into a population of size 2N. Then, a selection based on fast non-dominated sorting and virtual crowding distance is performed to generate a next-generation parent population of size N. ;

[0243] Parental population For the current population, the iteration is repeated, and the Pareto optimal solution set is obtained after a preset number of iterations.

[0244] The multi-objective genetic algorithm NSGA-II ultimately outputs a Pareto optimal solution set, rather than a single solution. Since maximizing economic benefit and maximizing reliability are two conflicting objectives, they cannot both be optimally achieved simultaneously. After obtaining the Pareto optimal solution set, fuzzy control theory is used to calculate the standardized satisfaction of the unmatched solutions with respect to different objective functions. The unmatched solution with the highest standardized satisfaction is selected, called the optimal compromise solution.

[0245] In the multi-objective genetic algorithm NSGA-II for photovoltaic-solar thermal power generation systems with electrothermal physics coupling, since the two objective function tables are economy and reliability respectively, the goal of multi-objective optimization scheduling is to pursue the highest possible grid-connected economic benefits and reliability levels. Therefore, a fuzzy satisfaction function should be selected with a larger satisfaction function, so that the larger the objective function value, the closer the fuzzy satisfaction function value is to 1.

[0246] Regarding the economic and reliability indices of the Pareto optimal solution set, the corresponding analytical expressions of the skewed fuzzy satisfaction function can be obtained by solving for them as follows:

[0247] ,

[0248] ,

[0249] in, For economical standardization of satisfaction, For the standardization of reliability satisfaction, and The x and y axes represent the values ​​in the Pareto optimal solution set, corresponding to economy and reliability, respectively. and Corresponding to minimum and maximum economic efficiency, and Corresponding to minimum and maximum reliability;

[0250] After determining the skewed fuzzy satisfaction function, the standardized satisfaction of each non-dominated solution is calculated as follows:

[0251] ,

[0252] in, For the corresponding number Standardized satisfaction of a non-dominated solution The number of non-dominated solutions. and The first Standardized satisfaction with the economy and reliability of a non-dominated solution;

[0253] By using the maximum satisfaction method in fuzzy control theory, the non-dominated solution with the highest standardized satisfaction is selected as the optimal compromise solution. Regarding how to achieve optimal scheduling of the photovoltaic-solar thermal power generation system that satisfies both economic efficiency and reliability based on the optimal compromise solution, it can be understood that the photovoltaic-solar thermal power generation system can be controlled to generate electricity by relying on the parameter solution obtained from the optimal compromise solution, thereby achieving optimal scheduling that satisfies both economic efficiency and reliability.

[0254] Example 2:

[0255] Embodiment 2 of the present invention provides an optimized scheduling device for a photovoltaic-solar thermal power generation system, comprising:

[0256] The power acquisition module is used to acquire the real-time electrical power generated by photovoltaic power plants and solar thermal power plants;

[0257] The power summation module is used to calculate the sum of the real-time power generated by the photovoltaic power station and the solar thermal power station based on the real-time power generated by the photovoltaic power station and the solar thermal power station.

[0258] The power difference module is used to calculate the difference between the real-time power generation and the power required by the power generation system load to obtain the electric heating power, and store the electric heating power in the heat storage tank of the solar thermal power plant.

[0259] The photovoltaic power plant grid-connected power acquisition module is used to obtain the grid-connected power of the photovoltaic power plant based on the real-time power generation and electric heating power of the photovoltaic power plant.

[0260] The overall objective function establishment module is used to establish an overall objective function with the economic benefits and reliability level of the photovoltaic-solar thermal power generation system as indicators, based on the real-time power generation of the solar thermal power plant, the grid-connected power of the photovoltaic power plant, and the power required by the power generation system load.

[0261] The solution module is used to solve the overall objective function using the multi-objective genetic algorithm NSGA-II under the premise of satisfying the constraints, obtain the Pareto solution set, obtain the optimal compromise solution in the Pareto solution set using the maximum satisfaction method in fuzzy control theory, and realize the optimal scheduling of the photovoltaic-solar thermal power generation system to meet the requirements of economy and reliability based on the optimal compromise solution.

[0262] The photovoltaic-solar thermal power generation system optimization scheduling device provided in Embodiment 2 of the present invention can execute the photovoltaic-solar thermal power generation system optimization scheduling method provided in Embodiment 1 of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0263] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0264] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0265] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0266] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0267] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing the scheduling of a photovoltaic-concentrated thermal power generation system, characterized in that, include: To obtain the real-time electrical power generated by photovoltaic power plants and solar thermal power plants; Calculate the sum of the real-time power output of the photovoltaic power station and the solar thermal power station based on their real-time power generation data. When the real-time power generation exceeds the power required by the power generation system load, the difference is calculated to obtain the electric heating power, which is then stored in the thermal storage tank of the solar thermal power plant. The grid-connected power of the photovoltaic power station is obtained based on the real-time power generation and electric heating power of the photovoltaic power station. Based on the real-time power generation of the solar thermal power plant, the grid-connected power of the photovoltaic power plant, and the power required by the power generation system load, a general objective function is established with the economic benefits and reliability level of the photovoltaic-solar thermal power generation system as indicators. Under the premise of satisfying the constraints, the overall objective function is solved by the multi-objective genetic algorithm NSGA-II to obtain the Pareto solution set. The optimal compromise solution is obtained from the Pareto solution set by the maximum satisfaction method in fuzzy control theory. Based on the optimal compromise solution, the photovoltaic-solar thermal power generation system is optimized to meet the requirements of economy and reliability.

2. The photovoltaic-solar thermal power generation system optimization scheduling method according to claim 1, characterized in that, Also includes: When the real-time power generation of the photovoltaic power station is less than the power required by the power generation system load, the heat storage tank is controlled to release heat to generate electricity until the real-time power generation equals the power required by the power generation system load.

3. The photovoltaic-solar thermal power generation system optimization scheduling method according to claim 1, characterized in that, Obtaining the real-time output power of a photovoltaic power station includes: ， in, The rated output power calculated for a photovoltaic power station represents the maximum power generation capacity of the photovoltaic power station at present. To determine the conversion efficiency of a photovoltaic power plant under standard test conditions, This is a temperature coefficient, representing the percentage decrease in efficiency for every 1 degree Celsius increase in temperature. for The ambient temperature at any given time for Sunlight intensity at any given time This refers to the nominal operating battery temperature. This refers to the total area of ​​the photovoltaic panels; To ensure safe and stable operation of photovoltaic power plants during dispatch, the real-time output power of the photovoltaic power plants should meet the following conditions: ， in, , ， in, for The real-time output power of the photovoltaic power station. for The minimum output power of a photovoltaic power station at any given time. for The maximum output power of the photovoltaic power station at any given time. for The predicted value, for The prediction error for The predicted value, for The prediction error.

4. The photovoltaic-solar thermal power generation system optimization scheduling method according to claim 2, characterized in that, The expressions for obtaining the electric heating power by subtraction include: ， in, yes Electric heating power at any time for The electrical power output of the solar thermal power plant at any given time. for The load requirements of the power generation system at all times for The real-time output power of the photovoltaic power station; Based on the aforementioned electric heating power, electrothermal energy is generated through an electric heating device, and the expression for the electrothermal energy includes: ， in, yes The electric heat energy generated by the electric heating device at all times Energy conversion efficiency of electric heating devices; The amount of heat added to the thermal storage tank due to the electric heating device is: ， in, Because of the increased heat from the electric heating device, To improve the efficiency of thermal storage charging.

5. The photovoltaic-solar thermal power generation system optimization scheduling method according to claim 4, characterized in that, The electrical power generated in real time by a concentrated solar power (CSP) plant includes: The heat in the thermal storage tank also originates from the solar thermal power plant's mirror field concentrating solar collector, whose instantaneous concentrating heat power is: ， in, for The heat output from the constant-time mirror field focusing light, for Sunlight intensity at any given time For concentrating heat collection area, For heat collection efficiency; The actual heat transferred to the thermal storage tank is obtained based on the instantaneous thermal power of the concentrated solar collector, and the expression includes: ， In the formula, for The actual amount of heat transferred to the heat storage tank at all times. for The waste solar thermal power plant's solar thermal energy; The heat added to the thermal storage tank in a concentrated solar power plant due to the focusing effect of the mirror field is: ， in, The heat generated in the thermal storage tank due to the focusing of light by the mirror field. To improve the efficiency of thermal storage charging; Obtaining thermal storage tanks The total amount of heat added at each moment : ， When the thermal storage tank releases heat and discharges, the amount of heat lost inside the tank is: , There are losses during the transfer of heat to the solar thermal power plant; therefore, the actual amount of heat output from the heat storage tank to the solar thermal power plant is... for: ， in, for The heat output of the thermal storage tank at all times for The amount of heat lost in the thermal storage tank at all times. For thermal storage discharge efficiency; Solar thermal power plants pass The generator produces electrical energy, which is: ， in, for The real-time power output of a solar thermal power plant. It refers to the power generation efficiency of a solar thermal power plant.

6. The photovoltaic-solar thermal power generation system optimization scheduling method according to claim 1, characterized in that, The overall objective function includes: ， ， in, The objective function is the economic benefit. For the scheduling period, and They are respectively The on-grid electricity price of photovoltaic and solar thermal power plants at any given time. for The grid-connected power generation of the photovoltaic power station at any time for The real-time output power of the photovoltaic power station. for Electric heating power at any time for The output power of the solar thermal power plant at any time The cost of electricity generated by a photovoltaic power plant. The cost of electricity generated by a solar thermal power plant, and Costs associated with system load shedding and light curtailment; For the reliability level objective function, To represent system reliability indicators, The probability of system load power shortage time. For system power outage time, This is the amount of load loss. for Power supply deficit at any given time for The load demand at any given moment.

7. The photovoltaic-solar thermal power generation system optimization scheduling method according to claim 6, characterized in that, The power generation cost of the photovoltaic power station Including operating and management costs and investment depreciation costs, expressed as: ， ， ， in, For the operation and management costs of photovoltaic power plants, This represents the unit operation and management cost coefficient for photovoltaic power plants. The investment depreciation cost of a photovoltaic power station. This refers to the service life of a photovoltaic power station. The initial investment cost per unit capacity of a photovoltaic power plant. For photovoltaic capacity factor, The discount rate; The power generation cost of the solar thermal power plant Including thermal storage costs and power generation costs, expressed as: ， ， ， In the formula, For the heat storage cost of solar thermal power plants, The unit initial investment cost of the thermal storage tank. For the installed capacity of the thermal storage tank, The service life of the thermal storage tank. The cost of electricity generated by a solar thermal power plant, This represents the power generation cost coefficient of a solar thermal power plant. for The electrical power output of the solar thermal power plant at any given time; The load shedding cost Represented as: ， ， in, The unit compensation cost for constant load shedding for Constantly cutting off load power, for The load requirements of the power generation system at all times; The cost of abandoned light Represented as: ， ， ， in, The unit compensation fee for the curtailed solar power generated by photovoltaic power plants. for The amount of curtailed solar power from photovoltaic power plants at all times. Compensation cost per unit for wasted solar thermal energy from solar thermal power plants. For the waste solar heat from solar thermal power plants, for The maximum output power of the photovoltaic power station at any given time. for The heat output from the constant-time mirror field focusing light, for The actual heat transferred to the heat storage tank at all times; The probability of system load power outage time Represented as: ， The amount of load loss Represented as: ， The constraints of the overall objective function include Power balance constraints: ， Photovoltaic power plant output constraints: ， Electric heating capacity constraints: ， Output constraints of solar thermal power plants: ， Climbing constraints: ， Thermal constraints of thermal storage systems: ， ， Thermal constraint of the mirror field concentrator: ， in, for The predicted minimum output power of a photovoltaic power station at any given time. for Predicted maximum output power of photovoltaic power station at any given time. for The maximum electric heating power at any given time. for The minimum electrical power output of the solar thermal power plant at any given time. for The maximum electrical power output of the solar thermal power plant at any given time. for The electrical power output of the solar thermal power plant at any given time. This represents the maximum uphill power output of a solar thermal power plant. This represents the maximum downhill ramp power of the solar thermal power plant. This represents the minimum heat storage capacity of the thermal storage tank. This represents the maximum heat storage capacity of the thermal storage tank. for The amount of heat stored in the thermal storage tank at all times. for The amount of heat lost in the thermal storage tank at all times. For the thermal storage tank in The total amount of heat added at any given moment.

8. The photovoltaic-solar thermal power generation system optimization scheduling method according to claim 1, characterized in that, Under the premise of satisfying the constraints, the overall objective function is solved by the multi-objective genetic algorithm NSGA-II to obtain the Pareto solution set. The optimal compromise solution is obtained from the Pareto solution set by the maximum satisfaction method in fuzzy control theory, including: Based on the optimized decision variables, an initial population of size N is randomly generated according to the constraints, serving as the parent population for the first iteration. ; Parental population For the current population, perform a fast non-dominated sort on the solutions in the current population and calculate the virtual crowding distance of the solutions in the current population. Based on the non-dominance level and crowding distance of individuals, genetic operations are performed according to preset selection probabilities, recombination rates, and mutation rates to generate a new offspring population of size N. ; The parent and offspring populations are merged into a single population of size 2N. Then, a selection based on fast non-dominated sorting and virtual crowding distance is performed to generate a next-generation parent population of size N. ; Parental population For the current population, the iteration is repeated, and the Pareto optimal solution set is obtained after a preset number of iterations. Regarding the economic and reliability indices of the Pareto optimal solution set, the corresponding analytical expressions of the skewed fuzzy satisfaction function can be obtained by solving for them as follows: ， ， in, For economical standardization of satisfaction, For the standardization of reliability satisfaction, and The x and y axes represent the values ​​in the Pareto optimal solution set, corresponding to economy and reliability, respectively. and Corresponding to minimum and maximum economic efficiency, and Corresponding to minimum and maximum reliability; After determining the skewed fuzzy satisfaction function, the standardized satisfaction of each non-dominated solution is calculated as follows: ， in, For the corresponding number Standardized satisfaction of a non-dominated solution The number of non-dominated solutions. and The first Standardized satisfaction with the economy and reliability of a non-dominated solution; By using the maximum satisfaction method in fuzzy control theory, the non-dominated solution with the highest standardized satisfaction is selected as the optimal compromise solution; The decision vector includes: photovoltaic power generation. Electric heating converts electrical energy The energy flowing into the thermal storage tank from the mirror field concentrator The power generation of solar thermal power plants .

9. A photovoltaic-solar thermal power generation system optimization scheduling device, characterized in that, include: The power acquisition module is used to acquire the real-time electrical power generated by photovoltaic power plants and solar thermal power plants; The power summation module is used to calculate the sum of the real-time power generated by the photovoltaic power station and the solar thermal power station based on the real-time power generated by the photovoltaic power station and the solar thermal power station. The power difference module is used to calculate the difference between the real-time power generation and the power required by the power generation system load to obtain the electric heating power, and store the electric heating power in the heat storage tank of the solar thermal power plant. The photovoltaic power plant grid-connected power acquisition module is used to obtain the grid-connected power of the photovoltaic power plant based on the real-time power generation and electric heating power of the photovoltaic power plant. The overall objective function establishment module is used to establish an overall objective function with the economic benefits and reliability level of the photovoltaic-solar thermal power generation system as indicators, based on the real-time power generation of the solar thermal power plant, the grid-connected power of the photovoltaic power plant, and the power required by the power generation system load. The solution module is used to solve the overall objective function using the multi-objective genetic algorithm NSGA-II under the premise of satisfying the constraints, obtain the Pareto solution set, obtain the optimal compromise solution in the Pareto solution set using the maximum satisfaction method in fuzzy control theory, and realize the optimal scheduling of the photovoltaic-solar thermal power generation system to meet the requirements of economy and reliability based on the optimal compromise solution.

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