As technology advances and distributed energy resources (DERs) become more common, electrical microgrids (MGs) will play an increasingly important role in future distribution grids. Radial distribution systems (RDS) are prone to problems, particularly after major natural disasters. To assess RDS resilience, a comprehensive approach is required. This paper proposes a novel approach that combines MGs and DERs with line hardening approaches to improve resilience under harsh operating conditions. It specifically integrates battery electric vehicles (BEVs), solar photovoltaic distributed generation (PV-DG), and battery energy storage systems (BESS) into a single IEEE 12-bus RDS. The goal is to improve the mentioned resilience metrics while also restoring all faulted loads. To optimize the system's objective, the group teaching optimization algorithm (GTOA) is used to determine the ideal PV-DG allocation.

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.

The rise in popularity of electric vehicles (EVs) is attributable to their economical maintenance, excellent performance, and environmentally-friendly nature due to zero carbon emissions. Nevertheless, the increased utilization of EVs poses challenges for the distribution system’s efficiency. The strategic placement of electric vehicle charging stations (EVCS) is crucial in maintaining the reliability of the radial distribution system (RDS). The improper allocation of EVCS can result in degradation and affect the distribution system. To overcome this issue, a potential solution involves integrating the charging stations with the RDS by utilizing distribution static compensators (DSTATCOMs) and distributed generation (DG) to mitigate the adverse effects of EVCS on the RDS. The appropriate sizing of DG/DSTATCOM depends on variations in load stages, as it impacts the stability of the RDS. Additionally, the uncertainty of distribution loads can lead to an underestimation of power within the system, posing a primary challenge. In this proposed work, two studies were examined: (i) DG and DSTATCOM allocation considering load uncertainty without EVCS impact, and (ii) DG and DSTATCOM allocation considering load uncertainty with EVCS impact. To address this multi-objective problem, an objective function was developed to reduce real power loss while adhering to system equality and inequality constraints. To tackle the challenge, the researchers used the bald eagle search algorithm (BESA), a revolutionary metaheuristic optimization methodology. The efficacy of the proposed approach was validated using two test systems: a 34-bus system and a 118-bus system. The results obtained from these test cases demonstrate that the BESA-based solution is highly exact in reducing real power loss, increasing bus voltage, and enhancing system stability with a significantly high convergence rate. Hence, the proposed approach presents a promising solution for optimizing RDS with multiple objectives.

This paper mainly focuses on the controller of portable direct current to direct current (DC-DC) converter which may be simple, low cost and efficient. Nowadays, proportional integral (PI) controller and opto-isolator based circuits are used for switching control. The switching control through the controller makes the DC-DC converter into larger circuit and less efficient. This problem will be rectified using the Arduino Nano controller which is small and low cost-effective controller. It is useful for low and medium power applications like residential solar power system, electronic gadgets, and academic laboratories. Arduino Nano-based DC chopper has been developed, and the Proteus software used for simulation. The different topologies of DC choppers like buck, boost, and buck-boost converter have been designed with mathematical calculations and simulated.

Electrical microgrids (EMGs) are positioned to play an important role in the future distribution grid as technology advances and distributed energy resources (DERs) emerge. In the event of major natural disasters, the functioning capabilities of active distribution systems (DS) face ongoing problems. To assess the resilience of a distribution system, a thorough methodology must be established. This study proposes a methodology that demonstrates how the use of EMGs and DERs, in conjunction with line hardening, can improve resilience in extreme operating situations. The framework examines four separate scenarios, each with its own set of restoration procedures and critical loads. A combination of battery electric vehicles (BEVs), solar photovoltaic distributed generation (SPV-DG), battery energy storage systems (BESS), and distribution static compensators (DSTATCOMs) is being integrated into practical Indian distribution systems consisting of 28 and 52 buses to improve resilience. The goal is to improve the newly specified resilience indices and restore all of the loads that have been affected by the faults. The bald eagle search algorithm (BESA) is used to identify the appropriate allocation of SPV-DG and solve the objective function within the system. The results of our tests show that our proposed technique has the capacity to enhancement the resilience and successfully restore all damaged loads in a distribution system.

Because of the increasing growth of Electric Vehicle (EV) in India, more electricity is required to power such vehicles. It is also gaining popularity because of its low maintenance, improved performance, and zero carbon impact. As the usage of electric vehicles grows, the distribution system’s performance is impacted. As an outcome, the reliability of the distribution system (DS) is dependent on the position of the electric vehicle charging station (EVCS). The fundamental difficulty is the deterioration of the DS due to an incorrect EVCS location. The DS is linked to the charging station and works with the distribution static compensator (DSTATCOM) to minimize the impact of the EVCS. A new nature-inspired Bald Eagle Search Algorithm (BESA) based optimization technique was utilized to find the optimal allocation of DSTATCOM and EVCS in the DS. The proposed strategy for mitigating the real power loss has been tested on practical Indian 28-bus and 108-bus distribution networks. Power loss reduction optimizes the system’s net savings, voltage stability, and bus voltage. The test case findings show that the BESA-based optimization is more accurate regarding power loss mitigation, bus voltage enhancement, and annual net saving improvement than the BA-based optimization in the DS.

The green-house gas emission from the vehicles’ using fuel is of great concern and it led to the development of electric vehicle. But, as it is battery powered, the charging technologies and the schedule of charging should be properly investigated. In this paper, the charging of the electric vehicle is developed in two ways by using solar power and wireless charging from the Grid. The whole paper is divided into three sections. In the first section, a manual cycle is converted into electric vehicle using the necessary components. In the second section, the simulation of EV is developed using MATLAB Simulink model. The third section deals with the implementation of real-time model of EV. The implemented charging technologies will be carried out for three scenarios based on different time interval.

This paper examines another way to deal with track down the ideal site and sizing of DSTATCOM with a target capacity of expanding the voltage stability. Voltage stability Index (VSI) and Fruit Fly Search (FFA) Algorithm is utilized to track down the ideal area and measuring of DSTATCOM. Present approach is tried on IEEE 33 standard test system. The acquired outcome shows that ideal arrangement and estimating of DSTATCOM in the spiral dissemination network adequately lessens the all out power misfortunes of the framework.

Solar energy has become one of the most significant renewable energy options, Because of the decline in fossil fuels. Conversion of Solar energy into Electric energy has been harvested through DC-DC Converters and stored in Batteries. A “Smart Multiport Bidirectional non isolated DC-DC Converter for PV-Battery Systems” has been proposed in this paper. One port is for unidirectional traffic, while the other is for bidirectional traffic. Previously, a SISO (single input single output) power flow system used, which resulted in power quality problems that were beyond the PV converters settings. In order to resolve the power quality problem and provide continuous supply, it has been changed into a multiport device with the use of LES (Local energy storage). High reliability, high power density, and fewer conversion stages are the advantages of this modified technique. A simulation work performed for all modes of proposed converter for low voltage levels. Simulation result ensures the satisfactory performance of new converter. IOT is introduced in this proposed converter to maintain a continuous power flow. So that the entire system can be monitored and regulated. IOT is an external module that can be added or removed based on specifications that vary by venue, context, and other factors. A new model has been implemented using 24V solar PV panel, 12V battery and the bidirectional power flow achieved when solar energy fails to charge LES.

The abrupt rise in energy demand has led many growing nations to a power shortage. Hence, most rural areas in those nations are purely dependent on off-grid based power generation for their electrification. Off-grid-based power generation has sounded loud recently for their higher advantage in generating independent energy and cost-cutting solutions in rural electrification. In this paper, a comprehensive review delivers enhanced hybrid electrification in rural areas using renewable energy sources like hydro, wind, biogas, and biomass. The review also highlights sustainable and reliable hybrid renewable power generation system operation. Furthermore, this review article focuses on the optimal integration of renewable energy systems used for rural electrification, factors influencing a particular hybrid energy system selection, and the energy management strategy followed to facilitate researchers' research work. The researchers and stakeholders can utilize the outcomes of this study for swotting rural electricity pricing and policymaking.

The growing energy needs of 21st century have made the electricity grid more intelligent that can accomplish the demand. Smart energy management system needs to be integrated for efficient usage of energy. Internet of things is a megatrend of 21st century which can be effectively used for smart energy management system. The proposed system in this paper deals with cost effective smart load management for off-grid renewable energy sources. A prototype model is developed with solar panel, battery storage system, controllable loads and the smart load management is developed using microcontroller,4-channel relay module. The whole system is supervised using mobile with cloud storage app, Cayenne.

Battery management system plays an important role for modern battery-powered application such as Electric vehicles, portable electronic equipment and storage for renewable energy sources.It also increases the life-cycle of the battery, battery state and efficiency.Monitoring the state of charge of the battery is a crucial factor for battery management system.This paper deals with monitoring the state of charge of the battery along with temperature, current for Solar panel fitted with battery for residential application.Microcontroller is used for controlling purpose, analog sensors are used for sensing the parameters of voltage, current.The information of the battery is given with tabular form and shown in photograph.Battery parameters are displayed with the LCD screen.

Solar PV application is one of the leading solution in Renewable energy resources to satisfy power demand in energy industry. This research explores the online solar-Off grid power generation to server room of Computer Centre-I in an educational institution located near Cauvery delta region of Tamilnadu state in India. Solar PV panels along with the combiner box, MPPT Charge controller have been integrated with existing Uninterruptible Power Supply (UPS)-Battery pair. IOKVA of existing UPS-Battery powered from 9KW PV panels. Design, Performance and cost-benefit analysis of the whole system addressed with necessary future development.

Penetration of renewable energy sources has become an important matter due to rapid diminishing of conventional sources. Environmental pollution is also one of the main reasons in many countries. Virtual power plant (VPP) is a new technology which can manage the uncertainties caused by the renewable sources in demand side. VPP will aggregate the capacities of distributed energy resources (DERs) to create a single operating profile. Each DER will get visibility and controllability in the electricity market with this technique. In this paper, virtual power plant concept is demonstrated and the bidding strategies of energy among VPP and grid are developed for four different scenarios. A model is considered for the analysis of the system which consists of two solar power generation units and one wind power generation unit with energy storage system (ESS).

A high-gain non-isolated DC–DC PWM boost converter of two-level output voltage is discussed. In traditional step-up converter like, transformerless converters using switched capacitor, switched inductor, etc., maximum voltage gain is not satisfied our expectations because of maximum duty cycle (i.e. duty cycle closely one). Switches are facing severe problem in reverse recovery, high on-state losses, high electromagnetic interference (EMI), etc., when they are operating at extreme duty cycle. Generally, grids are interconnected with AC supply from various power stations. But increase in solar energy demands the use of grid for DC supply. Nowadays, DC micro-grid is having higher attention due to rise in load requirement in DC and betterment in power quality. Based on power rating, these DC loads need various output voltages. In DC micro-grid, photovoltaic source (PV) is the best source of energy. The purpose of non-isolated converters is low cost and high reliability. A high-gain converter with PWM control is an essential for DC micro-grid due to very minimum voltage from photovoltaic. To achieve this, a boost DC–DC PWM converter configuration is discussed that exhibits a maximum voltage gain behaviour and the switches are controlled by a single control signal, which simplifies the operation. The new converter functions in uninterrupted output current mode.

This paper implements a new Reptile Search Algorithm to determine the optimal allocation of distributed generation in a radial distribution system. The main objective of this work is to minimize the total power loss of the system while satisfying the operating constraints. The proposed method is tested on the 69-bus radial distribution system. The performance analysis of multiple distributed generation placement has been analyzed in detail. The simulated results are compared with other existing works. It is found that the performance of the proposed method gives encouraging results.

Nowadays, losses in power system increases the energy demand and the number of consumers and proper allocation of capacitors bank around the distributed system. Form capacitor bank, it decreases the losses due to bus voltage and unsuitable situation of capacitor bank which clues to mitigate the advantages of system. The ultimate purpose of the present approach is to mitigate the losses of the RDS satisfying the all conditions. To pre-identity the appropriate sitting of the capacitor bank with the PLI. In this paper CSA is to find the placement of capacitor bank and optimal location of capacitor bank of typical RDS. The present approach for mitigation of losses has been implemented on IEEE 34 bus RDS. The present approach is based upon the CSA. This result obtained are related to the existing algorithm to demonstrate the efficiency and performance of the present algorithm.