基于CiteSpace的能源系统优化调度研究热点与趋势分析

Research hotspots and trends analysis of energy systems optimal scheduling based on CiteSpace

能源系统优化调度对保证能源供需平衡有重要作用。对30余年国内外该领域发展状况、热点及趋势的量化对比,通过CiteSpace软件对1990—2022年CNKI和WoS数据库的能源系统优化调度进行分析。结果表明:该领域虽处于常规科学阶段但文献具有高增速,国内文献增速较国际快且机构间交流密切;国外热点为微电网的优化算法、不确定性和稳定性控制,综合能源系统的含储能动态调度,调度技术的强化学习和博弈论;国内热点趋势为微电网的算法-动态优化/双层优化/分时电价-多智能体-需求侧管理-深度学习及综合能源系统的不确定性-能源集线器-电转气-综合需求响应-数据驱动-碳交易、碳捕集和强化学习等。由分析结果可见,启发式算法和深度学习等在未来大规模能源系统下有望实现研究范式转变。

The optimal scheduling of energy systems is important in ensuring the balance of energy supply and demand.Quantitative comparative studies of the development status,hot spots and trends in this field at home and abroad for more than 30 years,an analysis of the CNKI and WoS from 1990-2022 through CiteSpace software was done.The results show that:the field is in the conventional scientific stage but the literature has a high growth rate,the domestic literature growth rate is faster than the international and the inter-institutional exchange is close;the foreign hotspots are optimization algorithms,uncertainty and stability control for microgrids,dynamic scheduling with energy storage for integrated energy system(IES),as well as reinforcement learning and game theory for scheduling technique;the domestic hotspot trends are algorithms,dynamic optimization/bilayer optimization/time-sharing tariffs,multi-intelligent bodies,demand side management and deep learning for microgrids,as well as uncertainty,energy hubs,electricity to gas,integrated demand response,data driven,carbon trading,carbon capture and reinforcement learning for IES.The results show heuristic algorithms and deep learning techniques are expected to achieve a paradigm shift in future large-scale energy systems.