Widespread application of residential photovoltaic (PV) systems and electric vehicles (EVs) has led the distribution system operators (DSOs) to face new technical challenges such as overloading and significant voltage variations, especially on low voltage (LV) grids. This adverse effect may be mitigated by employing the aggregators as intermediary actors to coordinate the operation at the distribution level. Therefore, this paper proposes a centralised coordination strategy to mitigate both PV and EV impacts, such as voltage rising/dropping at noon or evening, respectively, by defining the optimal export limit of PV power and EVs charging among multiple aggregators at the DSO level. The latter is in charge to dictate the optimal aggregated signals to every aggregator by employing a mixed-integer quadratic programming (MIQP) approach. The aggregated PV power is evenly managed for each aggregator by weighting. Two convex optimisation models are defined to satisfy both power and voltage constraints of the LV network. Each proposed optimisation approach can be utilised when there is or no detailed information about the LV network topology. The concepts discussed in this paper are tested on a real low voltage network considering a critical penetration level of EVs and PVs.

住宅光伏（PV）系统和电动汽车（EV）的广泛应用使配电系统运营商（DSO）面临新的技术挑战，例如过载和明显的电压变化，特别是在低压（LV）电网上。通过将聚合器用作中介参与者来协调分配级别的操作，可以减轻这种不利影响。因此，本文提出了一种集中化的协调策略，以通过在DSO级别上定义多个聚合器之间的PV功率和EV充电的最佳出口限制来分别缓解中午或傍晚的电压上升/下降等对PV和EV的影响。后者负责通过采用混合整数二次规划（MIQP）方法，为每个聚合器指示最佳聚合信号。通过加权为每个聚合器平均管理聚合的PV功率。定义了两个凸优化模型，以满足LV网络的功率和电压约束。当没有或没有有关LV网络拓扑的详细信息时，可以利用每种建议的优化方法。考虑到EV和PV的临界渗透水平，本文讨论的概念在真实的低压网络上进行了测试。