Assessment of Classical Demand Management Strategies and Batteries for Electric Vehicle Impact Mitigation in Distribution Networks

The rapid transition to electrical transportation has prompted researchers to analyse the impact of Electric Vehicles (EVs) on the electrical network and propose mitigating solutions. Among various solutions, traditional Time-of-Use (ToU) and Demand Response (DR) strategies are widely used by utilities for load management due to their effectiveness and ease of implementation. However, the performance of these strategies for managing EV loads in the networks currently operating at different load levels has not been thoroughly investigated in the literature. This study aims to address this gap by evaluating the performance efficacy of legacy charging strategies in managing EV load and mitigating their impact in a representative urban network. The findings of this analysis show that the ToU strategies are effective in managing the network demand by shifting between 50 to 90% of EV loads from peak hours to non-peak hours. However, the performance of these ToU strategies depends on the base loading of the network and requires controlled consumer participation rates to be effective, as more participation may worsen the impact. Additionally, the current body of literature does not address the necessary penetration levels of Battery Energy Storage System (BESS) and solar PV required to effectively manage EV demand at different penetration levels. This paper addresses this question by quantifying the capacity and penetration level needed for solar PV and BESS and by developing the BESS dispatch schedules to alleviate the impact of EVs at different penetration levels. The study reveals that the amount of solar PV and BESS required to shift EV load demand from peak hours to off-peak hours at their 100% penetration is relatively moderate, at below 40%. This estimate aligns with the growth projections for solar PV, BESS and EVs anticipated in many countries. The findings of this study aimed to serve as guidelines for stakeholders to understand the relative effectiveness of different strategies under different network conditions, and the need for their deployment at various levels of EV penetration.