考虑动态激励型需求响应的微电网两阶段优化调度

针对微电网中风电、光伏出力和负荷大小的不确定性,从日前和实时两个阶段出发,建立了微电网两阶段优化调度模型。日前调度阶段建立以微电网总运行成本最优的经济调度模型。实时调度阶段在日前调度优化结果的基础上,综合考虑实时优化调度各电源的出力调整顺序,提出了一种动态激励型需求响应参与的实时滚动优化策略。该策略的激励价格和用户参与容量随时间尺度前进呈现出动态变化,旨在利用价格引导用户提高需求响应的参与程度。通过算例表明,动态激励型需求响应相较于静态激励型需求响应不仅可以提升对日前联络线计划的跟踪效果,还能更好地消除微电网日前预测误差。该策略在显著提高用户收益的同时有效降低了系统运行成本,为市场化的微电网优化运行提供了参考。

Two-stage optimal dispatching for microgrid considering dynamic incentive-based demand response

There is uncertainty over the amount of wind power, photovoltaic output and load size in a microgrid. To tackle this, starting from the two stage of day-ahead and real-time, a two-stage optimal dispatching model of a microgrid is established. In the day-ahead dispatching stage, an economic dispatching model based on the optimal total operation cost of the microgrid is established. Based on the results of day ahead scheduling optimization, the real-time scheduling stage considers the output adjustment sequence of each power supply in real-time optimization scheduling, and proposes a real-time rolling optimization strategy with dynamic incentive demand response participation. The incentive price and user participation capacity of the strategy presents dynamic changes with a time scale moving forward, aiming to use price to guide users to increase their participation in demand response. A calculation example shows that dynamic incentive model demand response, compared with static incentive model demand response, can not only improve the tracking effect of the day-ahead tie line plan, but also better eliminate the day-ahead prediction error of the microgrid. It can significantly improve user income and effectively reduce the system operation cost. This provides a reference for the optimal operation of the market-oriented microgrid. This work is supported by the National Natural Science Foundation of China (No. 52077146).