Sewage plant integrated energy system planning method, computer equipment and medium

Abstract

The invention provides a sewage plant integrated energy system planning method, computer equipment and a medium, and relates to the field of sewage plant integrated energy system modeling planning. The method comprises the steps of collecting original data of a to-be-calculated integrated energy system, constructing a maximum access capacity calculation model for determining the integrated energy system in the sewage plant, inputting the original data into the maximum access capacity calculation model, solving the model by adopting an NSGA-II algorithm to obtain a group of Pareto frontier solutions, and calculating the maximum access capacity of the integrated energy system in the sewage plant according to the Pareto frontier solutions. According to the method, alternative schemes are sequenced through a multi-criterion decision analysis method, the scheme with the highest sequence is selected as the final maximum access capacity scheme, a model calculation and optimization algorithm is combined, efficient planning of the energy system of the sewage plant is achieved, economic cost and energy self-sufficiency rate can be better balanced, planning is more reasonable, and the method is suitable for large-scale popularization and application. And the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of integrated energy system modeling and planning for sewage treatment plants, and in particular to an integrated energy system planning method, computer equipment and medium for sewage treatment plants. Background Art

[0002] The resource and energy use of sewage treatment plants is an inevitable trend in the development of the industry and an inevitable requirement for high-quality economic and social development. Traditional sewage treatment plants consume a large amount of energy, accounting for 1%-3% of the total energy consumption of the whole society, and the energy contained in sewage is 9-10 times the energy consumed by sewage treatment itself. However, the energy in sewage treatment plants is not effectively utilized.

[0003] On the other hand, there is a lot of idle land in the sewage treatment plant, which can be used to deploy a large number of photovoltaic and wind turbines. The sewage source heat pump and biogas gas turbine cogeneration can also provide a large amount of energy. Exploring the potential of sewage and developing renewable energy can greatly improve the energy self-sufficiency rate of the plant.

[0004] In addition, the sewage treatment plant integrated energy system, which features multi-energy complementarity and energy cascade utilization, has the advantages of greater flexibility and higher energy utilization efficiency, and will become the typical form of future energy systems; and the prediction, monitoring, and scheduling processes of multi-energy systems also need to rely on data centers as information-physical carriers. Therefore, it is necessary to analyze the maximum capacity of the sewage treatment plant integrated energy system. Summary of the invention

[0005] The main purpose of the present invention is to provide a sewage treatment plant integrated energy system planning method, computer equipment and medium to solve the current technical problem of how to reasonably plan the sewage treatment plant integrated energy system.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for planning a comprehensive energy system for a sewage treatment plant, comprising the following steps:

[0007] S1: Obtain the original data of the comprehensive energy system to be calculated, wherein the comprehensive energy system includes three subsystems: source, storage and load. The source subsystem includes city power, photovoltaic power generation, wind power generation, sewage source heat pump and biogas gas turbine cogeneration. The storage subsystem includes electrical energy storage, thermal energy storage and chemical energy storage. The load subsystem includes electric drive pumps, fans, other water purification electrical equipment, biogas blowers, sludge drying equipment, sludge anaerobic digestion equipment and energy consumption equipment in resource recovery process.

[0008] S2: Based on the economic input cost and energy self-sufficiency rate of the integrated energy system, a calculation model for the maximum access capacity of the integrated energy system in the sewage treatment plant is constructed;

[0009] S3: Input the original data into the maximum access capacity calculation model, use the NSGA-II algorithm to solve the maximum access capacity calculation model in S2, and obtain a set of Pareto frontier solutions. Use multi-criteria decision analysis to get the ranking of the alternative solutions for the maximum access capacity of the integrated energy system, and select the alternative with the highest ranking as the maximum access capacity solution for the integrated energy system in the sewage treatment plant.

[0010] In a preferred embodiment, the original data includes: time series data and economic input data related to power generated during daily operation of the source subsystem, economic input data of the storage subsystem, and power consumption time series data of the load subsystem.

[0011] In the preferred solution, the maximum access capacity calculation model in S2 includes two optimization objectives, namely, the lowest economic investment cost of the sewage treatment plant integrated energy system and the highest energy self-sufficiency rate of the sewage treatment plant, where:

[0012] The optimization objective function formula for the lowest economic investment cost of the sewage treatment plant is:

[0013]

[0014] In the formula, Cost represents the economic input of the comprehensive energy system, P i S (i=1, ..., 5) represents the power of the source subsystem, P represents the economic investment of adding or renovating the unit power of the source subsystem; j ES (j=1, ..., 3) represent the power of electrical energy storage, thermal energy storage and chemical energy storage respectively, They represent the economic investment of adding electric energy storage, thermal energy storage and chemical energy storage to build a comprehensive energy system for a sewage treatment plant;

[0015] The optimization objective function formula for the highest energy self-sufficiency rate of the sewage treatment plant is:

[0016]

[0017] In the formula, E sS represents the energy self-sufficiency rate of the sewage treatment plant, represents the power of the charge system, Indicates the power of the mains electricity used by the sewage treatment plant.

[0018] In the preferred solution, the constraint condition included in the maximum access capacity calculation model in S2 is: the sum of the power of the source subsystem is greater than the sum of the power of the load subsystem, and less than the sum of the power of the load subsystem and the power of the storage subsystem;

[0019] The constraint formula is:

[0020]

[0021] In the formula, It represents the sum of the power consumed by each device in the load subsystem. Represents the sum of the power of each device in the source subsystem, Represents the total power of each device in the storage subsystem.

[0022] In the preferred solution, the maximum access capacity calculation model of the integrated energy system in the sewage treatment plant in S2 is based on the storage and load boundary conditions of the integrated energy system in the sewage treatment plant to calculate the maximum access capacity of photovoltaic and wind turbines in the sewage treatment plant, and also includes energy consumption demand data and the maximum access capacity of photovoltaic and wind energy, where:

[0023] Based on the spatiotemporal variation characteristics of the load subsystem equipment, a time series-based comprehensive energy system energy consumption prediction model is established to predict the time series data of each device in the load subsystem and obtain the maximum energy consumption demand data of the sewage treatment plant.

[0024] A model for solving the maximum capacity of the integrated energy system is constructed, and the boundary conditions of the storage subsystem and load subsystem of the integrated energy system in the sewage treatment plant are solved to calculate the maximum access capacity of photovoltaic and wind energy in the sewage treatment plant.

[0025] The preferred solution also includes: constructing a maximum capacity solution model for the integrated energy system, using a dynamic programming model with time dynamic change characteristics according to the time series characteristics, clarifying the boundary conditions, and obtaining the optimal strategy, wherein the state transfer equation formula is:

[0026]

[0027] Among them, R t (s t ,x t ) is the decision x selected in the tth stage t The immediate benefit or utility obtained when t+1 According to the decision x t The next state to transition to.

[0028] A sewage treatment plant integrated energy system planning system, comprising:

[0029] The data acquisition module is used to acquire the original data of the integrated energy system to be calculated. The integrated energy system includes three subsystems: source, storage and load. The source subsystem includes city power, photovoltaic power generation, wind power generation, sewage source heat pump and biogas gas turbine cogeneration. The storage subsystem includes electrical energy storage, thermal energy storage and chemical energy storage. The load subsystem includes electric drive pumps, fans, other water purification electrical equipment, biogas blowers, sludge drying equipment, sludge anaerobic digestion equipment and energy consumption equipment in resource recovery process.

[0030] Model calculation module, used to construct the maximum access capacity calculation model of the integrated energy system in the sewage treatment plant based on the economic input cost and energy self-sufficiency rate of the integrated energy system;

[0031] The scheme planning module is used to input the original data into the maximum access capacity calculation model, use the NSGA-II algorithm to solve the maximum access capacity calculation model, obtain a set of Pareto frontier solutions, and use multi-criteria decision analysis to get the ranking of various alternative schemes for the maximum access capacity of the integrated energy system, and select the alternative with the highest ranking as the maximum access capacity scheme for the integrated energy system in the sewage treatment plant.

[0032] A computer device includes a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the steps of a sewage treatment plant integrated energy system planning method by executing the computer instructions.

[0033] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for planning a comprehensive energy system for a sewage treatment plant is implemented.

[0034] The present invention provides a method, computer equipment and medium for planning an integrated energy system of a sewage treatment plant. First, the original data of the integrated energy system to be calculated is collected, and then a maximum access capacity calculation model for determining the integrated energy system in the sewage treatment plant is constructed. The original data is input into the maximum access capacity calculation model, and the NSGA-II algorithm is used to solve the model to obtain a set of Pareto frontier solutions. The alternative solutions are ranked by a multi-criteria decision analysis method, and the highest ranked solution is selected as the final maximum access capacity solution. The model calculation and optimization algorithm are combined to achieve efficient planning and management of the energy system of the sewage treatment plant. The NSGA-II algorithm performs well in multi-objective optimization and can provide multiple optimization solutions to find a balance between economic cost and energy self-sufficiency rate, make planning more reasonable, and improve energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0036] Figure 1 is a flow chart of the integrated energy system planning method of the present invention;

[0037] Figure 2 It is a system diagram of the integrated energy system planning of the present invention;

[0038] Figure 3 It is the principle diagram of NSGA-II algorithm of the present invention;

[0039] Figure 4It is a specific flow chart of the objective function obtained by NSGA-II of the present invention based on Pareto;

[0040] Figure 5 It is a schematic diagram of the process of accessing the SEABODE method of the present invention. DETAILED DESCRIPTION

[0041] Example 1

[0042] like Figure 1-5 As shown, a method for planning a comprehensive energy system for a sewage treatment plant comprises the following steps:

[0043] S1: Obtain the original data of the integrated energy system to be calculated, specifically including the data of the three subsystems of the integrated energy system, namely source, storage and load. The source subsystem includes city power, photovoltaic power generation, wind power generation, sewage source heat pump and biogas gas turbine cogeneration. The storage subsystem includes electrical energy storage, thermal energy storage and chemical energy storage. The load subsystem includes electric drive pumps, other water purification electrical equipment, biogas blowers, sludge drying equipment, sludge anaerobic digestion equipment and energy consumption equipment in the resource recovery process. The original data of the integrated energy system includes the installed capacity of each part of the source subsystem and the storage subsystem, and the power of each energy consumption equipment in the load subsystem.

[0044] S2: Based on the economic input cost and energy self-sufficiency rate of the integrated energy system, a calculation model for the maximum access capacity of the integrated energy system in the sewage treatment plant is constructed.

[0045] S3: Input the original data into the maximum access capacity calculation model, use the NSGA-II (Non-dominated Sorting Genetic Algorithm II) algorithm to solve the maximum access capacity calculation model in S2, and obtain a set of Pareto frontier solutions. Use multi-criteria decision analysis to get the ranking of various alternative schemes for the maximum access capacity of the integrated energy system, and select the alternative with the highest ranking as the maximum access capacity solution for the integrated energy system in the sewage treatment plant.

[0046] As shown in Tables 1 to 3, these are some of the data used in this embodiment, and each calculation model is constructed based on the data in the table. This embodiment first collects the original data of the integrated energy system to be calculated, and then constructs a calculation model for determining the maximum access capacity of the integrated energy system in the sewage treatment plant. The original data is input into the maximum access capacity calculation model, and the NSGA-II algorithm is used to solve the model to obtain a set of Pareto frontier solutions. The alternative solutions are ranked by a multi-criteria decision analysis method, and the highest ranked solution is selected as the final maximum access capacity solution. The model calculation and optimization algorithm are combined to achieve efficient planning and management of the sewage treatment plant energy system. The NSGA-II algorithm performs well in multi-objective optimization and can provide multiple optimization solutions to find a balance between economic costs and energy self-sufficiency, make planning more reasonable, and improve energy efficiency.

[0047] Table 1 Data table of source subsystems of comprehensive energy system in sewage treatment plant

[0048] Source Subsystem Average operating power Run time Economic investment Mains electricity 200kW 24h Electricity price: 0.7 yuan / kWh Photovoltaic power generation 200kW 8h Investment cost 4 yuan / W Wind power 20kW 8h Investment cost: 8.9 yuan / W Sewage source heat pump 50kW 10h Investment cost: 4.4 yuan / W Biogas gas turbine 150kW 24h Investment cost 15 yuan / W

[0049] Table 2 Data table of load subsystem in comprehensive energy system of sewage treatment plant

[0050] Charge System Actual operating power of a single unit Actual daily power consumption Electric lift pump 15kW 360kWh Screw conveyor compactor 1.1kW 13.2kWh Flushing pump 7.5kW 180kWh Filtrate reflux pump 8.8kW 70.4kWh Feed agitator 7.5kW 60kWh High temperature anaerobic digestion equipment 16.4kW 393.6kWh Air suspension blower 64kW 640kWh Sludge drying equipment 20kW 200kWh

[0051] Table 3 Data table of storage subsystem of comprehensive energy system in sewage treatment plant

[0052] Storage subsystem Actual operating power Economic investment Lithium iron phosphate battery 200kW Investment cost is about 1.7 yuan / kWh

[0053] like Figure 3 This is the NSGA-II algorithm flow. Figure 4 The NSGA-II algorithm is an evolutionary multi-objective algorithm based on the concept of Pareto dominance, which solves the multi-objective optimization function of the maximum access capacity of the integrated energy system of the above-mentioned sewage treatment plant. The specific process of obtaining the non-inferior solution set of the objective function is shown in the figure, and the main steps are as follows:

[0054] Step 1: Randomly generate the initial population P0 (population size N), the number of iterations g = 0, and the capacity plan of the integrated energy system in the sewage plant for individual j is H j express.

[0055] Step 2: For each individual H in the parent population P0 j According to the above-mentioned objective function of setting the lowest cost and the highest energy self-sufficiency rate of the sewage treatment plant, the corresponding objective function value CT is obtained. j and ES j .

[0056] Step 3: sort the parent population P0 into non-dominated groups (Z1, Z2, ...), and assign a non-dominated layer number (rank = 1, 2, ...) to each individual.

[0057] Step 4: For the parent population P g Perform selection, crossover and mutation operations to generate the offspring population S g .

[0058] Step 5: Evaluate the offspring population S according to step 2 g The objective function value of each individual in .

[0059] Step 6: Form a merged population M g , M g =P g ∪S g (Population size 2N).

[0060] Step 7: Perform fast non-dominated sorting on the merged population Mg to identify the non-dominated layers Z1, Z2, ..., Z n .

[0061] Step 8: Calculate the crowding degree of each non-dominated layer individual.

[0062] Step 9: Use the crowding comparison operator to generate a new offspring population Pg+1 for the merged population Mg.

[0063] Step 10: Set g = g + 1, return to step 4, and repeat steps 4-9 until the maximum number of iterations (g = maxgen) is reached.

[0064] By solving the model in the above steps, we can obtain a set of non-inferior solutions for the maximum capacity access of the sewage treatment plant integrated energy system H = {H1, H2, ..., H N}.

[0065] Furthermore, if Figure 5 As shown in the figure, it is the capacity access scheme of the integrated energy system of the sewage treatment plant---SEABODE scheme, which can be better sorted, specifically:

[0066] (1) Collection and organization of model inputs, including power consumption data of the electric drive pumps, fans, and other electrical equipment for water purification in the integrated energy system of the sewage treatment plant.

[0067] (2) Establishment and solution of multi-objective optimization model. The NSGA-II algorithm is used to solve the maximum capacity access model of the integrated energy system of the sewage treatment plant, obtain a set of non-inferior solutions, and generate a decision space H = {H1, H2, ..., H N}.

[0068] (3) Multi-attribute solution decision-making: Establish an evaluation index system to construct the attribute space C, use the SEABODE method to evaluate and eliminate each alternative solution, and select the final preferred solution.

[0069] The two evaluation criteria in this embodiment are: the economic input cost of the sewage treatment plant and the energy self-sufficiency rate of the sewage treatment plant; the weights are determined by pairwise comparison, and then a comprehensive score is given, and the ranking is based on the score, with the higher the score, the higher the ranking.

[0070] In a preferred embodiment, the original data includes: time series data and economic input data related to power generated during daily operation of the source subsystem, economic input data of the storage subsystem, and power consumption time series data of the load subsystem.

[0071] In the preferred scheme, the maximum access capacity calculation model in S2 contains two optimization objectives, namely, the lowest economic investment cost of the sewage treatment plant integrated energy system and the highest energy self-sufficiency rate of the sewage treatment plant, among which:

[0072] The optimization objective function formula for the lowest economic investment cost of the sewage treatment plant is:

[0073]

[0074] In the formula, Cost represents the economic input of the comprehensive energy system, P i S (i=1, ..., 5) represents the power of the source subsystem, P represents the economic investment of adding or renovating the unit power of the source subsystem; j ES (j=1, ..., 3) represent the power of electrical energy storage, thermal energy storage and chemical energy storage respectively, They respectively represent the economic investment of additional electrical energy storage, thermal energy storage and chemical energy storage in order to build a comprehensive energy system for a sewage treatment plant;.

[0075] The optimization objective function formula for the highest energy self-sufficiency rate of the sewage treatment plant is:

[0076]

[0077] In the formula, E SS represents the energy self-sufficiency rate of the sewage treatment plant, represents the power of the charge system, Indicates the power of the mains electricity used by the sewage treatment plant.

[0078] In the preferred solution, the constraint condition included in the maximum access capacity calculation model in S2 is that the sum of the power of the source subsystem is greater than the sum of the power of the load subsystem, and less than the sum of the power of the load subsystem and the power of the storage subsystem.

[0079] The constraint formula is:

[0080]

[0081] In the formula, It represents the sum of the power consumed by each device in the load subsystem. Represents the sum of the power of each device in the source subsystem, Represents the total power of each device in the storage subsystem.

[0082] The objective function can optimize the economic input cost of the integrated energy system of the sewage treatment plant and maximize its energy self-sufficiency rate, thereby realizing efficient planning and management of the integrated energy system; the constraints ensure that the power of the source subsystem will not exceed the sum of the power of the storage subsystem and the load subsystem while meeting the needs of the load subsystem, thereby ensuring the stability and economy of the system.

[0083] The preferred solution also includes: in step S2, the maximum access capacity calculation model of the integrated energy system in the sewage treatment plant is solved based on the storage and load boundary conditions of the integrated energy system in the sewage treatment plant to calculate the maximum access capacity of photovoltaic and wind turbines in the sewage treatment plant, and also includes energy consumption demand data and the maximum access capacity of photovoltaic and wind energy, wherein:

[0084] Based on the spatiotemporal variation characteristics of the load subsystem equipment, a time series-based energy consumption prediction model for the comprehensive energy system is established. The time series data of the consumption of each equipment in the load subsystem is predicted separately, and the maximum energy consumption demand data of the sewage treatment plant is obtained.

[0085] A model for solving the maximum capacity of the integrated energy system is constructed, and the boundary conditions of the storage subsystem and load subsystem of the integrated energy system in the sewage treatment plant are solved to calculate the maximum access capacity of photovoltaic and wind energy in the sewage treatment plant.

[0086] In this embodiment, the original data includes historical data of electric drive pumps, blowers, other electrical equipment for water purification, biogas blowers, sludge drying equipment, sludge anaerobic digestion equipment and energy consumption equipment in resource recovery process.

[0087] There are many methods and techniques that can be used to build a model to solve the maximum capacity of an integrated energy system. The appropriate method should be selected based on the complexity of the specific problem, the required accuracy, and the type of available data.

[0088] The preferred solution also includes: constructing a maximum capacity solution model for the integrated energy system, using a dynamic programming model with time dynamic change characteristics according to the time series characteristics, clarifying the boundary conditions, and obtaining the optimal strategy, wherein the state transfer equation formula is:

[0089]

[0090] Among them, R t (s t ,x t ) is the decision x selected in the tth stage t The immediate benefit or utility obtained when t+1 According to the decision x t The next state to transition to.

[0091] Furthermore, the maximum capacity solution model of the integrated energy system can also be constructed by using a linear programming model, an integer programming model, an optimization method based on a heuristic algorithm, or a multi-objective optimization method to solve the maximum capacity of the energy system according to the specific requirements and constraints of the actual problem.

[0092] In this embodiment, the process of the integrated energy system planning method is further refined. After obtaining the original data, energy consumption forecasting is performed. Based on the spatiotemporal variation characteristics of the load subsystem equipment, an energy consumption forecasting model is established to predict the energy consumption time series data of each device in the load subsystem to obtain the maximum energy consumption demand data of the sewage treatment plant.

[0093] Among them, the boundary conditions of the storage subsystem and the load subsystem are used to construct a maximum capacity solution model for the integrated energy system. The maximum access capacity of photovoltaic and wind energy is calculated based on the boundary conditions of the storage subsystem and the load subsystem.

[0094] The integration of time series forecasting and boundary condition analysis enables comprehensive evaluation and optimization of the design and operation of the integrated energy system of the sewage treatment plant. Through these steps, energy consumption can be effectively managed, energy access capacity can be optimized, and the economy and reliability of the system can be improved.

[0095] Example 2

[0096] In combination with Example 1, a sewage treatment plant integrated energy system planning system is provided, including:

[0097] The data acquisition module 101 is used to obtain the original data of the integrated energy system to be calculated. The integrated energy system includes three subsystems: source, storage and load. The source subsystem includes city power, photovoltaic power generation, wind power generation, sewage source heat pump and biogas gas turbine cogeneration. The storage subsystem includes electrical energy storage, thermal energy storage and chemical energy storage. The load subsystem includes electric drive pumps, fans, other water purification electrical equipment, biogas blowers, sludge drying equipment, sludge anaerobic digestion equipment and resource recovery process energy consumption equipment.

[0098] The model calculation module 102 is used to construct a maximum access capacity calculation model of the integrated energy system in the sewage treatment plant based on the economic input cost and energy self-sufficiency rate of the integrated energy system.

[0099] The scheme planning module 103 is used to input the original data into the maximum access capacity calculation model, use the NSGA-II algorithm to solve the maximum access capacity calculation model, obtain a set of Pareto frontier solutions, use multi-criteria decision analysis to get the ranking of various alternative schemes for the maximum access capacity of the integrated energy system, and select the alternative with the highest ranking as the maximum access capacity scheme for the integrated energy system in the sewage treatment plant.

[0100] A computer device includes a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the steps of the method in Example 1 by executing the computer instructions.

[0101] A computer-readable storage medium includes: a computer program stored on the computer-readable storage medium, and the computer program implements the method in embodiment 1 when executed by a processor.

[0102] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A method for planning an integrated energy system for a sewage treatment plant, characterized in that: The following steps are involved: S1: Obtain the original data of the comprehensive energy system to be calculated, wherein the comprehensive energy system includes three subsystems: source, storage and load. The source subsystem includes city power, photovoltaic power generation, wind power generation, sewage source heat pump and biogas gas turbine cogeneration. The storage subsystem includes electrical energy storage, thermal energy storage and chemical energy storage. The load subsystem includes electric drive pumps, fans, other water purification electrical equipment, biogas blowers, sludge drying equipment, sludge anaerobic digestion equipment and energy consumption equipment in resource recovery process. S2: Based on the economic input cost and energy self-sufficiency rate of the integrated energy system, a calculation model for the maximum access capacity of the integrated energy system in the sewage treatment plant is constructed; S3: Input the original data into the maximum access capacity calculation model, use the NSGA-II algorithm to solve the maximum access capacity calculation model in S2, and obtain a set of Pareto frontier solutions. Use multi-criteria decision analysis to get the ranking of the alternative solutions for the maximum access capacity of the integrated energy system, and select the alternative with the highest ranking as the maximum access capacity solution for the integrated energy system in the sewage treatment plant.

2. The method for planning a comprehensive energy system for a sewage treatment plant according to claim 1, characterized in that: The original data include: time series data and economic input data related to power generated by the daily operation of the source subsystem, economic input data of the storage subsystem and power consumption time series data of the load subsystem.

3. The method for planning a comprehensive energy system for a sewage treatment plant according to claim 1, characterized in that: The maximum access capacity calculation model in S2 includes two optimization objectives, namely, the lowest economic input cost of the sewage treatment plant integrated energy system and the highest energy self-sufficiency rate of the sewage treatment plant, among which: The optimization objective function formula for the lowest economic investment cost of the sewage treatment plant is: In the formula, Cost represents the economic input of the integrated energy system, represents the power of the source subsystem, It represents the economic investment of adding or renovating the unit power of the source subsystem; (j=1, ..., 3) represent the power of electrical energy storage, thermal energy storage and chemical energy storage respectively, They represent the economic investment of adding electric energy storage, thermal energy storage and chemical energy storage to build a comprehensive energy system for a sewage treatment plant; The optimization objective function formula for the highest energy self-sufficiency rate of the sewage treatment plant is: In the formula, E SS represents the energy self-sufficiency rate of the sewage treatment plant, represents the power of the charge system, Indicates the power of the mains electricity used by the sewage treatment plant.

4. According to claim 3, a sewage treatment plant integrated energy system planning method, computer equipment and medium, characterized in that: The constraint conditions included in the maximum access capacity calculation model in S2 are: the sum of the power of the source subsystem is greater than the sum of the power of the load subsystem, and less than the sum of the power of the load subsystem and the power of the storage subsystem; The constraint formula is: In the formula, It represents the sum of the power consumed by each device in the load subsystem. Represents the sum of the power of each device in the source subsystem, Represents the sum of the power of each device in the storage subsystem.

5. According to claim 1, a sewage treatment plant integrated energy system planning method, computer equipment and medium, characterized in that: The maximum access capacity calculation model of the integrated energy system in the sewage treatment plant in S2 is based on the storage and load boundary conditions of the integrated energy system in the sewage treatment plant, and calculates the maximum access capacity of photovoltaic and wind turbines in the sewage treatment plant, and also includes energy consumption demand data and the maximum access capacity of photovoltaic and wind energy, where: Based on the spatiotemporal variation characteristics of the load subsystem equipment, a time series-based comprehensive energy system energy consumption prediction model is established to predict the time series data of each device in the load subsystem and obtain the maximum energy consumption demand data of the sewage treatment plant. A model for solving the maximum capacity of the integrated energy system is constructed, and the boundary conditions of the storage subsystem and load subsystem of the integrated energy system in the sewage treatment plant are solved to calculate the maximum access capacity of photovoltaic and wind energy in the sewage treatment plant.

6. A sewage treatment plant integrated energy system planning method, computer equipment and medium according to claim 5, characterized in that: Also includes: The maximum capacity solution model of the integrated energy system is constructed according to the time series characteristics, using a dynamic programming model with time dynamic change characteristics, clarifying the boundary conditions and obtaining the optimal strategy, wherein the state transfer equation formula is: Among them, R t (s t ,x t ) is the decision x selected in the tth stage t The immediate benefit or utility obtained when t+1 According to the decision x t The next state to transition to.

7. A sewage treatment plant integrated energy system planning system, characterized in that: include: The data acquisition module is used to acquire the original data of the integrated energy system to be calculated. The integrated energy system includes three subsystems: source, storage and load. The source subsystem includes city power, photovoltaic power generation, wind power generation, sewage source heat pump and biogas gas turbine cogeneration. The storage subsystem includes electrical energy storage, thermal energy storage and chemical energy storage. The load subsystem includes electric drive pumps, fans, other water purification electrical equipment, biogas blowers, sludge drying equipment, sludge anaerobic digestion equipment and energy consumption equipment in resource recovery process. Model calculation module, used to construct the maximum access capacity calculation model of the integrated energy system in the sewage treatment plant based on the economic input cost and energy self-sufficiency rate of the integrated energy system; The scheme planning module is used to input the original data into the maximum access capacity calculation model, use the NSGA-II algorithm to solve the maximum access capacity calculation model, obtain a set of Pareto frontier solutions, and use multi-criteria decision analysis to get the ranking of various alternative schemes for the maximum access capacity of the integrated energy system, and select the alternative with the highest ranking as the maximum access capacity scheme for the integrated energy system in the sewage treatment plant.

8. A computer device, comprising a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the steps of a sewage treatment plant integrated energy system planning method as described in any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: include: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements a method for planning a comprehensive energy system for a sewage treatment plant as described in any one of claims 1 to 6.

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