Energy cost optimization in distribution network considering hybrid electric vehicle and photovoltaic using modified whale optimization algorithm.

The economic emission dispatch problem is one of the most crucial problems for the future smart power network. The integration of renewable energy resources and the use of electric vehicles (EVs) are various techniques that have been suggested to deal with the increase in greenhouse gas emissions. However, to carefully examine various scenarios of integration of the above elements is important to reduce emission rates while considering economic constraints. In this research, the effectiveness of the use of photovoltaics (PVs) and EVs' discharging/charging behavior is investigated from various perspectives in a hybrid economic emission dispatch. Here, a multi-objective model includes the optimization of two objectives: cost and pollution is suggested. Based on a penalty factor, we convert the multi-objective function into a single objective. For solving this non-convex, nonlinear and on-smooth problem, a modified whale optimization algorithm (WOA) is exerted to gain the optimum results. The idea of two sub-modifications is derived from Lévy flight algorithm and the mutation operator of the genetic algorithm. The verification of the suggested model is performed by the IEEE 30-bus system with 6-units. The simulated results illustrate that the incorporation of PV along with EVs in economic dispatch problem can improve the pollution emission, the economic costs, and convergence rate, effectively. [ABSTRACT FROM AUTHOR]