摘要
微能网是实现多能互补的有效技术手段之一。以包含电转气和电池-超级电容器混合储能系统的电-热-气联供型微能网为研究对象,针对风光出力和负荷不确定性导致系统优化控制结果可信度较低的问题,基于模型预测控制的滚动优化思想,提出包含长时间尺度滚动优化层和短时间尺度实时滚动调整层的多时间尺度双层滚动优化控制方法。其中,上层以系统运行经济性最优为目标,通过多步滚动求解制定长时间尺度调度计划;下层以跟踪和修正上层调度计划为目标,并在短时间尺度滚动优化平滑功率波动的基础上,引入超级电容器,进一步应对风光和负荷短时间尺度的功率波动。分析结果表明,电转气和超级电容器在提高微能网消纳能力和平抑系统功率波动方面具有显著作用,同时双层滚动优化控制方法在保证微能网经济运行的前提下,能够有效应对不确定因素对系统优化控制的影响。
Multi-energy microgrid is one of the effective technological methods for multi-energy complementation. Taking the electricity-heat-gas multi-energy microgrid with power-to-gas and battery-supercapacitor hybrid energy storage system as the research object,as for the credibility of optimal control results of system is lower due to the uncertainties of wind power output,photovoltaic output and load demand,the multi-time-scale twolayer receding horizon optimal control method that contains long time-scale receding horizon optimization layer and short time-scale real-time receding horizon adjustment layer based on the receding horizon optimal idea of model predictive control is proposed. In this model,the upper layer takes the optimal operating economy of system as the objective,and the scheduling plan in long time-scale is formulated by multi-step receding horizon solution,while the lower layer takes tracing and correcting scheduling plan in upper layer as the objective,and the supercapacitor is introduced to further deal with the power fluctuations of wind power,photovoltaic and load demand in short time-scale based on smoothing the power fluctuation by receding horizon optimization in short time-scale. The analysis results show that the power-to-gas and supercapacitor have significant effects on increasing the absorption ability of multi-energy microgrid and smoothing the power fluctuation of system,meanwhile the two-layer receding horizon optimal control method can mitigate the effects of uncertain elements on optimal control of system under the premise of guaranteeing the economic operation of multi-energy microgrid.
作者
陈飞雄
林炜晖
邵振国
CHEN Feixiong;LIN Weihui;SHAO Zhenguo(College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China;Fujian Smart Electrical Engineering Technology Research Center,Fuzhou 350108,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2022年第5期23-31,共9页
Electric Power Automation Equipment
基金
国家自然科学基金青年项目(52107080)
福建省自然科学基金青年项目(2021J05135)
福州市科技创新平台项目(2020-PT-143)。
关键词
微能网
混合储能
电转气
滚动优化
多时间尺度
multi-energy microgrid
hybrid energy storage
power-to-gas
receding horizon optimization
multitime-scale
