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A new research paper proposes an optimal planning technique to identify the locations and sizes of electric-vehicle (EV) charging stations with controlled charging and hybrid wind and PV systems in a multi-microgrid.
Power system designers and operators are increasingly focused on boosting the integration of large numbers of EVs and intermittent renewable energy resources (RERs), as part of a move toward modern microgrids. However, such microgrids will likely encounter serious challenges in terms of increased power losses, thermal loading, voltage deviation, and overall system costs.
Now, an international group of researchers from Egypt, the United Arab Emirates, and Finland has proposed an efficient planning approach, the “jellyfish search optimizer” (JSO) method, to solve the allocation problem of EV charging stations and RERs in multi-microgrids.
Different scenarios have been investigated, including the optimal integration of EV charging stations without RERs, the optimal integration of EV charging stations and RERs with a controlled charging strategy, and the optimal integration of EV charging stations and RERs with controlled charging and discharging strategies.
Superior results are obtained in the case of optimal integration EV charging stations and RERs with a controlled charging and discharging strategy, under which voltage deviation, energy not supplied, and total costs have been reduced considerably from the base case. The researchers also found that the proposed optimizer could reduce operating costs for RERs and conventional stations while increasing the capacity of charging stations. This makes the JSO approach superior for solving the allocation problem of EV charging stations and RERs compared to the other well-known algorithms, said the researchers.
They presented their findings in “Multi-objective optimal planning of EV charging stations and renewable energy resources for smart microgrids,” which was recently published in Energy Science and Engineering.