In recent times, the limited availability of fossil fuels and growing concerns regarding the emission of greenhouse gases (GHGs) have directly impacted the shift from conventional automobiles to electric vehicles (EVs). Additionally, there have been notable advancements in new energy research, which have significantly improved the viability of EVs. Consequently, EVs have gained widespread recognition and have been rapidly adopted in many countries worldwide. However, the rapid growth of EVs has given rise to several challenges, such as insufficient charging infrastructure, unequal distribution, high costs, and a lack of charging stations, which have become increasingly significant. The limited availability of charging facilities is hindering the widespread adoption of EVs. However, as more people embrace EVs, there has been a growth in the installation of electric vehicle charging stations (EVCSs) in public locations. Recent research has focused on identifying the ideal locations for EVCSs in order to assist the electrification of transport systems and meet the growing demand for EVs. A well-developed EVCS infrastructure can help address some key issues facing EVs, such as pricing and range limitations. Researchers have used various methodologies, objective functions, and constraints to formulate the problem of identifying the best sites for EVCSs. Current research is focused on determining the best locations for EVCSs. This endeavor intends to ease the transition to electrified transport networks while also addressing the growing demand for EVs. This review article explores various optimization techniques to achieve optimal solutions while considering the impact of EV charging load on the distribution system (DS), environmental implications, and economic impact. The research used a standard IEEE 33-bus radial distribution system (RDS) with a full variety of potential energy sources to improve understanding of the subject. The use of the bald eagle search algorithm (BESA) and cuckoo search algorithm (CSA) aided in the best identification of energy source locations and their relative capacities. In addition, the examination of EV charging techniques, including both the traditional charging technique (TCT) and the innovative charging technique (ICT), is being undertaken to assess the effectiveness of these approaches. The study included ten separate scenarios, each of which was thoroughly evaluated to demonstrate the individual and synergistic usefulness of various energy sources in mitigating the effects of EV charging on the DS. The collected data from the empirical inquiry was aggregated and thoroughly analyzed.

This paper proposes a new method of scheduling for optimal placement and sizing of Distribution STATic COMpensator in the radial distribution networks to minimize the power loss. In the proposed method Voltage Stability Index is used to search the optimal placement for installation of DSTATCOM. Optimal size of DSTATCOM is found by using bat algorithm. The feeder loads are varied by linearly from light load to peak load with a step size of 1%. In each load step, the optimal placement and sizing for DSTATCOM are calculated. By using the Curve Fitting Technique, the optimal sizing for DSTATCOM per load level is formulated in the form of generalized equation. The proposed approach will help the Distribution Network Operators to select the DSTATCOM size according to the load changes. To check the feasibility of the proposed method, system has been tested on two standard buses such as IEEE 33 and 69 bus radial distribution systems

In this literature, a new automated control strategy has been developed to manage the power supply from the wind power generation system to the load. The main objective of this research work is to develop a fuzzy logic–based pitch angle control and to develop a static transfer switch to make power balance between the wind power generation system and the loads. The power management control system is a progression of logic expressions, designed based on generating power and load power requirement. The outcome of this work targets at an improved power production, active and reactive power compensation and ensures system load constraints. To validate the proposed control strategy, a detailed simulation study is carried out on a 9-MW wind farm simulation simulated in MATLAB/Simulink environment.

This paper investigates a new approach to find the optimal location and sizing of Distribution STATic COMpensator (DSTATCOM) with an objective function of minimizing the total network power losses. Harmony search algorithm is used to find the optimal location and sizing of DSTATCOM. The proposed work is tested on standard IEEE 33-bus radial distribution systems. The obtained result shows that optimal placement and sizing of DSTATCOM in the radial distribution network effectively reduces the total power losses of the system

In this paper, a new approach to determine the optimal location and sizing of capacitor is being analyzed and the objective function is formulated to minimize power losses and voltage profile of the system subjected to equality and inequality constraints. Voltage stability index (VSI) is implemented to pre-determine the optimal location of capacitor. The newly developed Cuckoo Search Algorithm (CSA) is proposed to determine the optimal size of the capacitor. To check the feasibility of the proposed method, it is tested on IEEE 34-bus and 69-bus radial distribution system with different load factors. The simulated results demonstrate well the performance and effectiveness of the proposed method

This article proposes a new approach based on a bio-inspired Cuckoo Search Algorithm (CSA) that can significantly envisage with several issues for optimal allocation of distribution static compensator (DSTATCOM) in Radial Distribution System (RDS). In the proposed method, optimal locations of the DSTATCOM are calculated by using the Loss Sensitivity Factor (LSF). The optimal size of the DSTATCOM is simulated by using the newly developed CSA. In the proposed method, load flow calculations are performed by using a fast and efficient backward/forward sweep algorithm. Here, the mathematically formed objective function of the proposed method is to reduce the total system power losses. Standard 33-bus and 69-bus systems have been used to show the effectiveness of the proposed CSA-based optimization method in the RDS with different load models. The simulated results confirm that the optimal allocation of DSTATCOM plays a significant role in power loss minimization and enhanced voltage profile. The placement of DSTATCOM in RDS also plan an important role for minimizing uncertainties in the distribution level. The proposed method encourages one to use renewable-based resources, which results in affordable and clean energy.