Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (4): 1129-1135.doi: 10.13229/j.cnki.jdxbgxb.20221560

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Collaborative optimal scheduling of renewable energy systems based on improved MOEA/D algorithm

Xin-gang ZHAO1,2(),Zhen WANG1,2   

  1. 1.School of Economics and Management，North China Electric Power University，Beijing 102206，China
    2.Beijing Key Laboratory of New Energy and Low-Carbon Development，Beijing 102206，China
  • Received:2022-12-06 Online:2024-04-01 Published:2024-05-17

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Abstract:

Microgrid with renewable energy system has high economy and environmental protection， and requires system load to be flexible and controllable， that is， resources can be coordinated for scheduling operation. Therefore， a collaborative optimal scheduling method for renewable energy system based on improved MOEA/D algorithm is proposed. Build key power generation models in renewable energy systems， including photovoltaic array model， wind power generation model and energy storage battery model. With the lowest energy consumption as the goal， build the system's collaborative optimal scheduling function， obtain the functional constraints of electric power and thermal power balance， and use the improved MOEA/D algorithm to solve the optimal solution of the function to achieve the collaborative optimal scheduling of renewable energy systems. The experimental results show that the proposed method has good SOC value control constraint ability， and the SOC value control result is the closest to the ideal state. Under the environmental optimization criterion， the system scheduling energy consumption is low， and the 24-hour energy consumption power is 0.6 kW.

Key words: MOEA/D algorithm, photovoltaic power generation, including renewable energy system, collaborative optimal scheduling, power consumption

CLC Number: 

  • TP242

Table 1

Experimental environment"

含可再生能源系统设备参数
含可再生能源功率2 000 kW
生产性能的储能模块1 000 kW/1 000 kW·h
电力储能第一单元2 500 kW/2 500 kW·h
电力储能第二单元2*2 000 kW/2 000 kW·h
电制冷机2*2 600 kW
燃气机2 040 kW
热储能模块1 720 kW/12 500 kW·h
燃气锅炉5 500 kW
余热吸收式冷温水机4 600 kW/3 450 kW
冷储能模块1 720 kW/12 500 kW·h

Fig.1

SOC value control results of three methods"

Fig.2

Energy consumption of three methods"

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