Summary
Charging electric vehicles (EVs) by the grid leads to unexpected spikes in load demand threatening the power system health. As EVs store energy, they can dispense power to meet peak load demands. This paper proposes a charging/discharging strategy to augment the utility of the EVs with a controlled schedule by considering an appropriate driving pattern. EVs are allowed to charge or discharge at the workplace or home which are connected to the same bus of a radial distribution system. Multiobjective multiverse optimization algorithm (MOMVO) is utilized to extract the best possible number of EVs and the bus at which they must be connected, not only to minimize the impact of EV charging/discharging on the grid but also to reduce the costs associated with the operation on behalf of both the EV owner and the utility company. The results obtained ensure both technical and economical appositeness of the proposed strategy.
With the advent of the smart grid paradigm many distribution system operators are making efforts to modernise their power grids through the optimal integration of renewable energy system (RES) such as photovoltaic/battery energy storage system (PV/BESS).This paper presents a novel mathematical model and solution approach for the optimal allocation of RES in radial distribution system (RDS). The optimal allocation of RES is formulated as a problem, and it is solved by multi-objective multi-course teaching learning based optimisation (MCTLBO). An efficient codification for the allocation of RES allows the multi-objective MCTLBO to find the optimal location, capacity and power dispatch of RESs for a given RESs for a given load level with time of use (TOU) pricing. The proposed methodology is tested on the 69-bus RDS. It was found that an appropriate allocation of RESs results techno-economic improvement for the system under study.
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