An optimized operation system, optimization method and medium for distributed integrated energy.

Abstract

This invention relates to the field of renewable energy technology, and discloses an optimized operation system, optimization method, and medium for distributed integrated energy, including a heat network model and an equipment operation model. The heat network model accurately describes the flow balance, energy conservation, and especially the heat transfer characteristics of the heat network pipelines to fully utilize the energy storage capacity of the heating network for economically optimized scheduling. Simultaneously, an optimization solution method based on this model is proposed. By constructing a hydrogen-electric coupling sub-model and a heating sub-model, the operation strategies of hydrogen energy equipment and heating equipment are processed hierarchically, thereby reducing the solution complexity. The solution method prioritizes the coupling of hydrogen energy equipment and electrical equipment to achieve efficient absorption of renewable energy sources such as photovoltaics, and dynamically adjusts the temperature and flow rate of the pipeline heat medium within the system. This effectively improves the adaptability and flexibility of the integrated energy system and optimizes system operation.

Description

Technical Field

[0001] This invention belongs to the field of renewable energy technology and relates to an optimized operation system, optimization method and medium for distributed integrated energy. Background Technology

[0002] With the escalating global energy crisis and environmental pollution, distributed integrated energy systems have gained attention due to their high energy efficiency and environmental friendliness. In a distributed integrated energy system comprised of multiple integrated energy stations, these stations are interconnected through power grids and heating networks to achieve mutual coordination. Unlike power grids, district heating networks, as the medium for heat energy transmission, exhibit higher transmission losses and delays. This characteristic presents challenges for modeling the heating network in distributed integrated energy systems, but it also indicates that the heating network possesses a certain energy storage capacity. Therefore, a distributed integrated energy system heating network model is needed to accurately and dynamically describe the heating network, thereby leveraging the regulatory potential of heating network energy storage to participate in the economic optimization of the distributed integrated energy system.

[0003] Furthermore, hydrogen energy, as a clean energy source, is widely used in distributed integrated energy systems. Hydrogen energy, like electricity, belongs to secondary energy sources. In hydrogen-containing integrated energy systems, surplus renewable energy sources such as wind and solar power can be converted into hydrogen energy through electrolysis and stored. During peak energy demand periods, hydrogen energy is then converted into electricity and heat energy through hydrogen fuel cells. Hydrogen energy is not only related to electricity and heat energy but also coupled with renewable energy sources, natural gas, and the power grid. Considering the volatility, complementarity, and real-time demand of different energy sources, efficiently coordinating the flow of hydrogen energy with electricity and heat energy within a system is a significant challenge. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides an optimized operation system, optimization method, and medium for distributed integrated energy, which can accurately describe the dynamic changes in heating pipelines, leverage the regulatory potential of heating network energy storage in the operation optimization of distributed integrated energy systems, and achieve efficient coordination of the flow of hydrogen energy, electricity, and heat energy within a single system.

[0005] This invention is achieved through the following technical solution:

[0006] A method for establishing an optimized operation system for distributed integrated energy, comprising:

[0007] Based on the internal operating structure of the distributed integrated energy system, and according to the operating mechanism of each internal device, an internal device operation model is established to obtain the internal device operation constraints.

[0008] A heat network model is established based on the heat loss of the heat medium in the heating pipeline to determine the heat transfer characteristics of the pipeline and obtain the operating constraints of the heat network.

[0009] Based on the relationship between energy supply and consumption in a distributed integrated energy system, energy and thermal balance constraints are obtained;

[0010] An energy optimization model is established based on internal equipment operation constraints, heating network operation constraints, and energy and heat balance constraints; the energy optimization model includes a hydrogen-electric coupling sub-model and a heating sub-model.

[0011] Based on the internal equipment operation model, the heating network model, and the energy optimization model, a distributed integrated energy system operation model is obtained by combining them.

[0012] Preferably, the internal equipment operating constraints include: operating constraints of photovoltaic panels, operating constraints of electric chillers, operating constraints of electric boilers, operating constraints of heat pumps, operating constraints of electrolyzers, operating constraints of fuel cells, operating constraints of energy storage units, operating constraints of hydrogen storage tanks, and operating constraints of energy storage water tanks.

[0013] Preferably, the operating constraints of the heating network include node flow balance constraints, node energy conservation constraints, pipeline water supply and return temperature constraints, and pipeline heat transfer characteristic constraints.

[0014] Preferably, the hydrogen-electric coupling sub-model is established through constraints of the heat network model, internal equipment operation constraints, energy balance constraints, and heat constraints at the heat source end and the load end; the energy balance constraints include electrical balance constraints and cold and heat balance constraints.

[0015] Preferably, the objective function of the hydrogen-electricity coupling sub-model is a function that minimizes the costs of purchasing electricity and hydrogen, specifically as follows:

[0016]

[0017] in, For the number of energy stations, and These are the th terms within the desired optimization period. The cost of purchasing electricity and hydrogen for each energy station.

[0018] Preferably, the heating sub-model is established through heating network operation constraints, internal equipment operation constraints including heating and cooling related equipment operation constraints, heat and cold balance constraints, and heat source and load end heat constraints;

[0019] The operating constraints of the heating and cooling related equipment include operating constraints of electric boilers, electric chillers, heat pumps, water tanks, and fuel cells.

[0020] Preferably, the objective function of the heating sub-model is the function that minimizes the electricity purchase cost, and the specific formula is as follows:

[0021]

[0022] in, For the number of energy stations, For the desired operation optimization period, the first The cost of purchasing electricity for each energy station.

[0023] Preferably, the internal operating structure is an energy transmission system that connects the energy station, the energy storage tank, and the user area through a heating pipeline network.

[0024] An optimized operation system for distributed integrated energy is obtained based on the method for establishing the operation model of the distributed integrated energy system.

[0025] An optimization solution method for a distributed integrated energy system, comprising:

[0026] Solve the hydrogen-electric coupling sub-model to obtain the operation strategy and cost of the distributed integrated energy system. Transfer the operation strategy of the hydrogen energy equipment and the temperature of the heating pipeline to the heating sub-model as initial conditions.

[0027] Solve the heating sub-model, update the pipeline flow rate using the obtained heating flow rate, and then feed the updated pipeline flow rate back to the hydrogen-electric coupling sub-model. Iterate through solving the hydrogen-electric coupling model until the optimal operating strategy and operating cost are obtained. Specifically:

[0028] Determine whether the ratio of the difference between the current operating cost of the distributed integrated energy system and the operating cost obtained in the previous iteration to the current operating cost is less than a preset threshold.

[0029] If the value is less than the preset threshold, the iteration stops, and the current operating strategy of the distributed integrated energy system is taken as the economically optimal operating strategy, and the strategy is used to control the operation of the distributed integrated energy system.

[0030] If the value is not less than the preset threshold, the current operating strategy of the hydrogen energy equipment is passed to the heating sub-model as the initial condition, and the iteration continues until the economically optimal operating strategy is obtained.

[0031] An optimization solution system for an optimized operation system of a distributed integrated energy system is obtained based on the aforementioned optimization solution method for an optimized operation system of a distributed integrated energy system.

[0032] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the optimization solution method for an optimized operation system of a distributed integrated energy system.

[0033] Compared with the prior art, the present invention has the following beneficial technical effects:

[0034] This invention constructs a distributed integrated energy system operation model. The heat network model within this model considers the transient characteristics of the heat medium temperature, accurately describing the temperature changes of the heat medium in the heating pipelines. It also proposes a method to determine the transient and steady-state heat transfer characteristics of the pipelines based on the scheduling cycle, pipeline length, inner diameter, and flow rate. This establishes a dynamic model of the distributed integrated energy system's heating network, reducing the impact of heat loss and heat transfer delay in the heating pipelines on the operation and scheduling of the distributed integrated energy system. Furthermore, it leverages the potential energy storage capacity of the heating network to optimize the operation of the distributed integrated energy system, achieving efficient coordination of the flow of hydrogen, electricity, and heat within a single system.

[0035] Furthermore, this invention proposes a method for optimizing the operation of a distributed integrated energy system, prioritizing hydrogen-electric coupling and solving the operational strategies of hydrogen-related equipment within the hydrogen-electric coupling sub-model. This reduces the complexity of the model solution while fully leveraging hydrogen's ability to absorb renewable energy sources such as photovoltaics, enhancing the adaptability and flexibility of the integrated energy system. In addition, in solving the operation of heating pipe networks, compared to traditional constant-temperature variable-flow and constant-flow variable-temperature schemes, this method simultaneously considers and adjusts the flow rate and temperature of the pipeline heat medium, providing a more accurate description of the heating pipe network. Solving for the pipeline heat medium temperature and flow rate separately in the hydrogen-electric coupling sub-model and the heating sub-model ensures feasibility and optimality while avoiding the difficulties caused by nonlinear constraints on temperature and flow rates. Attached Figure Description

[0036] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of the structure of the distributed integrated energy system provided in an embodiment of the present invention.

[0038] Figure 2 This is a schematic diagram of the internal structure of an energy station in a distributed integrated energy system provided in an embodiment of the present invention.

[0039] Figure 3 This is a schematic diagram of the basic structure of the heating pipeline model provided in the embodiment of the present invention.

[0040] Figure 4 This is a flowchart illustrating the method for optimizing the operation of a distributed integrated energy system provided in an embodiment of the present invention.

[0041] Figure 5 This is a flowchart of the distributed integrated energy system model establishment and operation optimization solution method described in this invention. Detailed Implementation

[0042] The present invention will be further described in detail below with reference to specific embodiments. These descriptions are for explanation purposes only and are not intended to limit the scope of the invention.

[0043] In a first aspect, the present invention provides a distributed integrated energy system model, which includes a heating network model and an equipment operation model; wherein...

[0044] The constraints of the heating network model include nodal flow balance, nodal energy conservation, pipeline supply and return water temperature constraints, and pipeline heat transfer characteristics; among which,

[0045] The node flow balance constraint is used to describe that the water flow into a node at any given time is equal to the water flow out of that node in the heating network pipeline.

[0046] The node energy conservation constraint is used to describe that the heat entering a node at any given moment in a heating network pipeline is equal to the heat flowing out of that node.

[0047] The pipeline heat transfer characteristic constraint takes into account the transient temperature change of the heat medium in the heating network. The pipeline transmission delay is calculated using pipeline length, pipeline inner diameter, flow rate, etc. The pipeline transmission delay is compared with the time scale of system operation scheduling to determine the steady-state and transient heat transfer characteristics of the pipeline.

[0048] Optionally, the constraints in the equipment operation model include operational constraints for power generation equipment such as photovoltaic panels, operational constraints for heat and cold generation equipment such as air source heat pumps, sewage source heat pumps, ground source heat pumps, electric chillers, and electric boilers, operational constraints for hydrogen energy equipment such as electrolyzers and fuel cells, and operational constraints for energy storage equipment such as hydrogen storage tanks, energy storage units, and energy storage water pipes. Among these, the energy storage water tank, as a heat (cold) storage device, is placed independently outside the heat source end of the system, and its input and output heat is not included in the heat (cold) generation at the heat source end.

[0049] The energy balance constraints include electrical balance constraints, thermal balance constraints, and cold balance constraints.

[0050] The heat source and load end heat constraints describe the relationship between the heat entering and leaving each heat source and load end and the water flow rate and temperature flowing into and out of the heat source or load.

[0051] Secondly, based on the operation model of the distributed integrated energy system, an energy optimization model for the distributed integrated energy system is established, which includes a hydrogen-electric coupling sub-model and a heating sub-model.

[0052] The hydrogen-electric coupling sub-model, through constraints such as the heat network model, equipment operation constraints, energy balance constraints, and heat constraints at the heat source and load ends, ensures that the system operating cost is minimized while meeting user load demands. Its objective function is to minimize the cost of purchasing electricity and hydrogen.

[0053] The energy balance constraints ensure the conservation of energy supply between the system and user demand, including electrical balance constraints and thermal balance constraints; wherein...

[0054] The power balance constraint comprehensively considers the power consumption of photovoltaic power generation, fuel cell power generation, energy storage unit discharge and charging, electrolytic cell power consumption, and power consumption of equipment such as electric boilers, heat pumps, and electric chillers, in order to meet the user's power load requirements;

[0055] The aforementioned heat and cold balance constraint ensures that the user's heat and cold load requirements are met based on the heat and cold output of equipment such as fuel cells, heat pumps, and electric boilers, as well as the heat and cold output of energy storage tanks.

[0056] The heat source end heat constraint further describes the relationship between the total output heat of the energy station and the heat generated by the equipment, as well as the relationship between the output heat and the inlet and outlet water temperature and flow rate, to ensure that the system operation matches the user load demand.

[0057] The heating sub-model includes constraints on the heating network model, operational constraints on heating and cooling related equipment, heat and cold balance constraints, and heat constraints at the heat source and load ends. Its objective function is to minimize the cost of electricity purchase. The constraints in the model include operational constraints on equipment such as electric boilers, electric chillers, heat pumps, water tanks, and fuel cells, as well as the energy balance relationship in the system's heating and cooling process, to meet the user's electrical load, heat load, and cooling load requirements.

[0058] Thirdly, this invention provides a method for optimizing the operation of a distributed integrated energy system, based on the proposed energy optimization model, to determine the economically optimal operating strategy for the system. The method includes:

[0059] Based on the aforementioned solution method, the hydrogen-electric coupling sub-model and the heating sub-model are iteratively solved; in each round of iterative solution:

[0060] Based on the existing pipeline flow rate, the hydrogen-electric coupling sub-model is solved. The operating strategy and operating cost from the solution are saved, and the operating strategy of the hydrogen energy equipment and the temperature of each heating pipeline are transferred to the heating sub-model as initial conditions. The heating sub-model is then solved again to solve and update the pipeline flow rate. The updated pipeline flow rate is then transferred to the hydrogen-electric coupling sub-model, and the hydrogen-electric coupling model is solved again to obtain a new operating strategy and operating cost.

[0061] Determine whether the ratio of the difference between the current operating cost and the operating cost obtained in the previous iteration to the current operating cost is less than a preset threshold;

[0062] If so, stop iterating, take the current operating strategy as the economically optimal operating strategy, and use this strategy to control the operation of the distributed integrated energy system.

[0063] If not, the current operating strategy of the hydrogen energy equipment is passed to the heating sub-model as the initial condition, and the iteration continues until the optimal operating strategy is obtained.

[0064] This invention discloses a distributed integrated energy system model and its optimization solution method. It includes a heating network model, an equipment operation model, and an energy optimization model. The heating network model accurately describes the flow balance, energy conservation, and especially the heat transfer characteristics of the heating network pipelines to fully utilize the energy storage capacity of the heating network for economically optimized scheduling. Simultaneously, an optimization solution method based on this model is proposed. By constructing a hydrogen-electric coupling sub-model and a heating sub-model within the energy optimization model, the operating strategies of hydrogen energy equipment and heating equipment are processed hierarchically, thereby reducing the solution complexity. The solution method prioritizes the coupling of hydrogen energy equipment and electrical equipment to achieve efficient absorption of renewable energy sources such as photovoltaics, and dynamically adjusts the temperature and flow rate of the pipeline heat medium within the system. This effectively improves the adaptability and flexibility of the integrated energy system and optimizes system operation.

[0065] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0066] Example 1

[0067] This invention, based on an internal equipment operation model, a heating network model, and an energy optimization model, simultaneously obtains an operation model for a distributed integrated energy system. Its operation optimization solution method is as follows: Figure 5 As shown, it includes the following steps:

[0068] S1. Establish the internal operation structure of a distributed integrated energy system under typical scenarios, and based on the internal equipment and operating mechanism of the internal operation structure, establish an internal equipment operation model to obtain the internal equipment operation constraints; wherein, S1 includes the following steps:

[0069] S101. Establish the internal operation structure of a distributed integrated energy system under typical scenarios:

[0070] Please refer to Figure 1 In a first aspect, one embodiment of the present invention provides a distributed integrated energy system model, specifically including: 5 energy stations (SOURCE1, SOURCE2, SOURCE3, SOURCE4, SOURCE5), each energy station is equipped with an energy storage tank (WT1, WT2, WT3, WT4, WT5), and 5 user areas (LOAD1, LOAD2, LOAD3, LOAD4, LOAD5).

[0071] Specifically, the energy station, energy storage tank, and user area are connected by a heating pipeline network, which consists of pipes 1 to 40 in the figure. The red pipes are water supply pipes, the blue pipes are return pipes, and the arrows on the pipes indicate the direction of the heat medium flow in the pipes.

[0072] If the energy station, energy storage tank, and user area have the same serial number, it indicates that they are in the same area. For example, energy station SOURCE1, energy storage tank WT1, and user area LOAD1 are located in area 1. The water supply pipes and return pipes of the energy station, energy storage tank, and user area in the same area are connected to the common nodes in that area. For example, the water supply pipes of energy station SOURCE1, energy storage tank WT1, and user area LOAD1 are connected to node 1, and the return pipes are connected to node 10.

[0073] It should be noted that, in order to emphasize the heating network of the distributed integrated energy system, the power supply network between the energy station and the user load is omitted in the figure.

[0074] Please refer to Figure 2 The energy station provided in this embodiment is specifically a hydrogen-containing integrated energy station, which includes equipment such as power supply equipment, heating equipment, cooling equipment, hydrogen energy equipment, and energy storage equipment.

[0075] Specifically, the power supply equipment includes photovoltaic panels; the heating equipment includes electric boilers, air source heat pumps, ground source heat pumps, and sewage source heat pumps; the cooling equipment includes electric chillers, air source heat pumps, ground source heat pumps, and sewage source heat pumps; the hydrogen energy equipment includes electrolyzers and hydrogen fuel cells, wherein the hydrogen fuel cells are also combined heat and power (CHP) devices; and the energy storage equipment includes energy storage units and hydrogen storage tanks.

[0076] Specifically, photovoltaic panels are used to supply electricity to energy stations, or to power equipment such as electric chillers, electric boilers, heat pumps, and electrolytic cells. Energy stations can also purchase electricity from the grid. Surplus electricity can be stored in energy storage units.

[0077] After the electrolyzer completes hydrogen production, the hydrogen is transported to a hydrogen storage tank, which is used to supply hydrogen to the hydrogen fuel cell.

[0078] Specifically, the hydrogen stored in the hydrogen storage tank can also be purchased from external sources.

[0079] Air source heat pumps, ground source heat pumps, and sewage source heat pumps operate in heat production mode during the heating season, and their heat production, together with that of electric boilers and hydrogen fuel cells, constitutes the heat supply of the energy station. During the cooling season, air source heat pumps, ground source heat pumps, and sewage source heat pumps operate in cooling mode, and their cooling capacity, together with that of electric chillers, constitutes the cooling capacity of the energy station.

[0080] S102. Based on the internal operating structure, and according to the operating mechanism of each internal device, a model is established for each internal device to obtain the operating model and operating constraints of the internal device:

[0081] Specifically, the operating constraints of photovoltaic panels are:

[0082]

[0083] in, It represents the electricity generated by the photovoltaic panel at time t. It refers to the efficiency of the photovoltaic system. It is the total area occupied by the solar panel. It is the radiation value at time t.

[0084] The operating constraints of the electric chiller are:

[0085]

[0086] in, The power consumption of the electric chiller at time t. This refers to the refrigeration efficiency coefficient of the electric chiller. Let be the cooling capacity of the electric chiller at time t. This is the maximum power of the electric chiller.

[0087] The operating constraints of electric boilers are:

[0088]

[0089] in, Let be the power consumption of the electric boiler at time t. This represents the power generation efficiency coefficient of the electric boiler. Let t be the heat output of the electric boiler at time t. This represents the maximum power output of the electric boiler.

[0090] The operating constraints of a heat pump are:

[0091]

[0092] in, The heat pump operates in the following mode at time t ( The time indicates heating. (Time indicates cooling) Let be the power consumption of the heat pump at time t. and These represent the heating and cooling capacities of the heat pump at time t, respectively. and These are the heating and cooling efficiency coefficients of the heat pump, respectively. This is the maximum power of the heat pump.

[0093] The operating constraints of the electrolytic cell are:

[0094]

[0095] in, Let be the hydrogen production rate of the electrolyzer at time t. This represents the hydrogen production efficiency coefficient of the electrolyzer. Let be the power consumption of the electrolytic cell at time t. This represents the maximum power of the electrolytic cell.

[0096] The operating constraints of fuel cells are:

[0097]

[0098] in, Let t be the amount of hydrogen consumed by the fuel cell. Let be the power generation of the fuel cell at time t. This refers to the calorific value of hydrogen. The power generation efficiency coefficient of the fuel cell. Let t be the heat generated by the fuel cell at time t. The coefficient of performance for heat generation in a fuel cell is _____. This represents the maximum power of the fuel cell.

[0099] The operating constraints of the energy storage unit are:

[0100]

[0101] in, Let be the discharge amount of the energy storage unit at time t. Let t represent the state of the energy storage unit. Time indicates discharge. The time indicates charging.

[0102] The operating constraints of the hydrogen storage tank are:

[0103]

[0104] in, The state of the hydrogen storage tank at time t. Let t be the amount of hydrogen purchased. This represents the maximum hydrogen storage and release rate of the hydrogen storage tank. One scheduling cycle.

[0105] In addition, the operational constraints of the energy storage tank are:

[0106]

[0107] in, To release heat from the water tank, The time indicates heat release / cold storage. The time indicates cooling / heat storage. The water tank is in energy storage mode. This refers to the water storage capacity of the water tank. The water temperature in the tank. and These are the inlet and outlet water temperatures of the water tank, respectively. This refers to the inlet and outlet water flow rates of the water tank. and These are the specific heat capacity and density of water, respectively.

[0108] S103. Establish a heat network model based on the heat loss of the heat medium in the heating pipeline to determine the heat transfer characteristics of the pipeline, thereby obtaining the operating constraints of the heat network.

[0109] Please refer to Figure 3 The pipeline heat transfer characteristic model provided in this embodiment considers the heat loss of the heat medium in the heating pipeline. Firstly, for a pipeline with a length of... The heat medium micro-element is analyzed, and its initial temperature when it is emitted from the heat source is... .

[0110] Initially, the energy of the thermal medium's infinitesimal element... for

[0111]

[0112] in, The inner diameter of the pipe. This refers to the return water temperature in the pipeline.

[0113] Neglecting the interactions between the heat medium elements, we only consider the heat lost by the heat medium elements through the pipe wall. According to Fourier's law, we can obtain:

[0114]

[0115] in, It is the thermal conductivity of the pipe. It is the heat transfer area of ​​the isothermal surface of the thermal medium micro-element. It refers to the pipe wall thickness. The ambient temperature.

[0116] The amount of heat lost after time t from the heat source is:

[0117]

[0118] The energy of the infinitesimal element of the thermal medium at time t can be obtained by subtracting the lost heat from the initial energy:

[0119]

[0120] The temperature of the thermal medium element at time t can be obtained from the above formula:

[0121]

[0122] The relationship between heat transfer time and transfer distance Substituting into the above equation and taking the linear part of its Taylor expansion, we can obtain the steady-state temperature at a distance x from the heat source in the pipe as follows:

[0123]

[0124] in .

[0125] The pipeline heat transfer characteristic model assumes that the temperature at a point x away from the heat source in the pipeline changes linearly, and the transient heat transfer characteristics of the pipeline can be expressed as follows:

[0126]

[0127] in, and These represent the heat source temperatures in the initial and steady-state states, respectively. .when At that time, the thermal medium element originating from the heat source has not reached a distance x from the heat source, and the temperature at that location has not reached a steady state; when At that time, the thermal medium element that started from the heat source has reached a distance x from the heat source, where the temperature has reached a steady state.

[0128] Specifically, in A small element of heat medium, originating from the head of a pipe of length L at any given time, during the scheduling cycle... After that, if the end of the pipe is not reached, that is If this happens, the pipeline will never reach a steady state. Therefore, until... At time (i.e., at the start of the next scheduling), the temperature at the end of the pipe can be expressed as:

[0129]

[0130] During the scheduling period Afterwards, if the heat medium element flowing in from the head of the pipe has reached the end of the pipe, that is... Then the pipeline can reach a steady state, until At time (i.e., at the start of the next scheduling), the temperature at the end of the pipe can be expressed as:

[0131]

[0132] in, for The temperature at the end of the pipeline at that time (i.e., during the last scheduling). for Constant temperature at the head of the pipe.

[0133] Furthermore, for each pipe node in the heating network, the inflow rate of the medium into it at any given time should equal the outflow rate of the medium, thus there is a node flow balance constraint:

[0134]

[0135]

[0136] in and These are the upper and lower connection matrices of the heating network. It is a flow column vector. Let be the flow rate of the i-th branch.

[0137] For each pipeline node, the node energy conservation constraint must also be satisfied:

[0138]

[0139]

[0140] in and These are the head temperature and the end temperature of pipe i, respectively, where i = 1, 2, ..., 40.

[0141] The temperature of node n is equal to the energy of the outflowing medium.

[0142]

[0143] in Let be the temperature of the i-th node. The initial temperature of the pipe that is directly connected to the i-th node and from which the heat medium flows out.

[0144] There are also constraints on the supply and return water temperatures for energy stations and user areas:

[0145]

[0146] In the formula, These refer to the supply and return water temperatures of the energy station. and These refer to the supply and return water temperatures for the user area, respectively.

[0147] S2. Based on the relationship between energy supply and consumption in the distributed integrated energy system, obtain energy and heat balance constraints. Establish an energy optimization model based on internal equipment operation constraints, heating network operation constraints, and energy and heat balance constraints. This energy optimization model includes a hydrogen-electricity coupling sub-model and a heating sub-model. S2 includes the following steps:

[0148] S201. The constraints of the heating network model, equipment operation constraints, energy balance constraints, and heat constraints at the heat source and load ends are summarized into a hydrogen-electric coupling sub-model:

[0149] The output of the hydrogen-electric coupling sub-model is used to ensure that system operating costs are minimized while meeting user load requirements. Therefore, the objective function of the hydrogen-electric coupling sub-model is:

[0150]

[0151] in, The number of energy stations in the example is [number]. and These are the th terms within the desired optimization period. The cost of purchasing electricity and hydrogen for each energy station.

[0152] The constraints of the hydrogen-electric coupling sub-model are set as the constraints of the heat network model, equipment operation constraints, energy balance constraints, and heat constraints at the heat source and load ends.

[0153] Among them, energy balance constraint refers to the conservation of energy supplied and consumed by the distributed integrated energy system. Specifically, it includes electrical balance constraint and heating / cooling balance constraint.

[0154] The electrical balance constraint can be expressed as ,in, , These represent the power generation of the photovoltaic panel and the fuel cell at each moment. This represents the amount of energy stored and discharged by the energy storage unit at each moment. For the amount of electricity purchased from the grid at any given moment, This represents the power consumption of the electrolytic cell at any given moment. This refers to the power consumption of the electric boiler at any given moment. The power consumption of each type of heat pump at any given moment. This refers to the power consumption of the electric chiller at any given moment. This represents the electrical load at each moment.

[0155] The thermal equilibrium constraint can be expressed as ,in, To generate heat for the fuel cell at every moment, To ensure that each type of heat pump generates heat at all times, To ensure the cooling capacity produced by each type of heat pump at any given moment, To ensure the cooling capacity of the electric chiller at all times, To ensure the electric boiler generates heat at all times, To ensure the water tank releases heat at all times, Time indicates heat release. Time indicates cooling. For the heating and cooling load at each moment, The time indicates the heat load. The time indicates the cooling load.

[0156] Heat source-side heat constraint refers to the relationship between the total heat output of each energy station and the heat generated by each piece of equipment, as well as the relationship between the total heat output and the inlet and outlet water temperatures and flow rates. Specifically, it is expressed as follows:

[0157]

[0158]

[0159] in, The total output heat of energy station i For the influent and effluent flow rates of energy station i, The outlet water temperature of energy station i The inlet water temperature of energy station i.

[0160] Load-side heat constraint refers to the relationship between the total heat input to each load and the inlet and outlet water temperatures and flow rates, specifically expressed as:

[0161]

[0162] in, The total input heat for load i, Let i be the influent and effluent flow rates. Let i be the outlet water temperature. Let be the inlet water temperature of load i.

[0163] It should be noted that distributed integrated energy systems are mainly used to supply energy to users; therefore, the output of each energy source depends primarily on the user's load demand.

[0164] The load demand specifically includes user electrical load, heat load, and cooling load.

[0165] S202. The constraints of the heating network model, the operational constraints of heating and cooling related equipment, the heat balance constraints, and the heat constraints at the heat source and load ends are summarized into a heating sub-model:

[0166] In this embodiment, since the hydrogen energy-related part has already been solved in the hydrogen-electric coupling sub-model, the objective function of the heating sub-model is:

[0167]

[0168] in, The number of energy stations in the example is [number]. For the desired operation optimization period, the first The cost of purchasing electricity for each energy station.

[0169] The constraints of the heating network model specifically include the heating network operation constraints in the distributed integrated energy system operation model.

[0170] The operational constraints of the heating and cooling related equipment specifically include the operational constraints of electric boilers, electric chillers, heat pumps, water tanks, and fuel cells in the distributed integrated energy system operation model.

[0171] The thermal equilibrium constraint can be expressed as .

[0172] The heat constraint at the heat source end is expressed as:

[0173]

[0174]

[0175] The load-side thermal constraint is expressed as:

[0176]

[0177] The meanings of each symbol are the same as those of the cold-heat balance constraint and the heat source end heat constraint in the hydrogen-electric coupling sub-model.

[0178] S3. Based on the energy optimization model, iteratively solve the hydrogen-electric coupling sub-model and the heating sub-model to optimize the operation of the distributed integrated energy system. (Refer to...) Figure 4 S3 includes the following steps:

[0179] S301, Set initial values:

[0180] Set the initial pipe flow rate and the number of iterations. initial operating cost of the system .

[0181] It should be noted that setting the initial pipeline flow rate only provides a starting point for the solution process and will not affect the final solution result. However, when setting the initial pipeline flow rate, the node flow balance constraint must be satisfied.

[0182] Setting the initial operating cost of the system to positive infinity ensures that the operating cost obtained from the first solution is always less than the current operating cost, thus guaranteeing the feasibility of the solution algorithm.

[0183] S302. Perform the initial solution of the hydrogen-electric coupling sub-model using the initialization parameters:

[0184] The given initial pipeline flow rate is substituted into the hydrogen-electric coupling sub-model for solution. The operating strategy and operating cost in the solution results are saved, and the operating strategy of the hydrogen energy equipment and the temperature of the heat medium in each heating pipeline are passed to the heating sub-model as initial conditions.

[0185] In this embodiment, when solving the hydrogen-electric coupling sub-model, since the flow rate of the heating pipeline has already been given, there is no need to consider the node flow balance constraints.

[0186] S303. Solve the heating sub-model, and use the solution results of the heating sub-model to iteratively solve the hydrogen-electric coupling sub-model:

[0187] The operating strategy of the hydrogen energy equipment and the temperature of each heating pipeline are used to solve the heating sub-model based on the solution results of the hydrogen-electric coupling sub-model, and the flow rate of each pipeline is updated using the solution results.

[0188] Furthermore, the updated pipeline flow rate is passed to the hydrogen-electric coupling sub-model, and the hydrogen-electric coupling sub-model is solved again to obtain a new operating strategy and operating cost.

[0189] It should be noted that when solving the heating sub-model, only the equipment and constraints related to heating and cooling need to be considered, and the required loads only include heat load data and cooling load data. At this time, the electricity used by each heating and cooling equipment comes from the power grid.

[0190] S304. Determine if the current operating strategy is optimal:

[0191] Divide the difference between the current operating cost and the operating cost obtained in the previous iteration by the current operating cost, and determine whether its absolute value is less than the set threshold.

[0192] If not, update the results of the previous iteration using the operating strategy of the hydrogen energy equipment and the temperature of each heating pipeline from the solution results, and continue to execute S3.

[0193] If so, the current operating strategy is considered to be economically optimal, and the current operating cost is the minimum operating cost of the distributed integrated energy system. The current operating strategy is then output.

[0194] It should be noted that the final output of the model includes: the flow rate of each pipeline at each moment; the power generation of the photovoltaic panels in each energy station at each moment; the operating power and cooling capacity of the electric chiller in each energy station at each moment; the operating power and heat generation of the electric boiler in each energy station at each moment; the operating mode, operating power, and heat or cooling capacity of each heat pump in each energy station at each moment; the operating power and hydrogen production of the electrolyzer in each energy station at each moment; the power generation, heat generation, and hydrogen consumption of the hydrogen fuel cell in each energy station at each moment; the capacity, hydrogen storage capacity, and hydrogen consumption of the hydrogen storage tank in each energy station at each moment; the capacity, energy storage capacity, and energy consumption of the energy storage unit in each energy station at each moment; the inlet and outlet water temperatures of each energy storage tank at each moment; the inlet and outlet water temperatures of each energy station at each moment; and the inlet and outlet water temperatures of each user area at each moment.

[0195] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory). This computer-readable storage medium is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the optimization solution method for an optimized operating system of a distributed integrated energy system in the above embodiments.

[0196] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0197] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Those skilled in the art can readily implement the present invention based on the accompanying drawings and the above description. However, any modifications, alterations, or variations made by those skilled in the art without departing from the scope of the present invention, utilizing the disclosed technical content, are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, or variations made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the present invention.

Claims

1. A method for establishing an optimized operation system for distributed integrated energy, characterized in that, include, Based on the internal operating structure of the distributed integrated energy system, and according to the operating mechanism of each internal device, an internal device operation model is established to obtain the internal device operation constraints. A heat network model is established based on the heat loss of the heat medium in the heating pipeline to determine the heat transfer characteristics of the pipeline and obtain the operating constraints of the heat network. Based on the relationship between energy supply and consumption in a distributed integrated energy system, energy and thermal balance constraints are obtained; An energy optimization model is established based on internal equipment operation constraints, heating network operation constraints, and energy and heat balance constraints; the energy optimization model includes a hydrogen-electric coupling sub-model and a heating sub-model. Based on the internal equipment operation model, the heating network model, and the energy optimization model, an optimized operation system for distributed integrated energy is obtained by combining them. The hydrogen-electric coupling sub-model is established through constraints of the heat network model, internal equipment operation constraints, energy balance constraints, and heat constraints at the heat source end and the load end; the energy balance constraints include electrical balance constraints and cold-heat balance constraints. The heating sub-model is established through heating network operation constraints, internal equipment operation constraints including heating and cooling related equipment operation constraints, heat balance constraints, and heat source and load end heat constraints. The operating constraints of the heating and cooling related equipment include operating constraints of electric boilers, electric chillers, heat pumps, water tanks, and fuel cells.

2. The method for establishing an optimized operation system for distributed integrated energy according to claim 1, characterized in that, The internal equipment operation constraints include: operation constraints of photovoltaic panels, operation constraints of electric chillers, operation constraints of electric boilers, operation constraints of heat pumps, operation constraints of electrolyzers, operation constraints of fuel cells, operation constraints of energy storage units, operation constraints of hydrogen storage tanks, and operation constraints of energy storage water tanks; the heating network operation constraints include node flow balance constraints, node energy conservation constraints, pipeline water supply and return temperature constraints, and pipeline heat transfer characteristic constraints. The internal operating structure is an energy transmission system that connects the energy station, the energy storage tank, and the user area through a heating pipeline network.

3. The method for establishing an optimized operation system for distributed integrated energy according to claim 1, characterized in that, The objective function of the hydrogen-electricity coupling sub-model is the minimization function of the costs of purchasing electricity and hydrogen, and the specific formula is as follows: in, For the number of energy stations, and These are the th terms within the desired optimization period. The cost of purchasing electricity and hydrogen for each energy station.

4. The method for establishing an optimized operation system for distributed integrated energy according to claim 1, characterized in that, The objective function of the heating sub-model is to minimize the electricity purchase cost, and the specific formula is as follows: in, For the number of energy stations, For the desired operation optimization period, the first The cost of purchasing electricity for each energy station.

5. An optimized operation system for distributed integrated energy, obtained based on the method for establishing an optimized operation system for distributed integrated energy as described in any one of claims 1-4.

6. The optimization solution method for a distributed integrated energy system as described in claim 5, characterized in that, include, Solve the hydrogen-electric coupling sub-model to obtain the operation strategy and cost of the distributed integrated energy system. Transfer the operation strategy of the hydrogen energy equipment and the temperature of the heating pipeline to the heating sub-model as initial conditions. Solve the heating sub-model, update the pipeline flow rate using the obtained heating flow rate, and then feed the updated pipeline flow rate back to the hydrogen-electric coupling sub-model. Iterate through solving the hydrogen-electric coupling model until the optimal operating strategy and operating cost are obtained. Specifically: Determine whether the ratio of the difference between the current operating cost of the distributed integrated energy system and the operating cost obtained in the previous iteration to the current operating cost is less than a preset threshold. If the value is less than the preset threshold, the iteration stops, and the current operating strategy of the distributed integrated energy system is taken as the economically optimal operating strategy, and the strategy is used to control the operation of the distributed integrated energy system. If the value is not less than the preset threshold, the current operating strategy of the hydrogen energy equipment is passed to the heating sub-model as the initial condition, and the iteration continues until the economically optimal operating strategy is obtained.

7. An optimization solution system for an optimized operation system of a distributed integrated energy system, obtained based on the optimization solution method for an optimized operation system of a distributed integrated energy system as described in claim 6.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the optimization solution method for an optimized operation system of a distributed integrated energy system as described in claim 6.

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