Multiobjective Dynamic Optimal Power Flow Considering Fuzzy-Based Smart Utilization of Mobile Electric Vehicles


During this study, an efficient and good fuzzy logic controller (FLC) is intended for charging/discharging (C/D) nodes of plug-in electric vehicles (PEVs). The designed controller controls the number of power to be compensated by these nodes so as to meet the specified peak shaving and voltage flattening. The most focus of this work is to practically coordinate the mobile PEVs in a very multiobjective security constrained dynamic optimal power flow (OPF) downside that aims at simultaneously minimizing the operation price and emission over 24-h time horizons. Within the formulation of the matter, nonsmooth, nonconvex, and nonlinear natures of valve-point effects, multifuel options, prohibited zones, and ac power flow equations also are thought of. This advanced downside desires a strong, quick, and powerful optimization algorithm, which is able to extract the Pareto-optimal surface (POS). Hence, a brand new improved black hole (IBH) algorithm is proposed with a brand new formulation for updating particles to allow a larger exploration and acceptable exploitation of the search space. The proposed framework is applied on IEEE 118-bus check system incorporating several aggregated PEVs to indicate its potency and skill.

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