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The increased diffusion of Photovoltaic (PV) generation could be limited by the grid capacity to host the power input from PV systems, especially in mid-day hours on sunny days. This paper proposes a framework of analysis to determine the mitigation of the PV energy curtailment in the grid, based on a novel smart charging strategy for electric vehicles (EVs) that operate in the grid-to-vehicle mode. This framework adopts a combination of methods and techniques, with a clustering procedure to group the EV charging stations with some PV systems based on the electrical distance, a novel smart charging strategy for the EVs based on the definition of fuzzy weights, and the exploitation of the blockchain technology with a Proof-of-Authority consensus protocol to reinforce network security and achieve decentralization. The blockchain provides full traceability of EV charging operations and grid status monitoring during time. The proposed framework contains novel indicators of avoided PV power reduction and energy curtailment. To account for the EV-related uncertainty, these indicators are determined from a Monte Carlo-based assessment of the three-phase power flow results. The results are presented on a three-phase unbalanced 123-node system with given locations of PV systems and EV charging stations.
Saadatmandi et al. (Thu,) studied this question.