Coordinated optimization method, device, equipment and medium for wind, light, fire and heat storage system

Abstract

The invention discloses a coordinated optimization method, device and equipment for a wind-light-fire-heat storage system and a medium, and relates to the field of power system optimization, and the method comprises the steps: determining the wind-light predicted generation power at a current moment according to the environment data of a historical time period; determining thermoelectric characteristics, energy storage characteristics and heat storage characteristics of the wind-light-fire heat storage system; determining a wind-light constraint condition according to the wind-light predicted generation power at the current moment; determining an electric power balance constraint condition, a thermal power balance constraint condition, a cogeneration unit constraint condition, an energy storage charging and discharging constraint condition and a heat storage absorbing and discharging constraint condition of the fire heat storage system; under the condition that the thermoelectric characteristic, the energy storage characteristic and the heat storage characteristic are met, the multi-energy constraint condition is used as the constraint, the target function is solved, and the optimal output combination of the wind, light, fire and heat storage system at the current moment is obtained. The dual purposes of improving the energy utilization efficiency and protecting the environment are achieved.

Description

Technical Field

[0001] The present application relates to the field of power system optimization, and in particular to a method, device, equipment and medium for coordinated optimization of a wind, solar, thermal and energy storage system. Background Art

[0002] At present, the rapid development of new energy requires fundamental changes in the structure and operation of the power system, bringing new challenges to the stability and peak load regulation of the power grid. In order to meet these challenges, researchers have constructed a variety of integrated coordinated optimization models, such as wind-solar-storage, wind-solar-hydro-storage, and wind-solar-thermal-storage, and achieved the security and economy of power supply by optimizing the dispatching strategy. These models promote the healthy and sustainable development of the power system.

[0003] Although the current research has made significant progress in multi-energy complementarity and coordinated optimization scheduling, there is a significant scheduling conflict between new energy and traditional thermal power in the winter heating season, which is one of the major challenges facing the current coordinated optimization of energy operations. Although new energy (such as wind power and photovoltaics) can generate a large amount of electricity, its instability makes it difficult to completely replace the peak load regulation of traditional thermal power during peak hours. Especially in the heating season, thermal power not only has to meet daily electricity demand, but also has to bear the responsibility of heating, which makes the contradiction between the coordinated optimization control system in ensuring the reliability of energy supply and meeting environmental protection requirements more acute.

[0004] Therefore, how to develop a new coordination optimization strategy to better coordinate wind, solar, thermal and storage systems, resolve the conflict between the volatility of renewable energy power generation and the stable heating demand of thermal power, and achieve efficient energy utilization and environmental protection has become a problem that needs to be solved urgently. Summary of the invention

[0005] The purpose of this application is to provide a coordinated optimization method, device, equipment and medium for a wind, solar, thermal and storage system, which can ensure the stable supply of electricity and thermal energy during peak demand periods and achieve the dual goals of improving energy utilization efficiency and environmental protection.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a coordinated optimization method for a wind, solar, thermal and energy storage system, comprising:

[0008] Obtain environmental data for historical periods;

[0009] Determine the predicted wind and solar power generation power at the current moment according to the environmental data of the historical period; the predicted wind and solar power generation power includes: the predicted power generation power of the photovoltaic equipment in the wind, solar, thermal and storage system and the predicted power generation power of the wind turbine in the wind, solar, thermal and storage system;

[0010] Determine the thermoelectric characteristics of the cogeneration unit in the wind-solar-thermal-storage system, the energy storage characteristics of the energy storage equipment in the wind-solar-thermal-storage system, and the heat storage characteristics of the heat storage equipment in the wind-solar-thermal-storage system;

[0011] Determine the wind and solar constraint conditions based on the wind and solar power forecast power generation at the current moment;

[0012] Determine the multi-energy constraints and objective function of the thermal energy storage system; the multi-energy constraints include: electric power balance constraints, thermal power balance constraints, combined heat and power unit constraints, wind and solar constraints, energy storage charging and discharging constraints, and heat storage absorption and discharging constraints; the objective function is constructed based on the coal consumption and wind and solar abandonment of the thermal energy storage system;

[0013] Under the condition of satisfying the thermoelectric characteristics, the energy storage characteristics and the heat storage characteristics, the objective function is solved with the multi-energy constraint conditions as constraints to obtain the optimal output combination of the wind, solar, thermal and storage systems at the current moment; the optimal output combination includes: the actual power generation power of the photovoltaic equipment corresponding to the minimum coal consumption and the amount of abandoned wind and solar power, the actual power generation power of the wind turbine, the power supply power of the cogeneration unit, the heating power of the cogeneration unit, the charging and discharging power of the energy storage equipment and the heat absorption and release power of the heat storage equipment.

[0014] In a second aspect, the present application provides a coordinated optimization device for a wind, solar, thermal and storage system, comprising:

[0015] A data acquisition module is used to obtain environmental data for historical periods;

[0016] The wind and solar power generation prediction module is used to determine the wind and solar power prediction power of the wind, solar, thermal and storage system at the current moment based on the environmental data of the historical period;

[0017] A thermoelectric storage characteristic determination module is used to determine the thermoelectric characteristics of the cogeneration unit in the wind-solar-thermal-storage system, the energy storage characteristics of the energy storage device, and the heat storage characteristics of the heat storage device;

[0018] A wind-solar constraint determination module is used to determine wind-solar constraint conditions according to the wind-solar predicted power generation at the current moment;

[0019] The optimization scheduling model determination module is used to determine the multi-energy constraints and objective function of the thermal energy storage system; the multi-energy constraints include: electric power balance constraints, thermal power balance constraints, combined heat and power unit constraints, wind and solar constraints, energy storage charging and discharging constraints, and heat storage absorption and discharging constraints; the objective function is constructed based on the coal consumption and wind and solar abandonment of the thermal energy storage system;

[0020] A solution module is used to solve the objective function under the condition that the thermoelectric characteristics, the energy storage characteristics and the heat storage characteristics are satisfied, taking the multi-energy constraint conditions as constraints, to obtain the optimal output combination of the wind, solar, thermal and storage system at the current moment; the optimal output combination includes: the actual photovoltaic power generation corresponding to the minimum coal consumption and the amount of wind and solar power abandonment, the actual power generation power of the wind turbine, the power supply power of the cogeneration unit, the heating power of the cogeneration unit, the charging and discharging power of the energy storage device and the heat absorption and release power of the heat storage device.

[0021] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-described coordinated optimization methods for wind, solar, thermal and energy storage systems.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described coordinated optimization methods for wind, solar, thermal and energy storage systems.

[0023] According to the specific embodiments provided in this application, this application has the following technical effects:

[0024] The present application provides a coordinated optimization method, device, equipment and medium for wind, solar, thermal and storage systems, integrating wind energy, solar energy, cogeneration energy storage, electrochemical energy storage and heat storage technology, constructing an objective function based on the coal consumption and wind and solar power abandonment of the thermal and storage systems, and constructing multi-energy constraints, which effectively solves the problem of coordinated optimization operation of wind, solar, thermal and storage systems during winter heating, not only ensuring the stable supply of electricity and heat during peak demand periods, but also significantly improving energy utilization efficiency, effectively reducing the coal consumption cost of power generation and heating, and at the same time increasing the absorption rate of new energy, which not only supports the heating needs of residents, but also achieves environmental protection and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 This is an application environment diagram of a coordinated optimization method for a wind-solar-thermal-storage system in an embodiment of the present application;

[0027] Figure 2 A schematic flow chart of a coordinated optimization method for a wind-solar-thermal-storage system provided in one embodiment of the present application;

[0028] Figure 3 A diagram showing the implementation process of a coordinated optimization method for a wind, solar, thermal and energy storage system in a practical application provided by an embodiment of the present application;

[0029] Figure 4 A schematic diagram of changes in predicted wind power and predicted photovoltaic power provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of changes in electric power in an optimization scheduling result provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of the change of thermal power in the optimization scheduling result provided in one embodiment of the present application;

[0032] Figure 7 A schematic diagram of functional modules of a coordinated optimization device for a wind-solar-thermal-storage system provided in another embodiment of the present application;

[0033] Figure 8 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0036] This application develops a new coordination optimization strategy to better coordinate wind, solar, thermal and storage systems to resolve the conflict between the volatility of renewable energy generation and the stable heating demand of thermal power. In addition, this strategy also takes into account environmental impact and optimizes the economic benefits of power generation and heating, thereby achieving the dual goals of efficient energy utilization and environmental protection.

[0037] This application proposes a coordinated optimization method for a wind, solar, thermal and storage system that integrates wind energy, solar energy, cogeneration energy storage, electrochemical energy storage, and heat storage technology to form a multi-source complementary energy supply network. The wind, solar, thermal and storage system is coordinated and optimized with the goal of minimizing the total coal consumption and wind and solar power abandonment of the multi-energy complementary system. This method not only ensures a stable supply of electricity and heat during the winter peak, but also effectively supports residents' heating needs and achieves dual environmental and economic benefits.

[0038] The coordinated optimization method of the wind-solar-thermal-storage system provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the environmental data of the historical period to the server 104. After the server 104 receives the environmental data of the historical period, for the environmental data of the historical period, the server 104 determines the predicted wind and solar power generation power at the current moment according to the environmental data of the historical period; determines the thermoelectric characteristics of the cogeneration unit in the wind, solar, thermal and storage system, the energy storage characteristics of the energy storage equipment, and the heat storage characteristics of the heat storage equipment; determines the wind and solar constraints according to the predicted wind and solar power generation power at the current moment; determines the multi-energy constraints and objective function of the thermal storage system; under the condition of satisfying the thermoelectric characteristics, energy storage characteristics and heat storage characteristics, takes the multi-energy constraints as constraints, solves the objective function, and obtains the optimal output combination of the wind, solar, thermal and storage system at the current moment.

[0039] The server 104 can feed back the optimal output combination obtained at the current moment to the terminal 102. In addition, in some embodiments, the coordinated optimization method of the wind, solar, thermal and energy storage system can also be implemented by the server 104 or the terminal 102 alone, such as the terminal 102 can directly process the environmental data of the historical period, or the server 104 can obtain the environmental data of the historical period from the data storage system and perform video tag processing on the environmental data of the historical period.

[0040] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0041] In an exemplary embodiment, Figure 2 As shown, a coordinated optimization method for a wind-solar-thermal-storage system is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or can be executed by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps 201 to 206. Among them:

[0042] Step 201, obtaining environmental data for a historical period.

[0043] Step 202, determining the predicted wind and solar power generation power at the current moment based on the environmental data of the historical period.

[0044] The predicted wind-solar power generation includes: the predicted power generation of photovoltaic equipment in the wind-solar-thermal storage system and the predicted power generation of wind turbines in the wind-solar-thermal storage system. The wind-solar-thermal storage system includes: photovoltaic equipment, wind turbines, cogeneration units, energy storage equipment and heat storage equipment. The photovoltaic equipment can be a photovoltaic cell, the energy storage equipment can be an electrochemical energy storage device, and the heat storage equipment can be a heat storage tank. Multiple equipment can complement each other to realize power supply and heat supply.

[0045] Step 203, determine the thermoelectric characteristics of the cogeneration unit in the wind-solar-thermal-storage system, the energy storage characteristics of the energy storage equipment in the wind-solar-thermal-storage system, and the heat storage characteristics of the heat storage equipment in the wind-solar-thermal-storage system.

[0046] Step 204, determining the wind and solar power constraint conditions according to the wind and solar power predicted power generation at the current moment.

[0047] Step 205, determining the multi-energy constraints and objective function of the thermal energy storage system.

[0048] Among them, the multi-energy constraints include: electric power balance constraints, thermal power balance constraints, cogeneration unit constraints, wind and solar constraints, energy storage charging and discharging constraints, and heat storage absorption and discharging constraints; the objective function is constructed based on the coal consumption and wind and solar power abandonment of the thermal storage system.

[0049] Step 206, under the condition of satisfying the thermoelectric characteristics, the energy storage characteristics and the heat storage characteristics, taking the multi-energy constraint condition as a constraint, solving the objective function to obtain the optimal output combination of the wind, solar, thermal and storage system at the current moment.

[0050] Among them, the optimal output combination includes: the actual power generation power of the photovoltaic equipment corresponding to the minimum coal consumption and the amount of wind and solar power abandoned, the actual power generation power of the wind turbine, the power supply power of the cogeneration unit, the heating power of the cogeneration unit, the charging and discharging power of the energy storage equipment, and the heat absorption and release power of the heat storage equipment.

[0051] The implementation of the above steps 201 to 206 can ensure the stable supply of electricity and heat during the peak demand period, and achieve the dual goals of improving energy efficiency and protecting the environment.

[0052] In another exemplary embodiment of the present application, step 202 specifically includes:

[0053] 1) Predicting the current environmental data based on the environmental data of the historical period; the environmental data includes: wind speed, light intensity, and ambient temperature.

[0054] 2) Calculate the predicted power generation of the photovoltaic equipment in the wind-solar-thermal-storage system at the current moment based on the current light intensity, the current ambient temperature and the photovoltaic output model.

[0055] According to the photovoltaic output characteristics, the output of photovoltaic equipment is related to the light intensity and ambient temperature. Therefore, the expression of the photovoltaic output model is:

[0056]

[0057] Among them, P pv (t) represents the predicted power generation of the photovoltaic equipment at time t; P STC Indicates the rated power of the photovoltaic equipment; G c (t) represents the radiation intensity at time t (when working), G c (t) is determined according to the light intensity at time t; T c Represents the surface temperature of the photovoltaic device, T c It is determined according to the ambient temperature at time t, which is similar to the ambient temperature; T STC Indicates the rated ambient temperature, T STC =25℃; G STC Indicates the rated value of radiation intensity, G STC =1kW / m 2 ; k represents the power temperature coefficient, and its value is -0.35% / K.

[0058] 3) Calculate the predicted power generation of the wind turbine in the wind-solar-thermal-storage system at the current moment based on the current wind speed and wind turbine output model.

[0059] The basic logic of the fan output characteristic lies in the functional relationship between the angular velocity and the wind speed. The expression of the fan output model is:

[0060]

[0061] Among them, P wt (t) represents the predicted power generation of the wind turbine at time t; v(t) represents the wind speed at time t; v in Indicates the cut-in wind speed, which can be 2.5m / s; v r Indicates the rated wind speed, which can be 14m / s; v out Indicates the cut-out wind speed, which can be 25m / s; P wr Indicates the rated power of the wind turbine, which can be 20MW.

[0062] In another exemplary embodiment of the present application, the cogeneration unit includes: a back pressure unit and an extraction condensing unit.

[0063] The exhaust steam in the steam turbine of the back-pressure unit is all used for heating. The power generation during its operation is limited by the amount of heat supplied. Its electrothermal characteristics can be approximated as a straight line. The expression of the thermoelectric characteristics of the back-pressure unit is:

[0064]

[0065] Among them, P CHP_bp (t) represents the power supply of the back pressure unit at time t; H CHP_bp (t) represents the heating power of the back pressure unit at time t; It represents the lower limit of the power supply of the back pressure unit, which can be set to 0MW; a represents the thermal power coefficient of the back pressure unit.

[0066] The extraction condensing unit refers to a unit in which, after the steam generated by the boiler enters the steam turbine, part of the steam is extracted from the steam turbine for heating, and the remaining steam is used for work. The expression of the thermoelectric characteristics of the extraction condensing unit is:

[0067]

[0068] Among them, condition 1 is Condition 2 is P CHP_cp (t) represents the power supply of the condensing unit at time t; Indicates the lower limit of power supply of extraction condensing unit; Indicates the upper limit of power supply of extraction condensing unit; H CHP_cp (t) represents the heating power of the extraction condensing unit at time t; Indicates the heating power output when the power supply of the extraction condensing unit is minimum, which can be set to 0MW; Indicates the heating power output when the extraction condensing unit has the maximum power supply; It represents the turning point of the heating power of the extraction-condensing unit, which can be set to 400MW; cv represents the reduction of power supply when unit steam is extracted under fixed steam inlet of the extraction-condensing unit; cv1 represents the cv value corresponding to the minimum steam inlet of the steam turbine in the extraction-condensing unit, which can be set to 0.1; cv2 represents the cv value corresponding to the maximum steam inlet of the steam turbine in the extraction-condensing unit, which can be set to 0.5; cm represents the ratio of power supply power to heating power during back pressure operation, which can be approximately regarded as a constant and can be set to 0.

[0069] In another exemplary embodiment of the present application, the expression of the energy storage characteristic is:

[0070]

[0071] Among them, E BAT (t) represents the energy storage capacity of the energy storage device (such as electrochemical energy storage device) at time t; EBAT (t-1) represents the energy storage capacity of the energy storage device at time t-1; P BAT_in (t-1) represents the charging power of the energy storage device at time t-1; P BAT_out (t-1) represents the discharge power of the energy storage device at time t-1; η BAT_in Represents the charging efficiency of the energy storage device; η BAT_out represents the discharge efficiency of the energy storage device; Δt represents the step length of the simulation period to which time t belongs; η BAT_in and η BAT_out Can be set to 0.9.

[0072] In another exemplary embodiment of the present application, the wind-solar-thermal heat storage system with heat storage function has a strong heat supply regulation characteristic, which makes the thermal power supply range of the unit wider. Its operation mode breaks the traditional "heat-to-electricity" operation mode, and improves the heat regulation capacity of the entire system through the heat absorption and release of the heat storage equipment. The expression of the heat storage characteristic is:

[0073]

[0074] Among them, E HS (t) represents the heat storage capacity of the heat storage device at time t; E HS (t-1) represents the heat storage capacity of the heat storage device at time t-1; λ HS_in Indicates the heat absorption efficiency of the heat storage device; H HS_in (t-1) represents the heat absorption power of the heat storage device at time t-1; H HS_out (t-1) represents the heat release power of the heat storage device at time t-1; λ HS_out Indicates the heat release efficiency of the heat storage device; HS_in and λ HS_out Can be set to 0.9.

[0075] In another exemplary embodiment of the present application, the objective function is:

[0076] min(f CHP_bp +f CHP_cp +λf cur );

[0077]

[0078] Among them, f CHP_bp Indicates the coal consumption of the back pressure unit; f CHP_cp represents the coal consumption of the extraction condensing unit; f cur represents the amount of wind and solar power abandoned; λ represents the penalty coefficient; T represents the end time; P CHP_bp (t) represents the power supply of the back pressure unit at time t; H CHP_bp(t) represents the heating power of the back pressure unit at time t; b0, b1, b2, b3, b4, b5 are the coal consumption coefficients of the back pressure unit, which can be set to b0 = 0.0435, b1 = 0.027, b2 = 0.011, b3 = 36.0, b4 = 0.60020, b5 = 1250; P CHP_cp (t) represents the power supply of the condensing unit at time t; H CHP_cp (t) represents the heating power of the extraction condensing unit at time t; c0, c1, c2, c3, c4, c5 are the coal consumption coefficients of the extraction condensing unit, which can be set to c0 = 0.0345, c1 = 0.030, c2 = 0.031, c3 = 14.5, c4 = 4.2, c5 = 2650; P cur_w (t) represents the abandoned power of the wind turbine at time t; P cur_p (t) represents the abandoned power of the photovoltaic equipment at time t.

[0079] The electric power balance constraint condition is:

[0080] P CHP_bp (t)+P CHP_cp (t)+P ws (t)+P ps (t)+P BAT_out (t) = P load (t)+P BAT_in (t);

[0081] Among them, P ws (t) represents the actual power generation of the wind turbine; P ps (t) represents the actual power generation of the photovoltaic equipment; P BAT_out (t) represents the discharge power of the energy storage device at time t; P BAT_in (t) represents the charging power of the energy storage device at time t; P load (t) represents the electrical load at time t.

[0082] The thermal power balance constraint condition is:

[0083] H CHP_bp (t)+H CHP_cp (t)+H HS_out (t) = H load (t)+H HS_in (t);

[0084] Among them, H HS_in (t) represents the heat absorption power of the heat storage device at time t; H HS_out (t) represents the heat release power of the heat storage device at time t; H load (t) represents the heat load at time t.

[0085] The cogeneration unit constraints include: back pressure unit output constraints and extraction condensing unit output constraints. The back pressure unit output constraints are:

[0086]

[0087] in, Indicates the lower limit of the power supply of the back pressure unit, which can be set to 40MW; Indicates the upper limit of the power supply of the back pressure unit, which can be set to 170MW; Indicates the heating power output when the back pressure unit has the minimum power supply, which can be set to 0MW; It indicates the heating power output when the back pressure unit supplies the maximum power, which can be set to 610MW.

[0088] The heat and power supply of the extraction condensing unit can vary within a certain range, and the output constraint of the extraction condensing unit is:

[0089]

[0090] in, Indicates the lower limit of the power supply of the extraction condensing unit, which can be set to 40MW; Indicates the upper limit of the power supply of the extraction condensing unit, which can be set to 170MW; Indicates the heating power output when the power supply of the extraction condensing unit is minimum, which can be set to 0MW; It indicates the heating power output when the extraction condensing unit has the maximum power supply, which can be set to 610MW.

[0091] The scenery constraint conditions are:

[0092] P wt (t) = P ws (t)+P cur_w (t);

[0093] 0≤P ws (t)≤P wt (t);

[0094] 0≤P cur_w (t)≤P wt (t);

[0095] P pv (t) = P ps (t)+P cur_p (t);

[0096] 0≤P ps (t)≤P pv (t);

[0097] 0≤Pcur_p (t)≤P pv (t);

[0098] Among them, P wt (t) represents the predicted power generation of the wind turbine at time t; P pv (t) represents the predicted power generation of the photovoltaic equipment at time t.

[0099] The energy storage charging and discharging constraint conditions are:

[0100]

[0101] in, Indicates the upper limit of the charging power of the energy storage device, which can be set to ±5MW; Indicates the upper limit of the discharge power of the energy storage device, which can be set to ±5MW; δ in1 Indicates the switching state of the energy storage device charging; δ out1 Indicates the switch state of the energy storage device discharging; E BAT (t) represents the energy storage capacity of the energy storage device at time t; Indicates the lower limit of the energy storage capacity of the energy storage device, which can be set to 0; Indicates the upper limit of the energy storage capacity of the energy storage device, which can be set to 50MWh; Indicates the power consumption at the initial moment, which can be set to 20MWh; Indicates the amount of electricity at the end time T. in1 and δ out1 The value of is 0 or 1, ensuring that δ in1 and δ out1 Cannot be 1 at the same time.

[0102] The heat storage absorption and release constraints are:

[0103]

[0104] in, Indicates the upper limit of the heat absorption power of the heat storage device, which can be set to 60MW; represents the upper limit of the heat release power of the heat storage device, which can be set to 50MW; σ in2 Indicates the switching state of the heat storage device absorbing heat; σ out2 Indicates the switch status of the heat storage device releasing heat; E HS (t) represents the heat storage capacity of the heat storage device at time t; Indicates the lower limit of the thermal storage capacity of the thermal storage device, which can be set to 0MWh; Indicates the upper limit of the thermal storage capacity of the thermal storage device, which can be set to 600MWh; Indicates the thermal storage capacity at the initial moment, which can be set to 30MWh; Indicates the heat storage capacity at the end time T. σ in2 and σ out2 The value of is 0 or 1, ensuring that σ in2 and σ out2 Cannot be 1 at the same time.

[0105] The embodiment of this application takes into account the scheduling conflicts between new energy and traditional thermal power, especially in the winter heating season, and proposes a coordinated optimization method for wind, solar, thermal and storage systems, integrating wind energy, solar energy, cogeneration energy storage, electrochemical energy storage and heat storage technology to coordinate and optimize the power system, aiming to minimize the total coal consumption and wind and solar power abandonment of the multi-energy system. This method forms a multi-source complementary energy supply network by optimizing resource allocation and scheduling strategies, improves the new energy absorption rate, enhances the peak-shaving capacity of the power system, and ensures the stability and reliability of energy supply, thereby effectively supporting residents' heating needs and achieving dual environmental and economic benefits.

[0106] Combine the following Figure 3 , a process of the coordinated optimization method of wind, solar, thermal and energy storage systems in practical applications is described, and an example is given to verify the effectiveness of the method.

[0107] The coordinated optimization method of the wind, solar, thermal and energy storage system mainly includes three parts: (1) modeling; (2) establishing multi-energy constraints; (3) establishing and solving the objective function.

[0108] (1) Modeling. By collecting 10 years of relevant data such as wind speed, light intensity, ambient temperature, and air pressure, and substituting them into the photovoltaic output model and wind turbine output model for calculation, the relevant wind and solar power forecast power generation is obtained; the thermoelectric characteristics of the back pressure unit, the thermoelectric characteristics of the extraction condensing unit, the energy storage characteristics of the energy storage device, and the heat storage characteristics of the heat storage device are established.

[0109] (2) Establish multi-energy constraints. Establish electric power balance constraints, thermal power balance constraints, combined heat and power unit constraints, wind and solar constraints, energy storage charging and discharging constraints, and heat storage absorption and discharging constraints.

[0110] (3) Establish and solve the objective function. The wind, solar, thermal and storage system can use the CPLEX solver to establish a system optimization scheduling objective function with the total coal consumption of the wind, solar, thermal and storage system and the minimum amount of wind and solar power curtailment with a penalty coefficient λ as the optimization objectives. Based on the multi-energy constraints and the control strategy of step (1), the objective function of the wind, solar, thermal and storage system is solved to achieve the optimal scheduling of the wind, solar, thermal and storage system.

[0111] The verification example is as follows:

[0112] In this example, a wind power, photovoltaic, cogeneration, electrochemical energy storage, and heat storage system with complementary wind, solar, thermal and thermal energy storage are selected for day-ahead scheduling analysis. The system is configured with a wind farm with a total installed capacity of 100MW, a photovoltaic power station with a total installed capacity of 150MW, a cogeneration unit with a total installed capacity of 340MW (including 1 170MW backpressure unit and 1 170MW extraction condensing unit), as well as electrochemical energy storage equipment with a total capacity of 50MWh and heat storage equipment with a total capacity of 600MWh.

[0113] The output of different generating units in different power stations is used as the optimization variable. The upper and lower limits of the output of each power station are determined according to the installed capacity of different units. The lowest operating cost and coal consumption cost and the least amount of abandoned wind and solar power are taken as the goals. The load forecast value and the forecast value of wind power and photovoltaic power on a typical day in a province are selected for example analysis. Figure 4 As shown, and taking 1h as a scheduling period, the optimized scheduling result is obtained, as shown in Figure 5 and Figure 6 shown.

[0114] Through the analysis of the model solution results, it can be seen that the wind, solar, thermal and storage system shows strong coordination ability in regulating and optimizing electricity and heating demand. During the day, photovoltaic power generation uses radiation intensity to achieve positive peak regulation of power peaks, while at night or when there is insufficient light, photovoltaic power generation stops. At this time, although wind power has a certain power supply capacity, its output is highly random and requires the assistance of other systems to stabilize the power grid.

[0115] In this case, thermal power and heat storage equipment play a particularly critical role. Thermal power can provide stable power output at night or during peak demand periods, while heat storage equipment can store thermal energy and release it during peak periods, effectively balancing the supply and demand of electricity and heat. The introduction of heat storage equipment not only enhances the system's ability to track power loads, but also improves the heating regulation characteristics of the entire system, ensuring the continuity of heating while optimizing the supply and consumption of electricity.

[0116] This multi-energy complementary wind, solar, thermal and storage system reduces the deep peak load regulation and rapid load change operation of thermal power caused by the large volatility of new energy through a fine scheduling strategy, thereby improving the economic operation efficiency and environmental protection benefits of the system, and achieving the dual goals of efficient use of renewable energy and environmental friendliness. By reducing the peak load regulation problem of the power system caused by the volatility of new energy, this application promotes the sustainable development of the power system and provides valuable technical references for regions with similar energy structures.

[0117] Based on the same inventive concept, the embodiment of the present application also provides a wind-solar-thermal-storage system coordinated optimization device for implementing the above-mentioned wind-solar-thermal-storage system coordinated optimization method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in the embodiments of one or more wind-solar-thermal-storage system coordinated optimization devices provided below can refer to the above-mentioned limitations on the wind-solar-thermal-storage system coordinated optimization method, which will not be repeated here.

[0118] In an exemplary embodiment, Figure 7 As shown, a coordinated optimization device for a wind-solar-thermal-storage system is provided, comprising:

[0119] The data acquisition module 701 is used to acquire environmental data of a historical period.

[0120] The wind-solar power generation prediction module 702 is used to determine the wind-solar predicted power generation of the wind-solar thermal energy storage system at the current moment according to the environmental data of the historical period.

[0121] The thermoelectric storage characteristic determination module 703 is used to determine the thermoelectric characteristics of the cogeneration unit in the wind-solar-thermal-storage system, the energy storage characteristics of the energy storage device, and the heat storage characteristics of the heat storage device.

[0122] The wind / solar constraint determination module 704 is used to determine the wind / solar constraint conditions according to the wind / solar predicted power generation at the current moment.

[0123] The optimization scheduling model determines the module 705, which is used to determine the multi-energy constraints and objective function of the thermal energy storage system; the multi-energy constraints include: electric power balance constraints, thermal power balance constraints, cogeneration unit constraints, wind and solar constraints, energy storage charging and discharging constraints, and heat storage absorption and discharging constraints; the objective function is constructed based on the coal consumption and wind and solar power abandonment of the thermal energy storage system.

[0124] The solution module 706 is used to solve the objective function under the condition of satisfying the thermoelectric characteristics, the energy storage characteristics and the heat storage characteristics, taking the multi-energy constraint conditions as constraints, to obtain the optimal output combination of the wind, solar, thermal and storage system at the current moment; the optimal output combination includes: the actual photovoltaic power generation corresponding to the minimum coal consumption and the amount of wind and solar power abandonment, the actual power generation power of the wind turbine, the power supply power of the cogeneration unit, the heating power of the cogeneration unit, the charging and discharging power of the energy storage device and the heat absorption and release power of the heat storage device.

[0125] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 8As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store environmental data for historical periods. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a coordinated optimization method for a wind, solar, thermal and storage system is implemented.

[0126] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0127] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0128] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0129] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0130] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0131] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, etc., but is not limited thereto.

[0132] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0133] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A coordinated optimization method for a wind, solar, thermal and energy storage system, characterized in that: The coordinated optimization method of the wind, solar, thermal and storage system comprises: Obtain environmental data for historical periods; Determine the predicted wind and solar power generation power at the current moment according to the environmental data of the historical period; the predicted wind and solar power generation power includes: the predicted power generation power of the photovoltaic equipment in the wind, solar, thermal and storage system and the predicted power generation power of the wind turbine in the wind, solar, thermal and storage system; Determine the thermoelectric characteristics of the cogeneration unit in the wind-solar-thermal-storage system, the energy storage characteristics of the energy storage equipment in the wind-solar-thermal-storage system, and the heat storage characteristics of the heat storage equipment in the wind-solar-thermal-storage system; Determine the wind and solar constraint conditions based on the wind and solar power forecast power generation at the current moment; Determine the multi-energy constraints and objective function of the thermal energy storage system; the multi-energy constraints include: electric power balance constraints, thermal power balance constraints, combined heat and power unit constraints, wind and solar constraints, energy storage charging and discharging constraints, and heat storage absorption and discharging constraints; the objective function is constructed based on the coal consumption and wind and solar abandonment of the thermal energy storage system; Under the condition of satisfying the thermoelectric characteristics, the energy storage characteristics and the heat storage characteristics, the objective function is solved with the multi-energy constraint conditions as constraints to obtain the optimal output combination of the wind, solar, thermal and storage systems at the current moment; the optimal output combination includes: the actual power generation power of the photovoltaic equipment corresponding to the minimum coal consumption and the amount of abandoned wind and solar power, the actual power generation power of the wind turbine, the power supply power of the cogeneration unit, the heating power of the cogeneration unit, the charging and discharging power of the energy storage equipment and the heat absorption and release power of the heat storage equipment.

2. The coordinated optimization method of wind, solar, thermal and energy storage system according to claim 1 is characterized in that: The predicted wind and solar power generation capacity at the current moment is determined based on the environmental data of the historical period, including: Predicting the current environmental data based on the environmental data of the historical period; the environmental data includes: wind speed, light intensity, and ambient temperature; Calculate the predicted power generation of the photovoltaic equipment in the wind-solar-thermal-storage system at the current moment according to the current light intensity, the current ambient temperature and the photovoltaic output model; The predicted power generation of the wind turbine in the wind-solar-thermal-storage system at the current moment is calculated based on the current wind speed and wind turbine output model.

3. The coordinated optimization method of wind, solar, thermal and energy storage system according to claim 2 is characterized in that: The expression of the photovoltaic output model is: Among them, P pv (t) represents the predicted power generation of the photovoltaic equipment at time t; P STC Indicates the rated power of the photovoltaic equipment; G c (t) represents the radiation intensity at time t, G c (t) is determined according to the light intensity at time t; T c Represents the surface temperature of the photovoltaic device, T c It is determined according to the ambient temperature at time t; T STC Indicates rated ambient temperature; G STC It represents the rated value of radiation intensity; k represents the power temperature coefficient; The expression of the fan output model is: Among them, P wt (t) represents the predicted power generation of the wind turbine at time t; v(t) represents the wind speed at time t; v in Indicates the cut-in wind speed; v r Indicates rated wind speed; v out Indicates the cut-out wind speed; P wr Indicates the rated power of the fan.

4. The coordinated optimization method of wind, solar, thermal and energy storage system according to claim 1 is characterized in that: The cogeneration unit includes: a back pressure unit and an extraction condensing unit; The expression of the thermoelectric characteristics of the back pressure unit is: Among them, P CHP_bp (t) represents the power supply of the back pressure unit at time t; H CHP_bp (t) represents the heating power of the back pressure unit at time t; Indicates the lower limit of the power supply of the back pressure unit; a indicates the thermal power coefficient of the back pressure unit; The expression of the thermoelectric characteristics of the extraction condensing unit is: Among them, condition 1 is Condition 2 is P CHP_cp (t) represents the power supply of the condensing unit at time t; Indicates the lower limit of power supply of extraction condensing unit; Indicates the upper limit of power supply of extraction condensing unit; H CHP_cp (t) represents the heating power of the extraction condensing unit at time t; Indicates the heating power output when the power supply of the extraction condensing unit is minimum; Indicates the heating power output when the extraction condensing unit has the maximum power supply; It indicates the turning point of the heating power of the extraction-condensing unit; cv indicates the reduction of power supply when unit steam is extracted at a fixed steam inlet of the extraction-condensing unit; cv1 indicates the cv value corresponding to the minimum steam inlet of the steam turbine in the extraction-condensing unit; cv2 indicates the cv value corresponding to the maximum steam inlet of the steam turbine in the extraction-condensing unit; cm indicates the ratio of power supply power to heating power during back pressure operation.

5. The coordinated optimization method of wind, solar, thermal and energy storage system according to claim 1 is characterized in that: The expression of the energy storage characteristic is: Among them, E BAT (t) represents the energy storage capacity of the energy storage device at time t; E BAT (t-1) represents the energy storage capacity of the energy storage device at time t-1; P BAT_in (t-1) represents the charging power of the energy storage device at time t-1; P BAT_out (t-1) represents the discharge power of the energy storage device at time t-1; η BAT_in Represents the charging efficiency of the energy storage device; η BAT_out Represents the discharge efficiency of the energy storage device; Δt represents the step size of the simulation period to which time t belongs.

6. The coordinated optimization method of wind, solar, thermal and energy storage system according to claim 1 is characterized in that: The expression of the heat storage characteristic is: Among them, E HS (t) represents the heat storage capacity of the heat storage device at time t; E HS (t-1) represents the heat storage capacity of the heat storage device at time t-1; λ HS_in Indicates the heat absorption efficiency of the heat storage device; H HS_in (t-1) represents the heat absorption power of the heat storage device at time t-1; H HS_out (t-1) represents the heat release power of the heat storage device at time t-1; λ HS_out represents the heat release efficiency of the heat storage device; Δt represents the step length of the simulation period to which time t belongs.

7. The coordinated optimization method of wind, solar, thermal and energy storage system according to claim 1 is characterized in that: The objective function is: min(f CHP_bp +f CHP_cp +λf cur ); Among them, f CHP_bp Indicates the coal consumption of the back pressure unit; f CHP_cp represents the coal consumption of the extraction condensing unit; f cur represents the amount of wind and solar power abandoned; λ represents the penalty coefficient; T represents the end time; P CHP_bp (t) represents the power supply of the back pressure unit at time t; H CHP_bp (t) represents the heating power of the back pressure unit at time t; b0, b1, b2, b3, b4, b5 are the coal consumption coefficients of the back pressure unit; P CHP_cp (t) represents the power supply of the condensing unit at time t; H CHP_cp (t) represents the heating power of the extraction condensing unit at time t; c0, c1, c2, c3, c4, c5 are the coal consumption coefficients of the extraction condensing unit; P cur_w (t) represents the abandoned power of the wind turbine at time t; P cur_p (t) represents the abandoned power of the photovoltaic equipment at time t; The electric power balance constraint condition is: P CHP_bp (t)+P CHP_cp (t)+P ws (t)+P ps (t)+P BAT_out (t)=P load (t)+P BAT_in (t); Among them, P ws (t) represents the actual power generation of the wind turbine; P ps (t) represents the actual power generation of the photovoltaic equipment; P BAT_out (t) represents the discharge power of the energy storage device at time t; P BAT_in (t) represents the charging power of the energy storage device at time t; P load (t) represents the electric load at time t; The thermal power balance constraint condition is: H CHP_bp (t)+H CHP_cp (t)+H HS_out (t)=H load (t)+H HS_in (t); Among them, H HS_in (t) represents the heat absorption power of the heat storage device at time t; H HS_out (t) represents the heat release power of the heat storage device at time t; H load (t) represents the heat load at time t; The cogeneration unit constraints include: back pressure unit output constraints and extraction condensing unit output constraints; The output constraint of the back pressure unit is: in, Indicates the lower limit of the power supply of the back pressure unit; Indicates the upper limit of the power supply of the back pressure unit; Indicates the heating power output when the back pressure unit has the minimum power supply; Indicates the heating power output when the back pressure unit has the maximum power supply; The output constraint of the extraction condensing unit is: in, Indicates the lower limit of power supply of extraction condensing unit; Indicates the upper limit of power supply of extraction condensing unit; Indicates the heating power output when the power supply of the extraction condensing unit is minimum; Indicates the heating power output when the extraction condensing unit has the maximum power supply; The scenery constraint conditions are: P wt (t)=P ws (t)+P cur_w (t); 0≤P ws (t)≤P wt (t); 0≤P cur_w (t)≤P wt (t); P pv (t)=P ps (t)+P cur_p (t); 0≤P ps (t)≤P pv (t); 0≤P cur_p (t)≤P pv (t); Among them, P wt (t) represents the predicted power generation of the wind turbine at time t; P pv (t) represents the predicted power generation of the photovoltaic equipment at time t; The energy storage charging and discharging constraint conditions are: in, Indicates the upper limit of the charging power of the energy storage device; Indicates the upper limit of the discharge power of the energy storage device; δ in1 Indicates the switching state of the energy storage device charging; out1 Indicates the switch state of the energy storage device discharging; E BAT (t) represents the energy storage capacity of the energy storage device at time t; Indicates the lower limit of the energy storage capacity of the energy storage device; Indicates the upper limit of the energy storage capacity of the energy storage device; Indicates the charge at the initial moment; Indicates the amount of electricity at the end time T; The heat storage absorption and release constraints are: in, Indicates the upper limit of the heat absorption power of the heat storage device; Represents the upper limit of the heat release power of the heat storage device; σ in2 Indicates the switching state of the heat storage device absorbing heat; σ out2 Indicates the switch status of the heat storage device releasing heat; E HS (t) represents the heat storage capacity of the heat storage device at time t; Indicates the lower limit of the heat storage capacity of the heat storage device; Indicates the upper limit of the heat storage capacity of the heat storage device; represents the heat storage capacity at the initial moment; Indicates the thermal storage capacity at the end time T.

8. A coordinated optimization device for a wind, solar, thermal and storage system, characterized in that: The coordinated optimization device of the wind, solar, thermal and storage system comprises: A data acquisition module is used to obtain environmental data for historical periods; The wind and solar power generation prediction module is used to determine the wind and solar power prediction power of the wind, solar, thermal and storage system at the current moment based on the environmental data of the historical period; A thermoelectric storage characteristic determination module is used to determine the thermoelectric characteristics of the cogeneration unit in the wind-solar-thermal-storage system, the energy storage characteristics of the energy storage device, and the heat storage characteristics of the heat storage device; A wind-solar constraint determination module is used to determine wind-solar constraint conditions according to the wind-solar predicted power generation at the current moment; The optimization scheduling model determination module is used to determine the multi-energy constraints and objective function of the thermal energy storage system; the multi-energy constraints include: electric power balance constraints, thermal power balance constraints, combined heat and power unit constraints, wind and solar constraints, energy storage charging and discharging constraints, and heat storage absorption and discharging constraints; the objective function is constructed based on the coal consumption and wind and solar abandonment of the thermal energy storage system; A solution module is used to solve the objective function under the condition that the thermoelectric characteristics, the energy storage characteristics and the heat storage characteristics are satisfied, taking the multi-energy constraint conditions as constraints, to obtain the optimal output combination of the wind, solar, thermal and storage system at the current moment; the optimal output combination includes: the actual photovoltaic power generation corresponding to the minimum coal consumption and the amount of wind and solar power abandonment, the actual power generation power of the wind turbine, the power supply power of the cogeneration unit, the heating power of the cogeneration unit, the charging and discharging power of the energy storage device and the heat absorption and release power of the heat storage device.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the coordinated optimization method for a wind, solar, thermal, and energy storage system according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the coordinated optimization method for the wind, solar, thermal and energy storage system described in any one of claims 1 to 7 is implemented.

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