电力市场环境下生物质气化耦合燃煤机组与风电场联合自调度优化策略
Joint Self-scheduling Optimization Strategy of Biomass Gasification Coupled Coal-fired Thermal Power Unit and Wind Farm Under Power Market Environment
郭旭升 1娄素华 1张金平 2李湃2
作者信息
- 1. 强电磁技术全国重点实验室(华中科技大学),湖北省武汉市 430074
- 2. 可再生能源并网全国重点实验室(中国电力科学研究院有限公司),北京市海淀区 100192
- 折叠
摘要
利用生物质气化耦合燃煤发电技术可以提升火电机组的燃料及运行灵活性,从而促进风电的高水平消纳,同时实现生物质能的有效开发利用.该文首先建立反映生物质气化耦合热电联产机组内部能流过程和外部出力特性的运行模型.然后,从能源供应商视角出发,给出耦合机组与风电场联合参与日前、日内和实时平衡市场的多阶段决策框架,提出反映联合体期望收益和条件风险价值的多目标自调度策略.最后,利用基于字典优化框架的增强e约束法,给出构建帕累托前沿的多目标优化求解流程.以一台350MW燃煤热电联产机组和一座600MW风电场构成的联合体为例进行分析.结果可知,增设生物质气化子系统和联合运行能够使其经济效益提升6％左右,同时有利于降低能源供应商的运营风险.
Abstract
Biomass gasification coupled coal-fired power generation technology can enhance the fuel and operation flexibility of thermal power units,thereby promoting the high-level accommodation of wind power as well as the effective exploitation of biomass energy.In this paper,an operation model reflecting the internal energy flow processes and the external output characteristics of the biomass gasification coupled CHP unit is firstly established.Then,from the perspective of an energy supplier,a multi-objective self-scheduling strategy reflecting the expected benefits and conditional value-at-risk(CVaR)of the coalition is proposed,considering the multi-stage decision framework for the joint participation of the coupled unit and the wind farm in the day-ahead,intra-day and real-time balancing markets.Finally,the multi-objective optimization solution procedure for constructing the Pareto front is illustrated using the augmented e-constraint method based on lexicographic optimization.The numerical analysis is performed to demonstrate that the addition of biomass gasification subsystem and the joint operation of the 350 MW CHP unit and the 600 MW wind farm can increase their economic benefits by about 6％,as well as reduce the operation risk of the energy supplier.
关键词
生物质气化耦合技术/燃煤热电联产机组/风电出力/联合运行/自调度策略Key words
biomass gasification coupling technology/coal-fired combined heat and power unit/wind power/joint operation/self-scheduling strategy引用本文复制引用
基金项目
国家重点研发计划项目(2022YFB2403004)
国家自然科学基金项目(51977087)
出版年
2024
国家科技期刊平台
NSTL
万方数据