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Multi-objective integrated design and optimization control method for comprehensive energy system

An integrated energy system, multi-objective integration technology, applied in the field of multi-objective integrated design and optimal control of integrated energy systems, can solve problems such as lack of, complex structure, and failure to consider the overall efficiency capacity configuration of integrated energy systems and the progressive relationship of optimal control.

Active Publication Date: 2018-12-21
STATE GRID SHANDONG ELECTRIC POWER +2
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AI Technical Summary

Problems solved by technology

[0003] The comprehensive energy system faces huge technical challenges in parameter design, capacity configuration and optimal control due to its complex structure, various types of equipment, large differences in operating characteristics, thermal and electrical coupling characteristics, and high-permeability new energy.
At present, there is no lack of relevant research and method application. It only studies the parameter optimization of a single device in the integrated energy system, or one of the aspects of parameter design, capacity configuration and optimal control, without considering the overall efficiency of the integrated energy system or parameter design and capacity configuration. The progressive relationship between optimization and control, and energy efficiency, operating economy, and new energy consumption levels need to be considered comprehensively, and collaborative optimization design and operation control

Method used

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  • Multi-objective integrated design and optimization control method for comprehensive energy system
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  • Multi-objective integrated design and optimization control method for comprehensive energy system

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Embodiment 1

[0071] Such as figure 1 As shown, the multi-objective integrated design and optimal control method of the comprehensive energy system of the present invention includes the following steps:

[0072] S1: Building the optimal operating mode of the system: building the optimal operating mode of the system is divided into system parameter optimization layer, system capacity configuration optimization layer, and system operation control optimization layer;

[0073] S2: Build the system parameter optimization layer: including the following small steps:

[0074] S21: Parameter design: it is divided into three steps: optimization objective, optimization variable and constraint condition, specifically including the following sub-steps:

[0075] S211: Optimization objective: take the maximization of system power conversion efficiency and system entropy efficiency as optimization objectives;

[0076] Among them, the maximum power conversion efficiency of the system is expressed as:

[...

Embodiment 2

[0128] Such as figure 2 As shown, the equipment in the integrated energy system in step S311, including micro gas turbines, wind power generation systems, photovoltaic power generation systems, compressed air energy storage systems and heat storage systems, can provide cooling, heating and power requirements for users and loads.

[0129] Among them, photovoltaic power generation system and wind power generation system provide users with clean electricity. Micro gas turbines and compressed air energy storage systems are used to stabilize the intermittent and fluctuating output power of new energy sources. At the same time, the micro gas turbine and compressed air energy storage system make full use of the waste heat generated by the system to provide users with cooling, heating and power needs and improve the efficiency of energy cascade utilization.

[0130] Specifically, such as image 3 As shown, the compressed air energy storage system in step S311 includes a compressor,...

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Abstract

The invention relates to a multi-objective integrated design and optimization control method for a comprehensive energy system, and belongs to the technical field of new energy power generation and energy storage. A system parameter optimization layer of the invention takes a maximized system electric energy conversion efficiency and a maximized system entropy efficiency as optimization objectives, and takes an output gas temperature and an expansion ratio of a compressed air energy storage system as optimization variables. A system capacity configuration optimization layer takes minimized system economic cost and minimized pollutant emission as the optimization objectives, and takes capacity configuration of a microturbine, a wind power generation system, a photovoltaic power generation system and a compressed air energy storage system as the optimization variables. Besides, a system operation control optimization layer takes minimized system operation cost, minimized SOC in the compressed air energy storage system, and minimized system relative energy consumption as the optimization objectives. A multi-objective genetic algorithm is adopted by the three layers for obtaining a Pareto optimal solution set, and energy efficiency, operation economic efficiency and new energy consumption level of the comprehensive energy system are improved through a fuzzy decision-making method.

Description

technical field [0001] The invention relates to a multi-objective integrated design and optimization control method for a comprehensive energy system, which belongs to the technical field of new energy power generation and energy storage. Background technique [0002] The integrated energy system refers to the use of advanced physical information technology and innovative management models in a certain area to integrate various energy sources such as coal, oil, natural gas, electric energy, and thermal energy in a certain area to achieve coordinated planning among various heterogeneous energy subsystems. Optimize operation, collaborative management, interactive response and mutual assistance. While meeting the diversified energy demand within the system, it is necessary to effectively improve energy utilization efficiency and promote a new integrated energy system for sustainable energy development. [0003] The comprehensive energy system faces huge technical challenges in...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/418G06Q10/04G06Q10/06G06Q50/06
CPCG05B19/41885G05B2219/32339G06Q10/04G06Q10/0631G06Q10/0637G06Q50/06Y02P90/02
Inventor 王超王瑞琪孙振海安树怀许玮慕世友
Owner STATE GRID SHANDONG ELECTRIC POWER
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