Optimal real-time management of aggregated EVs and batteries for technical support of residential virtual power plants using a binary TSO algorithm

To reduce carbon emissions by domestic customers, especially in transport needs, the UK government offers incentives to them for using zero-emission vehicles such as electric vehicles (EVs). Moreover, it encourages them to install rooftop photovoltaics and batteries. However, the increasing number of domestic EV chargers involves a significant investment in distribution network reconfiguration. Therefore, to support voltage regulation at distribution nodes, this paper offers optimal real-time management of aggregated large-scale smart chargers of EVs and batteries using a residential virtual power plant (VPP). In addition, the VPP maximizes the number of serving chargers and ensures fair charging for all connected EVs. Firstly, this paper proposes a novel binary transient search optimization (BTSO) algorithm for finding the optimal high-dimensional binary variable (switching EV chargers ON or OFF). Secondly, this paper presents a modified IEEE 33-bus system that includes around 1000 houses, each with an EV, a rooftop photovoltaic system, a static battery system, and household appliances. After that, the proposed BTSO-VPP is applied to monitor the buses’ voltages in the modified IEEE 33-bus system and coordinate the charging demand of all connected EVs. The simulation results revealed that the BTSO-VPP maintained the buses’ voltages above 94% compared to seven algorithms. Furthermore, BTSO-VPP guaranteed fair charging to all EVs, with charging priority given to EVs with low energy.