CN-121980922-A - Design optimization method for comprehensive energy system

CN121980922ACN 121980922 ACN121980922 ACN 121980922ACN-121980922-A

Abstract

The invention relates to a comprehensive energy system design optimization method, which is suitable for the field of comprehensive energy system planning and design. The method comprises the steps of building a digital twin simulation model capable of reflecting actual operation characteristics of a system according to energy equipment composition of a comprehensive energy system, determining corresponding intelligent body types of all equipment according to function types of the energy equipment related to the comprehensive energy system, building an intelligent body model capable of quantitatively describing optimization targets of all the energy equipment, building a design scheme virtual verification sand table based on the digital twin simulation model and the intelligent body models corresponding to all the energy equipment, wherein equipment operation parameters output by the digital twin simulation model are used as input of the intelligent body model, performing global optimization on alternative design scheme combinations by adopting a heuristic optimization algorithm and combining the system optimization targets based on the virtual verification sand table, and outputting an optimal design scheme of the comprehensive energy system, wherein the design scheme comprises equipment capacity parameters of the energy equipment related to the comprehensive energy system.

Inventors

WANG ZIHAO
FANG HAO
HUANG YANZHONG
XU JUNYANG
LI DEDI
WU YUECHAO
LUO YUANLIN
ZHENG LI

Assignees

中国电建集团华东勘测设计研究院有限公司
杭州华辰电力控制工程有限公司

Dates

Publication Date: 20260505
Application Date: 20251226

Claims (10)

1. The comprehensive energy system design optimization method is characterized by comprising the following steps of: According to the energy equipment composition of the comprehensive energy system to be built, a digital twin simulation model capable of reflecting the actual operation characteristics of the system is built; determining the types of the intelligent agents corresponding to the devices according to the function types of the energy devices related to the comprehensive energy system, and establishing an intelligent agent model capable of quantitatively describing the optimization targets of the energy devices; constructing a design scheme virtual verification sand table based on the digital twin simulation model and an agent model corresponding to each energy device, wherein the device operation parameters output by the digital twin simulation model are used as the input of the agent model; based on the virtual verification sand table, adopting a heuristic optimization algorithm and combining a system optimization target to globally optimize the combination of alternative design schemes and output an optimal design scheme of the comprehensive energy system, wherein the design scheme comprises equipment capacity parameters of energy equipment related to the comprehensive energy system; The energy equipment optimization targets are equipment annual total cost, including equipment annual investment cost and equipment annual operation cost, and the system optimization targets are system annual total cost, which is determined based on the equipment annual total cost of each energy equipment in the system.
2. The integrated energy system design optimization method of claim 1, wherein the types of agents include energy production facility agents, energy conversion facility agents, energy storage facility agents, and end use energy load agents.
3. The integrated energy system design optimization method according to claim 1 or 2, wherein the energy device optimization objective is quantified by combining the device operation parameter and the device capacity parameter based on the type of the intelligent agent corresponding to the energy device.
4. The integrated energy system design optimization method of claim 2, wherein the energy production facility agent comprises: ; wherein the subscript Represents an energy source production device, and the energy source production device, Representing an equal-annual factor of the device, Representing a fixed maintenance cost factor for the device, Representing the net residual rate of the device, Indicating the life cycle of the device, Indicating the design capacity of the device, Representing the investment cost per unit capacity of the device, Representation of The price of energy source at the moment of time, Representation of Power consumption at the moment.
5. The integrated energy system design optimization method of claim 2, wherein the intelligent agent model of the energy conversion device is represented by the following formula: ; ; wherein the subscript An energy conversion device is represented as such, And Respectively represent The energy power after and before the time conversion, Representing the transfer function between the different energy forms, is determined by the thermodynamic characteristics of the particular energy conversion device.
6. The integrated energy system design optimization method of claim 2, wherein the agent model of the energy storage device is represented by the following formula: ; ; wherein the subscript Representing an energy storage device such as a solar energy storage device, Representation of The energy charging and discharging amount at the moment, The energy charging is represented by the energy charging, Indicating the energy release of the device, Represents the energy storage state of the energy storage device, is determined by the energy storage state and the energy charging and discharging amount at the last moment, Representing the energy storage efficiency of the energy storage device, And Respectively representing the charging efficiency and the discharging efficiency.
7. The integrated energy system design optimization method of claim 2, wherein the end-use energy load agent model is represented by the formula: ; wherein the subscript The energy load for the end is represented, Representation of The energy demand at the moment of time, Representing the energy compensation price of the end-use energy load participating in the demand side response, Representation of The reference demand of the energy source at the moment, The weight coefficient is represented by a number of weight coefficients, Representing the end user's satisfaction function.
8. An integrated energy system design optimization device, comprising: The simulation model building model is used for building a digital twin simulation model capable of reflecting the actual operation characteristics of the system according to the energy equipment composition of the comprehensive energy system to be built; The intelligent agent construction module is used for determining the intelligent agent type corresponding to each device according to the function type of the energy device related to the comprehensive energy system and establishing an intelligent agent model capable of quantitatively describing the optimization target of each energy device; the verification sand table construction module is used for constructing a virtual verification sand table of a design scheme based on the digital twin simulation model and the intelligent body model corresponding to each energy device, and taking the device operation parameters output by the digital twin simulation model as the input of the intelligent body model; The design scheme optimizing module is used for carrying out global optimization on the combination of alternative design schemes by adopting a heuristic optimization algorithm and combining a system optimization target based on the virtual verification sand table and outputting an optimal design scheme of the comprehensive energy system, wherein the design scheme comprises equipment capacity parameters of energy equipment related to the comprehensive energy system; The energy equipment optimization targets are equipment annual total cost, including equipment annual investment cost and equipment annual operation cost, and the system optimization targets are system annual total cost, which is determined based on the equipment annual total cost of each energy equipment in the system.
9. A storage medium having stored thereon a computer program executable by a processor, wherein the computer program when executed performs the steps of the integrated energy system design optimization method of any one of claims 1 to 7.
10. An integrated energy system design optimization device having a memory and a processor, the memory storing a computer program executable by the processor, characterized in that the computer program when executed implements the steps of the integrated energy system design optimization method of any one of claims 1 to 7.

Description

Design optimization method for comprehensive energy system Technical Field The invention relates to a design optimization method of a comprehensive energy system. The method is suitable for the field of comprehensive energy system planning and design. Background The comprehensive energy system can integrate various renewable energy sources such as wind power, photovoltaic and the like in an area, and through coordination optimization and efficient complementation of energy flows in various forms such as cold, hot and electric, the absorption rate and the overall energy utilization efficiency of the renewable energy sources are improved, and the multi-element energy utilization load demands of end users are ensured. As a most basic and important ring in the engineering application of the comprehensive energy system, the development of the optimization design research of the comprehensive energy system has important significance in reducing the construction cost of the system and improving the overall economy of the system, and can promote the large-scale application and popularization of the comprehensive energy system in practical projects. The comprehensive energy system has the characteristics of long project implementation period, wide system operation working condition, complex multi-energy flow coupling and the like, the existing research method is difficult to simultaneously consider the investment cost of the early stage of the system and the operation cost under the full life cycle when designing and planning, and the energy supply reliability of the planning scheme in the actual variable operation working condition is ensured. How to fully utilize advanced technologies such as artificial intelligence and the like to realize global optimization design and planning of the comprehensive energy system is still to be further researched. Disclosure of Invention The invention aims to solve the technical problems and provides a comprehensive energy system design optimization method. The technical scheme adopted by the invention is that the comprehensive energy system design optimization method comprises the following steps: According to the energy equipment composition of the comprehensive energy system to be built, a digital twin simulation model capable of reflecting the actual operation characteristics of the system is built; determining the types of the intelligent agents corresponding to the devices according to the function types of the energy devices related to the comprehensive energy system, and establishing an intelligent agent model capable of quantitatively describing the optimization targets of the energy devices; constructing a design scheme virtual verification sand table based on the digital twin simulation model and an agent model corresponding to each energy device, wherein the device operation parameters output by the digital twin simulation model are used as the input of the agent model; based on the virtual verification sand table, adopting a heuristic optimization algorithm and combining a system optimization target to globally optimize the combination of alternative design schemes and output an optimal design scheme of the comprehensive energy system, wherein the design scheme comprises equipment capacity parameters of energy equipment related to the comprehensive energy system; The energy equipment optimization targets are equipment annual total cost, including equipment annual investment cost and equipment annual operation cost, and the system optimization targets are system annual total cost, which is determined based on the equipment annual total cost of each energy equipment in the system. The intelligent agent type comprises an energy production equipment intelligent agent, an energy conversion equipment intelligent agent, an energy storage equipment intelligent agent and an end energy utilization load intelligent agent. The intelligent agent model of the energy equipment is based on the intelligent agent type corresponding to the energy equipment, and the energy equipment optimization target is quantized by combining equipment operation parameters and equipment capacity parameters. The energy production facility agent includes: ; wherein the subscript Represents an energy source production device, and the energy source production device,Representing an equal-annual factor of the device,Representing a fixed maintenance cost factor for the device,Representing the net residual rate of the device,Indicating the life cycle of the device,Indicating the design capacity of the device,Representing the investment cost per unit capacity of the device,Representation ofThe price of energy source at the moment of time,Representation ofPower consumption at the moment. The intelligent body model of the energy conversion equipment is shown as follows: ; ; wherein the subscript An energy conversion device is represented as such,AndRespectively representThe energy power after and before the time