Optimized scheduling method, device, equipment and medium for wind-solar coupled combined heat and power generation unit

Abstract

The embodiment of the invention provides an optimal scheduling method, device and equipment for a wind-solar coupled cogeneration unit and a medium, and belongs to the technical field of energy optimal scheduling. The method comprises the steps that user electric heating loads, wind and light generating capacity and the like serve as input, an objective function is constructed, constraints are set, then an MDP-DDPG algorithm is adopted for optimization solving, the optimal user side electric loads, user side heat loads, wind power generating capacity, photovoltaic generating capacity, steam pipeline pressure, boiler coal feeding capacity and steam turbine heat supply steam extraction capacity are obtained, and the optimal user side electric loads, the optimal user side heat loads, the optimal wind power generating capacity, the optimal photovoltaic generating capacity, the optimal steam pipeline pressure, the optimal boiler coal feeding capacity and the optimal steam turbine heat supply steam extraction capacity are obtained with the operation cost minimized. And finally, the optimal parameters are issued to a corresponding cogeneration unit, photovoltaic equipment, a wind generating set, a user side heat supply end and a user side power supply end. According to the invention, photovoltaic, wind power and cogeneration units are combined, and an MDP-DDPG algorithm is adopted to realize intelligent scheduling, so that the problem of source load uncertainty is effectively solved, the equipment operation efficiency is optimized, and stable and adaptive operation of the system is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of energy optimization scheduling, and specifically to a wind-solar coupled cogeneration unit optimization scheduling method, a wind-solar coupled cogeneration unit optimization scheduling device, an electronic device and a computer-readable storage medium. Background Art

[0002] In recent years, renewable energy has attracted much attention in the energy field due to its environmental protection and cleanliness, but its intermittent and volatile characteristics limit its widespread integration in the energy system, making the absorption of renewable energy a major challenge currently faced. In the context of promoting the transformation and upgrading of coal-fired power and achieving the dual carbon goals, traditional cogeneration units urgently need to improve their operating flexibility in order to connect to renewable energy on a large scale.

[0003] At present, the strategies for improving the load regulation capacity of cogeneration units mainly include: enhancing the heating capacity of the units and implementing the "thermal-electrical decoupling" technology of the units. Specifically, the technical path to achieve "thermal-electrical decoupling" mainly includes installing heat storage devices and using heat storage in the thermal network.

[0004] However, the existing strategies for load regulation of cogeneration units have the following problems: (1) Most existing studies focus on optimal scheduling under specific scenarios, but there is a lack of research on optimal scheduling under scenarios with source and load uncertainty; (2) Existing research on cogeneration unit scheduling often regards the unit as an overall power output unit for optimal scheduling, ignoring the interaction between the various devices within the unit system.

[0005] In general, the existing strategies for load regulation capabilities of cogeneration units cannot solve the problem of equipment-level efficient, intelligent and real-time scheduling of cogeneration units under source and load uncertainty. Summary of the invention

[0006] The purpose of the embodiments of the present invention is to provide a method, device, equipment and medium for optimizing the scheduling of a wind-solar coupled cogeneration unit, so as to solve the problem that the existing strategies for load regulation capability of cogeneration units cannot solve the problem of efficient, intelligent and real-time scheduling of cogeneration units at the equipment level under source and load uncertainty.

[0007] In order to achieve the above-mentioned purpose, an embodiment of the present invention provides a method for optimizing the scheduling of a wind-solar coupled cogeneration unit, wherein the wind-solar coupled cogeneration unit comprises: a cogeneration unit, a photovoltaic device, a wind turbine generator set, a user-side heating terminal and a user-side power supply terminal, and the method comprises: Taking the user-side electrical load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction of the wind-solar coupled cogeneration unit as input, and the minimum operating cost of the wind-solar coupled cogeneration unit as the target output, the objective function of the wind-solar coupled cogeneration unit is constructed, and the constraints of the objective function of the wind-solar coupled cogeneration unit are determined; The MDP-DDPG algorithm is used to optimize and solve the objective function of the wind-solar coupled cogeneration unit, and determine the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed rate, and turbine heating steam extraction that meet the constraints of the objective function of the wind-solar coupled cogeneration unit; The optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction are sent to the corresponding cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to control the cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to operate according to the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction.

[0008] Optionally, the objective function of the wind-solar coupled cogeneration unit is: ;in, represents the minimum operating cost of the wind-solar coupled cogeneration unit, Indicates the preset coal purchase cost coefficient, represents the coal purchase cost, Indicates the preset heating network state cost coefficient, Indicates the change in internal pressure of the heat network pipeline. represents the preset excess power generation penalty coefficient, Indicates excess power. Indicates the preset power shortage penalty coefficient. Indicates the amount of electricity to be compensated. Indicates the penalty coefficient for excess pressure in the preset heat network pipeline. Indicates excess pressure in the heat network pipeline. Indicates the penalty coefficient for insufficient pressure in the preset heating network pipeline. Indicates insufficient pressure in the heating network pipeline.

[0009] Optionally, the cost of purchased coal is determined by: ;in, represents the coal purchase cost, represents the unit price of coal, Indicates the amount of coal fed to the boiler; The change in internal pressure of the heating network pipeline is determined by: ;in, Indicates the change in internal pressure of the heat network pipeline. Indicates the steam extraction capacity of the steam turbine for heating. Indicates the heat load on the user side; represents the steam constant, Indicates the steam temperature in the heating network pipeline. Indicates the molar mass of steam in the heating network pipeline, Indicates the volume of the heat network pipeline; Excess power is determined as follows: ;in, Indicates excess power. represents the power generation of the cogeneration unit, represents the photovoltaic power generation, represents the wind power generation, Indicates the user side electrical load; The amount of electricity to be compensated is determined by: ;in, Indicates the amount of electricity to be compensated; The excess pressure in the heating network pipeline is determined by: ;in, Indicates excess pressure in the heat network pipeline. Indicates the pressure in the heat network pipeline. Indicates the maximum pressure in the heat network pipeline; The insufficient pressure in the heating network pipeline is determined by: ;in, Indicates insufficient pressure in the heating network pipeline. Indicates the minimum pressure in the heating network pipeline.

[0010] Optionally, the boiler coal feed rate is determined by: ;in, Indicates the amount of coal fed to the boiler. Indicates total calories, Indicates the lower heating value of coal; The power generation of a combined heat and power unit is determined by: ;in, represents the power generation of the cogeneration unit, represents the power generation efficiency of the generator, represents the power generation of high-pressure steam turbine, represents the power generation of the medium-pressure steam turbine, Indicates the power generation of low-pressure steam turbine; Photovoltaic power generation is determined by: ;in, represents the photovoltaic power generation, represents the photovoltaic cell efficiency, represents the inverter efficiency, Represents the effective illumination area, Indicates the intensity of solar radiation; Wind power generation is determined as follows: ;in, represents the wind power generation, Indicates the real-time wind speed. Indicates the starting wind speed. Indicates the shutdown wind speed. Indicates the rated wind speed, Indicates the installed capacity of wind turbines.

[0011] Optionally, the power generation of the high pressure steam turbine is determined by: ;in, represents the power generation of high-pressure steam turbine, represents the efficiency of the high-pressure steam turbine, represents the inlet steam flow rate of the high-pressure steam turbine, represents the enthalpy of the inlet steam of the high-pressure steam turbine, Indicates the enthalpy of the outlet steam of the high-pressure steam turbine; The power generation of the medium pressure steam turbine is determined by: ;in, represents the power generation of the medium-pressure steam turbine, represents the efficiency of the medium pressure turbine, represents the enthalpy of the inlet steam of the medium-pressure turbine, Indicates the enthalpy of the first stage extraction steam of the medium pressure steam turbine, Indicates the enthalpy of the secondary extraction steam of the medium pressure turbine, Indicates the enthalpy value of the three-stage extraction steam of the medium-pressure steam turbine, represents the enthalpy of the outlet steam of the medium-pressure steam turbine, represents the inlet steam flow rate of the medium-pressure steam turbine, Indicates the flow rate of the first stage extraction steam of the medium pressure steam turbine. Indicates the flow rate of the second stage extraction steam of the medium pressure steam turbine, Indicates the flow rate of the third-stage extraction steam of the medium-pressure steam turbine; The power generation of the low-pressure steam turbine is determined by: ;in, represents the power generation of the low-pressure steam turbine, represents the efficiency of the low-pressure steam turbine, represents the enthalpy of the inlet steam of the low-pressure turbine, Indicates the enthalpy of the first stage extraction steam of the low pressure steam turbine, Indicates the enthalpy of the secondary extraction steam of the low-pressure steam turbine, Indicates the enthalpy value of the three-stage extraction steam of the low-pressure steam turbine, represents the enthalpy of the outlet steam of the low-pressure turbine, represents the inlet steam flow rate of the low-pressure turbine, Indicates the flow rate of the first stage extraction steam of the low pressure steam turbine, Indicates the flow rate of the second stage extraction steam of the low pressure steam turbine, Indicates the flow rate of the third-stage extraction steam of the low-pressure steam turbine.

[0012] Optionally, the constraints of the objective function of the wind-solar coupled cogeneration unit include: safe operation constraints; The safe operation constraints are: ;in, Indicates the initial pressure in the heat network pipeline. Indicates the minimum pressure in the heat network pipeline. Indicates the maximum pressure in the heating network pipeline. Indicates the amount of coal fed to the boiler. Indicates the minimum value of boiler coal supply. Indicates the maximum amount of coal fed to the boiler. represents the heat load on the user side, Indicates the steam extraction capacity of the steam turbine for heating. Indicates the minimum value of steam extraction for heating of steam turbine. Indicates the maximum value of steam extraction for heating of steam turbine.

[0013] Optionally, the constraints of the objective function of the wind-solar coupled cogeneration unit include: power balance constraints; The power balance constraints are: ;in, Indicates the user side electrical load, Indicates excess wind power generation. represents the power generation of the cogeneration unit, represents the photovoltaic power generation, represents the wind power generation, Indicates the difference between the steam extraction capacity of the steam turbine and the heat load on the user side. Indicates the steam extraction capacity of the steam turbine for heating. Indicates the heat load on the user side.

[0014] In a second aspect of an embodiment of the present invention, a wind-solar coupled cogeneration unit optimization scheduling device is provided, comprising: A function construction module is used to take the user-side electrical load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating extraction as inputs of the wind-solar-coupled heat and power cogeneration unit, and the minimum operating cost of the wind-solar-coupled heat and power cogeneration unit as the target output, to construct the objective function of the wind-solar-coupled heat and power cogeneration unit, and to determine the constraint conditions of the objective function of the wind-solar-coupled heat and power cogeneration unit; The function solving module is used to optimize and solve the objective function of the wind-solar coupled cogeneration unit by using the MDP-DDPG algorithm, and determine the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction that meet the constraint conditions of the objective function of the wind-solar coupled cogeneration unit; The scheduling and operation module is used to send the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction to the corresponding cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends, so as to control the cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to operate according to the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction.

[0015] In a third aspect of the embodiments of the present invention, an electronic device is provided, including: a processor and a memory, the memory storing machine-readable instructions executable by the processor, and the machine-readable instructions, when executed by the processor, execute the above-mentioned wind-solar coupled cogeneration unit optimization scheduling method.

[0016] In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, storing computer instructions. When the computer instructions are executed on a computer, the computer executes the above-mentioned method for optimizing the scheduling of a wind-solar coupled cogeneration unit.

[0017] Beneficial effects of the present invention: Solve the problem of source-load uncertainty: By combining photovoltaic and wind power generation with cogeneration units, the volatility of photovoltaic and wind power generation can be effectively dealt with, and the system's adaptability to source-load uncertainty can be improved. In addition, the MDP-DDPG algorithm is used for real-time scheduling, which can dynamically adjust the unit operating parameters according to real-time data, quickly respond to source-load changes, and ensure stable system operation. Equipment-level optimization: Equipment-level optimization is performed for cogeneration units, photovoltaic equipment, and wind turbines, and refined control is performed according to the characteristics of each device to improve equipment operation efficiency. Intelligent scheduling: The advanced MDP-DDPG reinforcement learning algorithm is used for optimized scheduling, which can automatically learn and adapt to the system operating environment, realize intelligent scheduling, and can adaptively adjust according to real-time data and system operating status to ensure the real-time and effectiveness of the scheduling strategy. Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent specific implementation method section. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings: Figure 1 It is a flow chart of a method for optimizing the dispatching of a wind-solar coupled cogeneration unit provided by an embodiment of the present invention; Figure 2 Schematic diagram of the system architecture of a wind-solar coupled cogeneration unit provided in an embodiment of the present invention; Figure 3 is a schematic diagram of a wind power generation power-time curve and a photovoltaic power generation power-time curve provided by an embodiment of the present invention; Figure 4 It is a schematic diagram of a user-side electric load-time curve and a user-side thermal load-time curve provided by an embodiment of the present invention; Figure 5 It is a schematic diagram of a DDPG algorithm training reward curve provided in an embodiment of the present invention; Figure 6 It is a structural schematic diagram of a wind-solar coupled cogeneration unit optimization scheduling device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0021] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0022] Embodiment 1 Please refer to Figure 1 , Figure 1 1 is a flow chart of a method for optimizing the dispatching of a wind-solar coupled cogeneration unit provided by an embodiment of the present invention, the method comprising the following steps: S100, taking the user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal supply and turbine heating extraction as inputs, and the minimum operating cost of the wind-solar-coupled heat and power unit as the target output, construct the objective function of the wind-solar-coupled heat and power unit, and determine the constraint conditions of the objective function of the wind-solar-coupled heat and power unit; Specifically, Figure 2 As shown, the wind-solar coupled cogeneration unit includes: a cogeneration unit, a photovoltaic power station, a wind turbine, a user-side heating end and a user-side power supply end; the cogeneration unit also includes: a boiler, a steam turbine, a generator and a steam pipe.

[0023] The user-side electric load usually refers to the total amount of electric energy consumed by the power user within a certain period of time, which reflects the user's electricity demand. The electric load can be classified according to different user types (such as residential, commercial, industrial, etc.) and usage characteristics (such as peak hours and off-peak hours), and is an important parameter for power system planning and operation.

[0024] User-side heat load refers to the total amount of heat energy consumed by users to meet production or living needs within a certain period of time. This usually involves heating, hot water supply, industrial heat treatment and other aspects. The size of the heat load is affected by factors such as external ambient temperature, building insulation performance, and user heating habits.

[0025] Wind power generation refers to the total amount of wind energy converted into electrical energy by wind turbines within a specified time, usually measured in kilowatt-hours (kWh). Wind power generation is affected by factors such as wind speed, wind direction, and the performance of wind turbines.

[0026] Photovoltaic power generation refers to the total amount of solar energy converted into electrical energy by photovoltaic panels within a certain period of time, and is usually measured in kilowatt-hours (kWh). Photovoltaic power generation is affected by factors such as light intensity, photovoltaic panel efficiency, installation angle and orientation.

[0027] Steam pipe pressure refers to the pressure exerted by steam on the inner wall of the steam pipe, usually measured in Pascal (Pa) or Megapascal (MPa). Steam pressure needs to be precisely controlled to ensure the safety and efficiency of industrial production and heating systems.

[0028] Boiler coal feed refers to the mass of coal supplied to the boiler combustion chamber within a certain operating time, usually measured in tons (t). The coal feed needs to be adjusted according to the load demand of the boiler to ensure stable operation and combustion efficiency of the boiler.

[0029] Steam turbine heating extraction refers to the amount of steam extracted from the steam turbine for heating during the cogeneration process, usually in tons per hour (t / h). The amount of steam extraction is directly related to the amount of heat supply and the power generation efficiency of the steam turbine, and needs to be adjusted according to the demand for heat load.

[0030] S200, using the MDP-DDPG algorithm, to optimize and solve the objective function of the wind-solar coupled heat and power cogeneration unit, and determine the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction that meet the constraint conditions of the objective function of the wind-solar coupled heat and power cogeneration unit; In one embodiment, the objective function of the wind-solar coupled cogeneration unit is: ;in, represents the minimum operating cost of the wind-solar coupled cogeneration unit, Indicates the preset coal purchase cost coefficient, represents the coal purchase cost, Indicates the preset heating network state cost coefficient, Indicates the change in internal pressure of the heat network pipeline. represents the preset excess power generation penalty coefficient, Indicates excess power. Indicates the preset power shortage penalty coefficient. Indicates the amount of electricity to be compensated. Indicates the penalty coefficient for excess pressure in the preset heat network pipeline. Indicates excess pressure in the heat network pipeline. Indicates the penalty coefficient for insufficient pressure in the preset heating network pipeline. Indicates insufficient pressure in the heating network pipeline.

[0031] It is understandable that the input parameters in the objective function of the wind-solar coupled heat and power unit seem to be unrelated to the user-side electrical load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal supply and turbine heating steam extraction. In fact, the coal purchase cost is , the change in internal pressure of the heating network pipeline , Excess electricity , Power to be compensated , Excess pressure in the heat network pipeline Insufficient pressure in the heating network pipeline It is related to the user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction, which will be explained in detail later.

[0032] In one embodiment, the coal purchase cost is determined by: ;in, represents the coal purchase cost, represents the unit price of coal, Indicates the amount of coal fed to the boiler.

[0033] Specifically, the boiler coal feed rate is determined by: ;in, Indicates the amount of coal fed to the boiler. Indicates total calories, Indicates the lower heating value of coal.

[0034] In one embodiment, the change in the internal pressure of the heating network pipeline is determined by: ;in, Indicates the change in internal pressure of the heat network pipeline. Indicates the steam extraction capacity of the steam turbine for heating. Indicates the heat load on the user side; represents the steam constant, Indicates the steam temperature in the heating network pipeline. Indicates the molar mass of steam in the heating network pipeline, Represents the volume of the heating network pipeline.

[0035] In one embodiment, the excess power is determined by: ;in, Indicates excess power. represents the power generation of the cogeneration unit, represents the photovoltaic power generation, represents the wind power generation, Indicates the user-side electrical load.

[0036] In one embodiment, the amount of electricity to be compensated is determined by: ;in, Indicates the amount of electricity to be compensated.

[0037] Specifically, the power generation of the cogeneration unit is determined by: ;in, represents the power generation of the cogeneration unit, represents the power generation efficiency of the generator, represents the power generation of high-pressure steam turbine, represents the power generation of the medium-pressure steam turbine, Indicates the power generation of the low-pressure turbine.

[0038] Specifically, the power generation of the high-pressure steam turbine is determined by: ;in, represents the power generation of high-pressure steam turbine, represents the efficiency of the high-pressure steam turbine, represents the inlet steam flow rate of the high-pressure steam turbine, represents the enthalpy of the inlet steam of the high-pressure steam turbine, Indicates the enthalpy of the outlet steam of the high-pressure steam turbine.

[0039] Specifically, the power generation of the medium-pressure steam turbine is determined by: ;in, represents the power generation of the medium-pressure steam turbine, represents the efficiency of the medium pressure turbine, represents the enthalpy of the inlet steam of the medium-pressure turbine, Indicates the enthalpy of the first stage extraction steam of the medium pressure steam turbine, Indicates the enthalpy of the secondary extraction steam of the medium pressure turbine, Indicates the enthalpy value of the three-stage extraction steam of the medium-pressure steam turbine, represents the enthalpy of the outlet steam of the medium-pressure steam turbine, represents the inlet steam flow rate of the medium-pressure steam turbine, Indicates the flow rate of the first stage extraction steam of the medium pressure steam turbine. Indicates the flow rate of the second stage extraction steam of the medium pressure steam turbine, Indicates the flow rate of the third-stage extraction steam of the medium-pressure steam turbine; Specifically, the power generation of the low-pressure steam turbine is determined by: ;in, represents the power generation of the low-pressure steam turbine, represents the efficiency of the low-pressure steam turbine, represents the enthalpy of the inlet steam of the low-pressure turbine, Indicates the enthalpy of the first stage extraction steam of the low pressure steam turbine, Indicates the enthalpy of the secondary extraction steam of the low-pressure steam turbine, Indicates the enthalpy value of the three-stage extraction steam of the low-pressure steam turbine, represents the enthalpy of the outlet steam of the low-pressure turbine, represents the inlet steam flow rate of the low-pressure turbine, Indicates the flow rate of the first stage extraction steam of the low pressure steam turbine, Indicates the flow rate of the second stage extraction steam of the low pressure steam turbine, Indicates the flow rate of the third-stage extraction steam of the low-pressure steam turbine.

[0040] Specifically, photovoltaic power generation is determined by: ;in, represents the photovoltaic power generation, represents the photovoltaic cell efficiency, represents the inverter efficiency, Represents the effective illumination area, Indicates the intensity of solar radiation.

[0041] Specifically, wind power generation is determined by: ;in, represents the wind power generation, Indicates the real-time wind speed. Indicates the starting wind speed. Indicates the shutdown wind speed. Indicates the rated wind speed, Indicates the installed capacity of wind turbines.

[0042] In one embodiment, the excess pressure in the heating network pipeline is determined by: ;in, Indicates excess pressure in the heat network pipeline. Indicates the pressure in the heat network pipeline. Indicates the maximum pressure in the heating network pipeline.

[0043] In one embodiment, the insufficient pressure in the heating network pipeline is determined by: ;in, Indicates insufficient pressure in the heating network pipeline. Indicates the minimum pressure in the heating network pipeline.

[0044] In one embodiment, the constraint conditions of the objective function of the wind-solar coupled cogeneration unit include: safe operation constraint conditions; The safe operation constraints are: ;in, Indicates the initial pressure in the heat network pipeline. Indicates the minimum pressure in the heat network pipeline. Indicates the maximum pressure in the heating network pipeline. Indicates the amount of coal fed to the boiler. Indicates the minimum value of boiler coal supply. Indicates the maximum amount of coal fed to the boiler. represents the heat load on the user side, Indicates the steam extraction capacity of the steam turbine for heating. Indicates the minimum value of steam extraction for heating of steam turbine. Indicates the maximum value of steam extraction for heating of steam turbine.

[0045] In one embodiment, the constraints of the objective function of the wind-solar coupled cogeneration unit include: power balance constraints; The power balance constraints are: ;in, Indicates the user side electrical load, Indicates excess wind power generation. represents the power generation of the cogeneration unit, represents the photovoltaic power generation, represents the wind power generation, Indicates the difference between the steam extraction capacity of the steam turbine and the heat load on the user side. Indicates the steam extraction capacity of the steam turbine for heating. Indicates the heat load on the user side.

[0046] It should be noted that the present invention is aimed at scheduling and optimizing the semi-decoupling problem of heat and electricity for wind-solar coupled cogeneration units, so the parameters in the constructed objective function of the wind-solar coupled cogeneration units will definitely be related to the cogeneration units, photovoltaic equipment and wind turbines. Therefore, the input parameters of the objective function of the wind-solar coupled cogeneration units include the user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed rate and turbine heating extraction steam.

[0047] In addition, the MDP-DDPG algorithm is used to optimize and solve the objective function of the wind-solar coupled cogeneration unit. In essence, it is to optimize the user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction in the objective function of the wind-solar coupled cogeneration unit. Specifically, the user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, and steam pipeline pressure are used as the state space of MDP, and the boiler coal feed and turbine heating steam extraction are used as the action space of MDP. Then, the DDPG algorithm is used for optimization scheduling to obtain the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction.

[0048] In order to better understand the use of the MDP-DDPG algorithm to optimize the objective function of the wind-solar coupled cogeneration unit, the following is a detailed description: Before introducing the MDP-DDPG algorithm, we first explain MDP and DDPG: MDP (Markov Decision Process) is a mathematical framework in reinforcement learning that is used to simulate the decision-making process of an agent in an environment. An MDP consists of the following elements: State set (S): all possible states of the environment.

[0049] Action Set (A): All possible actions that the agent can take.

[0050] Transition probability (P): The probability of taking an action in the current state and transitioning to the next state.

[0051] Reward function (R): The immediate reward that the agent receives after taking an action in a certain state.

[0052] Discount factor (γ): The importance of future rewards relative to current rewards.

[0053] The goal of MDP is to find a policy for the agent that maximizes the long-term accumulated rewards.

[0054] DDPG (Deep Deterministic Policy Gradient) is an algorithm for solving continuous action space reinforcement learning problems. It combines the ideas of deep learning and deterministic policy gradient. The following are several key components of DDPG: Deep neural networks: used to approximate the policy and value function (Q-function).

[0055] Deterministic policies: Compared to random policies, the actions output by DDPG are deterministic, which makes it easier to handle continuous action spaces.

[0056] Replay Buffer: It is used to store the agent’s experience and randomly extract it during training to break the correlation between data.

[0057] Target Network: Used to generate target Q values ​​to stabilize the training process.

[0058] The core idea of ​​DDPG is to use the actor network to output a deterministic policy and use the critic network to evaluate the quality of the policy.

[0059] Step 1 (MDP modeling): The input parameters of the objective function of the wind-solar coupled cogeneration unit are converted into the state space and action space of the MDP framework.

[0060] State space: user-side electrical load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure. The state space can be expressed as: .

[0061] Action space: boiler coal supply and turbine heating steam extraction. The action space can be expressed as: .

[0062] Reward function:

[0063]

[0064]

[0065]

[0066]

[0067] Step 2 (DDPG algorithm implementation) 2.1 Initializing the Neural Network Actor Network: Input state s t , output deterministic strategy a t .

[0068] Critic network: input state s t and action a t , output Q value.

[0069] 2.2 Experience Replay Use an experience replay buffer to store ( ) tuple.

[0070] 2.3 Training Process 2.3.1 Select action: In the current state space, use the Actor network to select action a t , adding random noise to explore the action space: a t =a t +noise.

[0071] 2.3.2 Execute action: Execute the selected action a in the environment t , observe the reward r t and the next state s t+1 For the next state, please refer to Figure 3 and Figure 4 As shown, Figure 3 It shows the wind power generation and photovoltaic power generation at each moment. Figure 4 It shows the user side electricity load and user side heat load at each moment, and the steam pipeline pressure is related to the user side electricity load and user side heat load, so according to Figure 3 and Figure 4 You can know that the selected action a is executed in the environment t The state space at the next moment (that is, wind power generation power, photovoltaic power generation power, user-side electric load, user-side thermal load and steam pipeline pressure).

[0072] 2.3.3 Storage Experience: ) is stored in the experience replay buffer.

[0073] 2.3.4 Sample extraction: Randomly extract a batch of experiences from the experience replay buffer for learning.

[0074] 2.3.5 Update Critic network: Calculate target Q value: Q_target=r t +γ*Q_target_next*(1-done), update the Critic network using the mean square error loss function: loss=MSE(Q_value, Q_target).

[0075] 2.3.6 Update the Actor Network: Update the Actor Network using Gradient Ascent: ∇_θ μ =∇_a t *Q(s t ,a t |θQ)*∇_θ μ (s t |θ μ ), use the gradient of the Critic network to update the Actor network.

[0076] 2.4 Target network update: Soft update target network parameters: θ_target=τ*θ+(1-τ)*θ_target.

[0077] Step 3 (scheduling optimization process): 3.1 Data preprocessing: Each feature in the state space is normalized to be in the range of [0, 1].

[0078] 3.2 State Observation and Action Selection: At each time step, update the state vector s t , using the normalized state vector s t and the Actor network selects the optimal action a t .

[0079] 3.3 Execution of actions and reward observation: Execution of action a t , observe the changes in the environment and the rewards r t , and checks whether the termination state is reached and sets the done flag.

[0080] 3.4 Model update: Add new experience samples to the experience replay buffer, and use the samples in the experience replay buffer to update the Actor and Critic networks.

[0081] 3.5 Iteration: Repeat the above process until the algorithm converges or reaches the predetermined number of training rounds.

[0082] Regarding the specific training process of DDPG, Figure 5 As shown, Figure 5 The training process of the DDPG algorithm is shown, where the training curve shows that during the training process, due to the relatively small fluctuation range of the internal pressure of the pipeline, more training iterations are required to achieve more detailed control of the scheduling process. The subscript "mean" in the figure represents the average value of the reward every five training rounds. After about 250 training rounds, the training curve began to stabilize, but the system's problems of excess and insufficient thermal energy and insufficient power supply have not been completely solved. There is still a certain degree of insufficient power generation, excess and insufficient thermal energy in the system. Therefore, in order to ensure that the problems of insufficient power, excess and insufficient thermal energy in the scheduling process are thoroughly solved, and to minimize the waste of wind energy and light energy, it is necessary to further increase the number of training rounds.

[0083] S300, sends the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction to the corresponding cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends, so as to control the cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to operate according to the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction.

[0084] Specifically, after optimizing and scheduling the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction, the user-side electric load is sent to the user-side power supply end, the user-side thermal load is sent to the user-side heating end, the boiler coal feed is sent to the boiler in the cogeneration unit, the turbine heating steam extraction is sent to the steam turbine unit in the cogeneration unit, the steam pipeline pressure is sent to the steam pipeline control valve in the cogeneration unit, the wind power generation is sent to the wind turbine unit, and the photovoltaic power generation is sent to the photovoltaic equipment, so as to control the user-side heating end and the user-side power supply end, the boiler, the steam turbine, the steam pipeline control valve, the wind turbine unit and the photovoltaic equipment to operate according to the above-mentioned corresponding optimal parameters, so as to minimize the thermal decoupling scheduling operation cost of the wind-solar coupled cogeneration unit.

[0085] Beneficial effects of the present invention: (1) Solve the problem of source-load uncertainty: By combining photovoltaic and wind power generation with cogeneration units, the volatility of photovoltaic and wind power generation can be effectively dealt with, and the system's adaptability to source-load uncertainty can be improved. In addition, the MDP-DDPG algorithm is used for real-time scheduling, which can dynamically adjust the unit operating parameters according to real-time data, quickly respond to source-load changes, and ensure stable system operation.

[0086] (2) Equipment-level optimization: Equipment-level optimization is carried out for cogeneration units, photovoltaic equipment, and wind turbines. Refined control is performed based on the characteristics of each device to improve equipment operating efficiency.

[0087] (3) Intelligent scheduling: It uses the advanced MDP-DDPG reinforcement learning algorithm for optimized scheduling, which can automatically learn and adapt to the system operating environment to achieve intelligent scheduling. It can also make adaptive adjustments based on real-time data and system operating status to ensure the real-time and effectiveness of the scheduling strategy.

[0088] Embodiment 2 Based on the same inventive concept, Figure 6 As shown, the embodiment of the present invention further provides a wind-solar coupled cogeneration unit optimization scheduling device 200, comprising: Function construction module 210, for taking the user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal supply and turbine heating extraction as inputs, and minimizing the operating cost of the wind-solar-coupled heat and power cogeneration unit as target output, constructing the objective function of the wind-solar-coupled heat and power cogeneration unit, and determining the constraint conditions of the objective function of the wind-solar-coupled heat and power cogeneration unit; The function solving module 220 is used to optimize and solve the objective function of the wind-solar coupled heat and power cogeneration unit by using the MDP-DDPG algorithm, and determine the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction that meet the constraint conditions of the objective function of the wind-solar coupled heat and power cogeneration unit; The scheduling operation module 230 is used to send the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction to the corresponding cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends, so as to control the cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to operate according to the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction.

[0089] It should be understood that the device corresponds to the above-mentioned embodiment of the method for optimizing the dispatch of a wind-solar coupled cogeneration unit, and can execute the various steps involved in the above-mentioned method embodiment. The specific functions of the device can be found in the description above. To avoid repetition, the detailed description is appropriately omitted here. The device includes at least one software function module that can be stored in a memory in the form of software or firmware or solidified in the operating system (OS) of the device.

[0090] Embodiment 3 Based on the same inventive concept, an embodiment of the present invention also provides an electronic device, including: a processor and a memory, the memory storing machine-readable instructions executable by the processor, and the machine-readable instructions, when executed by the processor, execute the above-mentioned wind-solar coupled cogeneration unit optimization scheduling method.

[0091] In a typical configuration, an electronic device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0092] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0093] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0094] Embodiment 4 Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium storing computer instructions. When the computer instructions are executed on a computer, the computer executes the above-mentioned wind-solar coupled cogeneration unit optimization scheduling method.

[0095] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0096] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0100] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part.

[0101] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0102] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for optimizing the dispatching of a wind-solar coupled cogeneration unit, characterized in that: The wind-solar coupled cogeneration unit comprises: a cogeneration unit, a photovoltaic device, a wind turbine generator set, a user-side heating terminal and a user-side power supply terminal. The method comprises: Taking the user-side electrical load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal supply and turbine heating steam extraction of the wind-solar coupled cogeneration unit as input, and the minimum operating cost of the wind-solar coupled cogeneration unit as the target output, the objective function of the wind-solar coupled cogeneration unit is constructed, and the constraints of the objective function of the wind-solar coupled cogeneration unit are determined; The MDP-DDPG algorithm is used to optimize and solve the objective function of the wind-solar coupled cogeneration unit, and determine the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed rate, and turbine heating steam extraction that meet the constraints of the objective function of the wind-solar coupled cogeneration unit; The optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction are sent to the corresponding cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to control the cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to operate according to the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction.

2. The method for optimizing the dispatching of wind-solar coupled cogeneration units according to claim 1 is characterized in that: The objective function of the wind-solar coupled cogeneration unit is: ;in, represents the minimum operating cost of the wind-solar coupled cogeneration unit, Indicates the preset coal purchase cost coefficient, represents the coal purchase cost, Indicates the preset heating network state cost coefficient, Indicates the change in internal pressure of the heat network pipeline. represents the preset excess power generation penalty coefficient, Indicates excess power. Indicates the preset power shortage penalty coefficient. Indicates the amount of electricity to be compensated. Indicates the penalty coefficient for excess pressure in the preset heat network pipeline. Indicates excess pressure in the heat network pipeline. Indicates the penalty coefficient for insufficient pressure in the preset heating network pipeline. Indicates insufficient pressure in the heating network pipeline.

3. The method for optimizing the dispatching of wind-solar coupled cogeneration units according to claim 2 is characterized in that: The cost of purchasing coal is determined in the following way: ;in, represents the coal purchase cost, represents the unit price of coal, Indicates the amount of coal fed to the boiler; The change in internal pressure of the heating network pipeline is determined by: ;in, Indicates the change in internal pressure of the heat network pipeline. Indicates the steam extraction capacity of the steam turbine for heating. Indicates the heat load on the user side; represents the steam constant, Indicates the steam temperature in the heating network pipeline. Indicates the molar mass of steam in the heating network pipeline, Indicates the volume of the heat network pipeline; Excess power is determined as follows: ;in, Indicates excess power. represents the power generation of the cogeneration unit, represents the photovoltaic power generation, represents the wind power generation, Indicates the user side electrical load; The amount of electricity to be compensated is determined by: ;in, Indicates the amount of electricity to be compensated; The excess pressure in the heating network pipeline is determined by: ;in, Indicates excess pressure in the heat network pipeline. Indicates the pressure in the heat network pipeline. Indicates the maximum pressure in the heat network pipeline; The insufficient pressure in the heating network pipeline is determined by: ;in, Indicates insufficient pressure in the heating network pipeline. Indicates the minimum pressure in the heating network pipeline.

4. The method for optimizing the dispatching of wind-solar coupled cogeneration units according to claim 3 is characterized in that: The boiler coal feed rate is determined by: ;in, Indicates the amount of coal fed to the boiler. Indicates total calories, Indicates the lower heating value of coal; The power generation of a combined heat and power unit is determined by: ;in, represents the power generation of the cogeneration unit, represents the power generation efficiency of the generator, represents the power generation of high-pressure steam turbine, represents the power generation of the medium-pressure steam turbine, Indicates the power generation of low-pressure steam turbine; Photovoltaic power generation is determined by: ;in, represents the photovoltaic power generation, represents the photovoltaic cell efficiency, represents the inverter efficiency, Represents the effective illumination area, Indicates the intensity of solar radiation; Wind power generation is determined as follows: ;in, represents the wind power generation, Indicates the real-time wind speed. Indicates the starting wind speed. Indicates the shutdown wind speed. Indicates the rated wind speed, Indicates the installed capacity of wind turbines.

5. The method for optimizing the dispatching of wind-solar coupled cogeneration units according to claim 4 is characterized in that: The power generation of the high-pressure steam turbine is determined by: ;in, represents the power generation of high-pressure steam turbine, represents the efficiency of the high-pressure steam turbine, represents the inlet steam flow rate of the high-pressure steam turbine, represents the enthalpy of the inlet steam of the high-pressure steam turbine, Indicates the enthalpy of the outlet steam of the high-pressure steam turbine; The power generation of the medium pressure steam turbine is determined by: ;in, represents the power generation of the medium-pressure steam turbine, represents the efficiency of the medium-pressure steam turbine, represents the enthalpy of the inlet steam of the medium-pressure turbine, Indicates the enthalpy of the first stage extraction steam of the medium pressure steam turbine, Indicates the enthalpy of the secondary extraction steam of the medium pressure turbine, Indicates the enthalpy value of the three-stage extraction steam of the medium-pressure steam turbine, represents the enthalpy of the outlet steam of the medium-pressure steam turbine, represents the inlet steam flow rate of the medium-pressure steam turbine, Indicates the flow rate of the first stage extraction steam of the medium pressure steam turbine. Indicates the flow rate of the second stage extraction steam of the medium pressure steam turbine, Indicates the flow rate of the third-stage extraction steam of the medium-pressure steam turbine; The power generation of the low-pressure steam turbine is determined by: ;in, represents the power generation of the low-pressure steam turbine, represents the efficiency of the low-pressure steam turbine, represents the enthalpy of the inlet steam of the low-pressure turbine, Indicates the enthalpy of the first stage extraction steam of the low pressure steam turbine, Indicates the enthalpy of the secondary extraction steam of the low-pressure steam turbine, Indicates the enthalpy value of the three-stage extraction steam of the low-pressure steam turbine, represents the enthalpy of the outlet steam of the low-pressure turbine, represents the inlet steam flow rate of the low-pressure turbine, Indicates the flow rate of the first stage extraction steam of the low pressure steam turbine, Indicates the flow rate of the second stage extraction steam of the low pressure steam turbine, Indicates the flow rate of the third-stage extraction steam of the low-pressure steam turbine.

6. The method for optimizing the dispatching of wind-solar coupled cogeneration units according to claim 2, characterized in that: The constraints of the objective function of the wind-solar coupled cogeneration unit include: safe operation constraints; The safe operation constraints are: ;in, Indicates the initial pressure in the heat network pipeline. Indicates the minimum pressure in the heat network pipeline. Indicates the maximum pressure in the heating network pipeline. Indicates the amount of coal fed to the boiler. Indicates the minimum value of boiler coal supply. Indicates the maximum amount of coal fed to the boiler. represents the heat load on the user side, Indicates the steam extraction capacity of the steam turbine for heating. Indicates the minimum value of steam extraction for heating of steam turbine. Indicates the maximum value of steam extraction for heating of steam turbine.

7. The method for optimizing the dispatching of wind-solar coupled cogeneration units according to claim 2, characterized in that: The constraints of the objective function of the wind-solar coupled cogeneration unit include: power balance constraints; The power balance constraints are: ;in, Indicates the user side electrical load, Indicates excess wind power generation. represents the power generation of the cogeneration unit, represents the photovoltaic power generation, represents the wind power generation, Indicates the difference between the steam extraction capacity of the steam turbine and the heat load on the user side. Indicates the steam extraction capacity of the steam turbine for heating. Indicates the heat load on the user side.

8. A wind-solar coupled heat and power cogeneration unit optimization scheduling device, characterized in that: include: A function construction module is used to take the user-side electrical load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating extraction as inputs of the wind-solar-coupled heat and power cogeneration unit, and the minimum operating cost of the wind-solar-coupled heat and power cogeneration unit as the target output, to construct the objective function of the wind-solar-coupled heat and power cogeneration unit, and to determine the constraint conditions of the objective function of the wind-solar-coupled heat and power cogeneration unit; The function solving module is used to optimize and solve the objective function of the wind-solar coupled cogeneration unit by using the MDP-DDPG algorithm, and determine the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and turbine heating steam extraction that meet the constraint conditions of the objective function of the wind-solar coupled cogeneration unit; The scheduling and operation module is used to send the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction to the corresponding cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends, so as to control the cogeneration units, photovoltaic equipment, wind turbines, user-side heating ends and user-side power supply ends to operate according to the optimal user-side electric load, user-side thermal load, wind power generation, photovoltaic power generation, steam pipeline pressure, boiler coal feed and steam turbine heating extraction.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the machine-readable instructions are executed by the processor, the method for optimizing the scheduling of a wind-solar coupled cogeneration unit according to any one of claims 1 to 7 is executed.

10. A computer-readable storage medium storing computer instructions, characterized in that: When the computer instructions are executed on a computer, the computer executes the method for optimizing the dispatching of a wind-solar coupled cogeneration unit according to any one of claims 1 to 7.

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