基于多场景模糊集和改进二阶锥方法的配电网优化调度

Optimal Dispatch Based on Multi-scene Ambiguity Set and Modified Second-order Cone Algorithm for Distribution Network

随着分布式光伏大量接入,储能、电动汽车、可平移的主动负荷等多种资源均参与到配电网调度之中,配电网亟需在消纳可再生能源的同时降低调度成本。针对光伏出力不确定性和复杂多资源接入下的配电网调度问题,提出了基于模糊集理论和改进二阶锥方法的日前-日内两阶段调度模型及求解算法。首先利用历史统计数据,基于event-wise模糊集理论构建了光伏出力不确定性调度模型,并进一步提出了考虑多类型主动负荷、电动汽车、储能在内的多种调节资源协同的日前-实时两阶段优化调度模型。日前调度采用改进的鲁棒随机优化方法求解,有效处理分布式光伏的不确定性影响,实现光伏消纳最大化的目标;实时调度则提出了二阶锥边界修正迭代算法,综合利用主动负荷响应、电动汽车多种手段追踪匹配光伏出力,实现以运行成本最小为目标的优化调度。最后,基于IEEE-33节点算例系统的仿真分析论证了所提方法的有效性。

With a large number of distributed photovoltaics integrated into the distribution system under the background of clean power transformation,various active load resources such as energy storage,translational load and electric vehicles are participating in the dispatch of the distribution network.Therefore,how to achieve the scheduling goal of minimum cost while consuming renewable energy has become a new challenge.To solve the distribution network dispatching problem with uncertain photovoltaic output and complex multi-resources,this paper proposes a two-stage scheduling model based on the ambiguity set and the modified second-order cone algorithm.Firstly,based on the event-wise ambiguity set theory and the historical data,the uncertainty model of photovoltaic output is constructed for scheduling optimization.Furthermore,a two-stage scheduling model considering the active load,electric vehicles and energy storage is proposed.The day-ahead scheduling model is solved by the robust stochastic optimization method,which effectively deals with the uncertainty of distributed photovoltaic and maximizes the photovoltaic consumption.For the real-time scheduling,this paper proposes a modified second-order cone algorithm and dispatches demand response and electric vehicles to track the PV output,which minimizes the operation cost.The effectiveness of the proposed method is demonstrated based on the IEEE-33 system.