摘要
为了提升不确定性环境中含光热电站热电联供型微网(CSP-CHPMG)优化调度的鲁棒性,基于机会约束高斯混合模型构造风电功率预测误差和负荷预测误差的不确定性集合,以实现对调度方案鲁棒性的准确描述;将鲁棒性作为协同优化目标,并计及电能需求响应构建CSP-CHPMG鲁棒经济多目标优化调度模型,以保障调度方案的鲁棒性和经济性,实现最佳均衡协调。算例结果验证了所提方法的优越性。
In order to improve the robustness of optimal dispatch of CSP-CHPMG(Concentrated Solar Power-Combined Heating and Power MicroGrid)in uncertain environment,the uncertain sets of wind power forecasting error and load forecasting error based on opportunity constraint Gaussian mixture model are constructed to realize accurate description of the robustness of dispatch scheme.Robustness is taken as the collaborative optimization target,and the robust economic multi-objective optimal dispatch model of CSP-CHPMG is built considering power demand response,which ensures the robustness and economy of the dispatch scheme and achieves the best balanced coordination.Case results verify the superiority of the proposed method.
作者
彭春华
陈婧
郑聪
PENG Chunhua;CHEN Jing;ZHENG Cong(School of Electrical and Automation Engineering,East China Jiaotong University,Nanchang 330013,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2021年第4期77-84,93,共9页
Electric Power Automation Equipment
基金
国家自然科学基金资助项目(51867008)
江西省自然科学基金资助项目(20192ACBL20007,20202BAB204024)
江西省主要学科学术和技术带头人项目(20204BCJL22038)
江西省教育厅科技项目(GJJ1903013)
江西省研究生创新资金资助项目(YC2019-S260)。
关键词
太阳能光热电站
高斯混合模型
机会约束
需求响应
鲁棒优化
concentrated solar power plant
Gaussian mixture model
opportunity constraint
demand response
robust optimization
