Integrated Intelligent Energy ›› 2026, Vol. 48 ›› Issue (1): 23-33.doi: 10.3969/j.issn.2097-0706.2026.01.003

• Optimization and Scheduling of Integrated Intelligent Energy System • Previous Articles     Next Articles

Research on hierarchical optimization scheduling of multi-energy complementary adaptive variable step-size SMPC for energy island

LI Kuo1(), TANG Yang1(), LIU Botao2(), HUANG Haocheng3a,3b(), SHAO Xianjie3a,3b(), YIN Gaojun3a,3b(), WEI Shangshang3a,3b,*()   

  1. 1. Power China Renewable Energy Company Limited,Beijing 100101,China
    2. Rundian Energy Science and Technology Company Limited,Zhengzhou 450018,China
    3a. School of Renewable Energy;b. National Wind Power Technology Innovation Center,Hohai University,Changzhou 213200,China
  • Received:2025-07-22 Revised:2025-08-05 Published:2026-01-25
  • Contact: WEI Shangshang E-mail:likuo0607@163.com;ty676854@163.com;looepr2011@163.com;huanghchhu0708@163.com;supoqiaji@163.com;yin1003895936@163.com;weishsh@hhu.edu.cn
  • Supported by:
    National Natural Science Foundation of China Project(52406233);China Postdoctoral Science Foundation General Funding Program(2024M750738);Technological Innovation Special Fund Project for Carbon Peaking and Carbon Neutrality in Jiangsu Province(BT024004);Changzhou Science and Technology Plan Project(525011412)

Abstract:

Based on a multi-objective hierarchical optimization method, a hierarchical collaborative optimization model for the multi-energy complementary system in an offshore energy island was constructed, considering both system balance and economic efficiency of scheduling. To address the impact of the volatility and randomness of wind and solar energy on the scheduling of the offshore energy island system, the stochastic model predictive control (SMPC) method was adopted to optimize the scheduling of the offshore energy island. A scheduling method of adaptive variable step-size SMPC was proposed. In the rolling optimization link of SMPC, the real-time scheduling deviation degree was tracked through a deviation reference coefficient using the proposed method, and the rolling optimization step-size was adjusted accordingly. This addressed the problems of scheduling accuracy loss and local optimization in the rolling optimization phase of the traditional SMPC scheduling method, thereby balancing scheduling accuracy and globality. The simulation results show that this method can effectively improve the scheduling accuracy and shorten calculation time.

Key words: hierarchical optimization, offshore energy island, multi-energy complementary system, adaptive variable step-size, stochastic model predictive control

CLC Number: