Optimal Placement of Distributed Photovoltaic Systems and Electric Vehicle Charging Stations Using Metaheuristic Optimization Techniques

Abstract

In this study, the concept of symmetry is introduced by finding the optimal state of a power system. An electric vehicle type load is present, where the supply stores’ electrical energy causes an imbalance in the system. The optimal conditions are related by adjusting the voltage of the bus location. The key variables are the load voltage deviation (LVD), the variation of the load and the power, and the sizing of the distributed photovoltaic (DPV), which are added to the system for power stability. Here, a method to optimize the fast-charging stations (FCSs) and DPV is presented using an optimization technique comparison. The system tests the distribution line according to the bus grouping in the IEEE 33 bus system. This research presents a hypothesis to solve the problem of the voltage level in the system using metaheuristic algorithms: the cuckoo search algorithm (CSA), genetic algorithm (GA), and simulated annealing algorithm (SAA) are used to determine the optimal position for DPV deployment in the grid with the FCSs. The LVD, computation time, and total power loss for each iteration are compared. The voltage dependence power flow is applied using the backward/forward sweep method (BFS). The LVD is applied to define the objective function of the optimization techniques. The simulation results show that the SAA showed the lowest mean computation time, followed by the GA and the CSA. A possible location of the DPV is bus no. 6 for FCSs with high penetration levels, and the best FCS locations can be found with the GA, with the best percentage of best hit counter on buses no. 2, 3, 13, 14, 28, 15, and 27. Therefore, FCSs can be managed and handled in optimal conditions, and this work supports future FCS expansion.

Challenges and opportunities of FACTS devices interacting with electric vehicles in distribution networks: A technological review

“…We propose a dynamic charge coordination (DCC) method for EVs that is centered on the batteries state of charge in this study (SOC) [51]. The notion of symmetric is proposed in this work by using several approaches to identify the best condition of a power grid, including the cuckoo search algorithm (CSA), genetic algorithm (GA), and simulated annealing algorithm (SAA) [52]. Throughout this analysis, the best feasible earnings for electrical-grid suppliers were determined by changing the time and location of charging a statistical sample of EVs [53].…”

Efficient Integration of PV Sources in Distribution Networks to Reduce Annual Investment and Operating Costs Using the Modified Arithmetic Optimization Algorithm

“…To solve the MINLP model in Equations ( 1)- (11) in the current literature, the predominant alternative corresponds to the usage of embedded combinatorial optimization methods due to the large dimensions of the solution spaces in these MINLP models [26,27]. These methods allow dealing with the nonlinearities and non-convexities of the model via sequential programming [14].…”

Extended Stochastic Coati Optimizer

“…Metaheuristics are popular in various optimization studies, especially in the engineering field. In studies regarding electric vehicle (EV) systems, metaheuristics have been implemented to optimize the routing problem of the plugin hybrid electric vehicles (PHEV) [1], fast charging stations [2], distributed photovoltaic systems [3], and so on. In studies regarding manufacturing systems, metaheuristics have been implemented to optimize the coupling between integrated batch machines and direct shipping trucks [4], reducing risk in the spare part inventory system [5], and so on.…”