Nowadays, the installations of photovoltaics (PVs) in the smart grid have been growing dramatically because the price of PVs is falling drastically. Undoubtedly, this is a great achievement for the recent smart grid technology. However, the colossal penetration of PVs’ power at the day-time changes the load demand of thermal generations (TGs) of a smart grid which creates duck shape load curve called duck curve. In a duck curve, peak and off-peak gaps are very large which increase the start-up cost (SUC) of TGs because the units of TGs must be turned on and turned-off frequently. Therefore, it is very significant to run TGs units optimally. Only an optimization technique is not enough to bring a good solution. This research considers concentrated solar power (CSP) and pumped storage hydroelectricity (PSH) as the energy storages. Also, fuel cells (FCs) are considered as the controllable loads in the demand side’s smart houses. In addition, this paper considers the real-time price-based demand response. The optimal unit commitment (UC) of TGs, PSHs and other generators is introduced for saving the fuel cost and SUC of TGs. The optimal results of the proposed model are determined by using MATLAB® INTLINPROG optimization toolbox. To evaluate the effectiveness of the proposed method, simulation results have been compared with some other methods.

Following a rise in population, load demand is increasing even in the remote areas and islands of Bangladesh. Being an island that is also far from the mainland of Bangladesh, St. Martin’s is in need of electricity. As it has ample renewable energy resources, a renewable energy-based microgrid system seems to be the ultimate solution, considering the ever-increasing price of diesel fuel. This study proposes a microgrid system and tests its technical and economic feasibility in that area. All possible configurations have been simulated to try and find the optimal system for the island, which would be eco-friendly and economical with and without considering renewable energy options. The existing power supply configuration has also been compared to the best system after analyzing and investigating all technical and economic feasibility. Sensitivity and risk analysis between different cases provide added value to this study. The results show that the current diesel-based system is not viable for the island’s people, but rather a heavy burden to them due to the high cost of per unit electricity and the net present cost. In contrast, a PV /Wind/Diesel/Battery hybrid microgrid appeared to be the most feasible system. The proposed system is found to be around 1.5 times and 28% inexpensive considering the net present cost and cost of energy, respectively, with a high (56%) share of renewable energy which reduces 23% carbon dioxide.

The absence of electricity is among the gravest problems preventing a nation’s development. Hybrid renewable energy systems (HRES) play a vital role to reducing this issue. The major goal of this study is to use the non-dominated sorting genetic algorithm (NSGA)-II and hybrid optimization of multiple energy resources (HOMER) Pro Software to reduce the net present cost (NPC), cost of energy (COE), and CO₂ emissions of proposed power system. Five cases have been considered to understand the optimal HRES system for Kutubdia Island in Bangladesh and analyzed the technical viability and economic potential of this system. To demonstrate the efficacy of the suggested strategy, the best case outcomes from the two approaches are compared. The study’s optimal solution is also subjected to a sensitivity analysis to take into account fluctuations in the annual wind speed, solar radiation, and fuel costs. According to the data, the optimized PV/Wind/Battery/DG system (USD 711,943) has a lower NPC than the other cases. The NPC obtained by the NSGA-II technique is 2.69% lower than that of the HOMER-based system.

DC microgrids are revolutionizing energy systems by offering efficient, reliable, and sustainable solutions to modern power grid challenges. By directly integrating renewable energy sources and eliminating the inefficiencies of AC-DC conversion, these systems simplify energy distribution and enhance performance in critical applications such as data centers, electric vehicle charging, and telecommunications. This review paper comprehensively examines the design, implementation, and performance of DC microgrids in real-world settings. Key components, including distributed energy resources (DERs), energy storage systems (ESSs), and control strategies, are analyzed to highlight their roles in ensuring reliability and operational efficiency. This review also explores the challenges facing DC microgrids, such as stability issues, protection mechanisms, and high initial costs, while offering insights into advanced control strategies and modular designs to overcome these obstacles. Through an evaluation of global case studies, this article bridges the gap between theoretical research and practical deployment and also demonstrates how DC microgrids can enhance energy efficiency, support sustainable power generation, and provide resilience in various applications. The findings highlight the potential of DC microgrids as a cornerstone of future energy systems, enabling clean, reliable, and decentralized energy solutions.

Combating climate change issues resulting from excessive use of fossil fuels comes with huge initial costs, thereby posing difficult challenges for the least developed countries in Sub-Saharan Africa (SSA) to invest in renewable energy alternatives, especially with rapid industrialization. However, designing renewable energy systems usually hinges on different economic and environmental criteria. This paper used the Multi-Objective Particle Swarm Optimization (MOPSO) technique to optimally size ten grid-connected hybrid blocks selected amongst Photo-Voltaic (PV) panels, onshore wind turbines, biomass combustion plant using sugarcane bagasse, Battery Energy Storage System (BESS), and Diesel Generation (DG) system as backup power, to reduce the supply deficit in Sierra Leone. Resource assessment using well-known methods was done for PV, wind, and biomass for proposed plant sites in Kabala District in Northern and Kenema District in Southern Sierra Leone. Long term analysis was done for the ten hybrid blocks projected over 20 years whilst ensuring the following objectives: minimizing the Deficiency of Power Supply Probability (DPSP), Diesel Energy Fraction (DEF), Life Cycle Costs (LCC), and carbon dioxide (CO ${}_2$ ) emissions. Capacity factors of $27.41\%$ and $31.6\%$ obtained for PV and wind, respectively, indicate that Kabala district is the most feasible location for PV and wind farm installations. The optimum results obtained are compared across selected blocks for DPSP values of 0–50% to determine the most economical and environmentally friendly alternative that policy makers in Sierra Leone and the region could apply to similar cases.

The Distributed Generator types have different combinations of real and reactive power characteristics, which can affect the total power loss and the voltage support/control of the radial distribution networks (RDNs) in different ways. This paper investigates the impact of DG’s penetration level (PL) on the power loss and voltage profile of RDNs based on different DG types. The DG types are modeled depending on the real and reactive power they inject. The voltage profiles obtained under various circumstances were fairly compared using the voltage profile index (VPI), which assigns a single value to describe how well the voltages match the ideal voltage. Two novel effective power voltage stability indices were developed to select the most sensitive candidate buses for DG penetration. To assess the influence of the DG PL on the power loss and voltage profile, the sizes of the DG types were gradually raised on these candidate buses by 1% of the total load demand of the RDN. The method was applied to the IEEE 33-bus and 69-bus RDNs. A PL of 45–76% is achieved on the IEEE 33-bus and 48–55% penetration on the IEEE 69-bus without an increase in power loss. The VPI was improved with increasing PL of DG compared to the base case scenario.