基于融合寻优算法的热电负荷经济性调度
惠斌斌¹，陈干勇¹，杨利^2，3，郑天帅^2，3，张文武¹，刘永林^2，3，刘学亮^2，3，韩威¹
（1. 国能（福州）热电有限公司，福建 福清 350309；2. 西安热工研究院有限公司，陕西 西安 710054；
3. 西安西热节能技术有限公司，陕西 西安 710054）
摘要： 在“双碳”目标下，发展能源利用效率高的热电联产电厂是非常必要的。热电负荷经济性调度是热电联产电厂降
低能耗、提高企业经济效益的重要技术手段。为了获得更具经济优势的负荷分配结果，以文献中七机组的典型热电联产电
厂为例，构建了热电负荷分配经济性模型，通过引入布谷鸟灰狼融合算法，同时使用惩罚函数进行约束处理，构建得到了
不同的优化分配方案，并对所建立模型进行了负荷经济性调度。结果表明：优化后发电成本最低可达10 113.81 美元/h，与
文献结果接近，且优于传统方案优化效果。此外，4 种不同方案的优化结果对比表明，提出的CS-GWO 算法在算法性能
方面具有明显优势，其展现出了更好的收敛性及鲁棒性，能更加快速、准确地为电厂与电网、热网间的负荷匹配问题提
供合理的解决方案。
关键词： 热电联产；灰狼算法；布谷鸟搜索算法；负荷经济性调度
中图分类号： TK121     文献标志码： A     文章编号： 2095-0802-(2022)10-0039-07
Economic Dispatch of Heat and Power Load Based on Optimization Fusion Algorithm
HUI Binbin¹, CHEN Ganyong¹, YANG Li^2,3, ZHENG Tianshuai^2,3, ZHANG Wenwu¹, LIU Yonglin^2,3,
LIU Xueliang^2,3, HAN Wei¹
(1. CHN Energy (Fuzhou) Thermal Power Co., Ltd., Fuqing 350309, Fujian, China; 2. Xi'an Thermal Power Research Institute
Co., Ltd., Xi'an 710054, Shaanxi, China; 3. Xi'an TPRI Energy Conservation Technology Co., Ltd., Xi'an 710054,
Shaanxi, China)
Abstract: Under the goals of "carbon peaking and carbon neutrality", it is necessary to develop cogeneration plants with high
energy utilization efficiency. For cogeneration plants, the heat and power load economic dispatch (LED) is an important means to
further reduce energy consumption and improve economic benefits of enterprises. To obtain a better load dispatch effect, a hybrid
Grey Wolf Optimization (GWO) algorithm integrated with Cuckoo Search (CS) was introduced. Based on CS-GWO algorithm and
LED problem constraint processing method, four optimization methods were proposed to solve the LED problem of a cogeneration
plant consisting of 7 units for achieving a low operation cost. The results show that the minimum operating cost can achieve
10 113.81 $/h, which is significantly lower than the value reported in the literature. In addition, the comparison results of four
optimization methods show that the CS-GWO algorithm has obvious advantages in terms of algorithm performance compared with
the GWO algorithm. Moreover, combined with the constraint processing scheme proposed in this paper, the CS-GWO algorithm
shows better convergence and robustness, and it is more suitable for solving practical engineering problems similar to thermal
power load dispatch. The CS-GWO algorithm can provide a good solution between the power plant and the power grid and the
heating network accurately.

Key words: cogeneration; Grey Wolf algorithm; Cuckoo Search algorithm; economic dispatch of load