基于量子万有引力算法的多能联合系统优化调度
Optimization scheduling for a multi-energy joint system based on a quantum universal gravity algorithm
吴凯槟 1邱泽晶1
作者信息
- 1. 国网电力科学研究院有限公司,江苏 南京 210000;国网电力科学研究院武汉能效测评有限公司,湖北 武汉 430074
- 折叠
摘要
为提高风光火一体化系统中风光资源的消纳水平和降低综合运营成本,提出一种多目标优化调度方法.构建以经济收益最大化、新能源消纳最大化及输出波动最小化为目标的多目标优化调度模型,提出量子启发式增强的万有引力算法,通过引入量子旋转门、自适应步长及突变概率来提升算法的搜索效率与精度,增强全局搜索能力.通过仿真验证该模型的有效性.研究结果表明:该方法在保障系统安全的前提下,显著提升了系统的经济性和环保性,全年可增加收益 2.33 亿元,减少碳排放34.42 万吨,节约标准煤 12.94 万吨.
Abstract
In order to improve the consumption level of wind and solar resources and reduce the comprehensive operation cost in the wind-solar-thermal integrated system,a multi-objective optimization scheduling method is proposed.A multi-objective optimization model is established with the goals of maximizing economic benefits,maximizing renewable energy utilization,and minimizing output fluctuations.A quantum-inspired enhanced gravitational search algorithm is introduced,by incorporating quantum rotation gates,adaptive step sizes,and mutation probabilities to improve search efficiency and accuracy,and enhance the algorithm's global search capability.The model's effectiveness is verified through simulations.The results show that,while ensuring system safety,this method significantly improves the system's economic and environmental performance,with an annual increase in revenue of 233 million yuan,a reduction in carbon emissions by 344 200 tons,and a savings of 129 400 tons of standard coal.
关键词
"双碳"目标/多目标优化/多能联合系统/量子启发式算法/万有引力算法Key words
"carbon peaking and carbon neutrality"goals/multi-target optimization/multi-energy joint system/quantum heuristic algorithm/universal gravity algorithm引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据