摘要
针对未来电网发展趋势下电力供给侧与需求侧间形成的新型供需关系,分析了江苏电网大规模清洁能源高比例渗透、电动汽车快速增长和海量柔性微负荷在内的电力供需结构特征,建立了电源、电网、负荷间友好互动效益综合评估模型,基于各参与方整体收益分析,提出了适应新型电力供需的多元化友好互动体系,研究了友好互动体系功能架构,包括状态感知、数据处理、状态可见和协同优化。最后,介绍了江苏电网开展多元化友好互动实施模式、策略及应用体系研究和实践,为提升电网与用户间互动水平、电网消纳可再生能源和充电负荷的弹性互动能力起到了重要的支撑作用,实现了能源供需联动应用下的各方互动共赢。
Considering a new power supply-demand relationship for the future power grid, the power supply-demand structure of Jiangsu electric power grid was analyzed, which involved the high penetration of large-scale clean energy integration, the rapid growth of electric vehicles and mass flexible loads of micro-grid. For analyzing friendly interaction among the power supplies, power grid and loads, a comprehensive benefit assessment model was worked up. Based on the overall benefits of all participants using the benefit assessment model built before, it proposed a pluralistic and friendly interaction system adapted for new power supply and demand. The function architecture includes state awareness, data processing, state visibility and collaborative optimization. Finally, the work of study and practice of the pluralistic and friendly interaction system in Jiangsu power grid was introduced in the fields of implementation mode, interaction strategy and the system's application. This work plays an important role in the enhancement of the interaction between power grid and users, the flexible interactive capability of accommodating the electric power generated by renewable energy and the charging load, and reaches an interactive win-win situation for all parties under the application of energy supply-demand linkage.
作者
李作锋
黄奇峰
杨世海
陆子刚
LI Zuofeng HUANG Qifeng YANG Shihai LU Zigang(State Grid Jiangsu Electric Power Company, Nanjing 210024, China State Grid Key Laboratory of Electric Energy Metering, State Grid Jiangsu Electric Power Company Electric Power Research Institute, Nanjing 210019, China)
出处
《江苏电机工程》
2016年第5期1-5,27,共6页
Jiangsu Electrical Engineering
关键词
新型电力供需
海量微负荷
友好互动
效益评估
协同优化
new power supply and demand
mass micro-load
friendly interaction
benefit assessment
collaborative optimization