In this work, the evaluation of the design and optimization of proposed offgrid hybrid microgrid systems for different load dispatch strategies is presented by assessing the component sizes, system responses and different cost analyses of the proposed system. This study optimizes the sizing of the Barishal and Chattogram (two popular divisions in Bangladesh) hybrid microgrid systems consisting of wind turbine, storage unit, solar PV, diesel generator and a load profile of 27.31 kW for five dispatch techniques: (i) generator order, (ii) cycle charging, (iii) load following, (iv) HOMER predictive dispatch and (v) combined dispatch strategy. The considered microgrids are optimized for the least CO ₂ gas emission, Net Present Cost, and Levelized Cost of Energy. The two microgrids are analyzed for the five dispatch techniques using HOMER software, and subsequently, the power system performance and feasibility study of the microgrids are performed in MATLAB Simulink. The results in this research provide a guideline to estimate different component sizes and probable costing for the optimal operation of the proposed microgrids under various load dispatch conditions. The simulation results suggest that ‘Load Following’ is the best dispatch strategy for the proposed microgrids having a stable power system response with the lowest net present cost, levelized cost of energy, operating cost, and CO ₂ emission rate. Additionally, the combined dispatch strategy is determined to be the worst dispatch technique for the proposed off-grid hybrid microgrid design having the maximum levelized cost of energy, net present cost, operating cost and CO ₂ emission.

Energy consumption is increasing rapidly; hence, the energy demand cannot be fulfilled using traditional power resources only. Power systems based on renewable energy, including solar and wind, are effective and friendly for the environment. Islanded hybrid microgrid systems (IHMS) are relatively new in this industry and combine two or more sustainable sources, such as wind turbines, solar photovoltaic (PV), and other renewable alternatives, ocean, wave, and geothermal energy, etc. While sustainable, long-lasting power sources are the best choice to satisfy the growing energy demands, they are still not yet ready to be used on a large scale due to their stochastic characteristics. Furthermore, integrating these sources into the existing energy system can cause high technical difficulties, due to the stochastic nature of solar and wind in the conventional grid system and common stand-alone framework. A review of research and applications of the effective hybridization of renewable energy sources is therefore essential to address those technical and economic issues and ensure system stability, reliability, and cost-effectiveness. This article discusses the challenges that might arise when a PV plant and a wind power station are combined to produce power for the conventional main grid or in a stand-alone system. In addition, this analysis provides light on optimization approaches for improving power quality and cost-effectiveness in a solar and wind integrated IHMS. Voltage fluctuation, frequency deviation, and the uncertain nature of solar irradiation and wind sources are significant challenges for both grid-connected and standalone hybrid systems. This study then provides an overview of the control strategies which might help enhance the integration of the IHMS in producing electricity for distribution to the grid-connected load and the islanded load. In this study, the possible issues that can hinder the smooth integration of these renewable sources have been discussed. Finally, this study discusses the recent platforms being used in IHMS as well as the potential of dispatch strategies on solar and wind-integrated IHMS.

Electricity has become a part and parcel of modern life. The world is constantly developing, and the electricity demand is inevitably increasing with it. It is a big challenge for the power generation organizations to cope up with this increasing demand. For a developing country like Bangladesh, this challenge is even bigger. Bangladesh has many remote areas which are deprived of grid connectivity. In this article, system design and performance evaluation are conducted on a solar battery‐based hybrid renewable energy system (HRES) with diesel backup for a school in a remote area located in the northern part of the country, where conventional power grid connectivity is not available. From field survey, a load demand of 10.468 kWh/day for a normal working day and a peak demand of 3.3 kW are considered in this work for the proposed site. For simulation purpose hybrid optimization model for electric renewable, very well‐known software is used. The solar radiation data required for the work are collected from NASA Surface meteorology and Solar Energy database. Analyzing the load requirements and metrological data a solar‐battery diesel generator‐based HRES is proposed for the school. From the analysis and simulation, the Net Present Cost (NPC) for the proposed system is found USD 6191 with a Cost of Energy (COE) of $0.125/kWh. Further, a comparative study is done and the proposed system can reduce the COE and Green House Gas (GHG) emission of about 29.85% and 69% respectively than the conventional power plants. Finally, a techno‐economic analysis is conducted with sensitivity analysis, time series analysis, and multiyear analysis to prove the rigidity of the proposed system.

This paper presents a performance evaluation of an off-grid PV-wind-biomass hybrid energy system for a remote area named Kuakata in Bangladesh considering dispatch strategy-based control, power system response, and reliability analysis-based stability and feasibility study. The simulation and optimization of operations of the system have been done by the HOMER software using the real-time field data of solar radiation, wind speed, and biomass of that particular area for ensuring economical and environmental feasibility offering the least net present cost (NPC), cost of energy (COE), and CO₂ emission. The result shows that NPC has been reduced by 88 percent, CO₂ emissions have been reduced by 99 percent, the operating cost has been lowered by 99 percent, and COE has been reduced by 92 percent than another available work. Besides, in comparison to traditional power sources, COE has been reduced by 40 percent, NPC has been lowered by 90 percent, and CO₂ emissions have been reduced by 99 percent. The proposed system has also been analyzed utilizing DIgSILENT PowerFactory software to find the power system responses, i.e., active, reactive powers, voltage, and frequency responses of the proposed microgrid in a per unit fashion on the occurrence of a three-phase fault. To establish the feasibility of the microgrid, a reliability study considering different reliability indices has also been done. The analyzed hybrid energy system might be applicable to other regions of the world where there are similar climatic conditions.

This paper depicts an approach with an artificial neural network (ANN) for classification and localization of faults on the power transmission line. A huge number of transmission and distribution lines are used for the transportation of electrical energy in the power system. Moreover, developing a completely reliable system is not possible within the economic and technical limitations. So, there always remains a probability of faults in the transmission lines. When occurs, it is aimed to locate and classify the fault to restore the sound condition of the transmission line. For analyzing the transmission line fault, this paper adopts the fault-tolerant neural network-based method as it can process incomplete and noisy data. This approach can deal with nonlinear problems and can carry out the prediction if trained. Feedforward neural networks along with the backpropagation algorithm are used each of the three phases of the transmission line for the fault localization process. The proposed method uses the instantaneous measure of the fault current to return the fault type and the distance from the experimental end. The modeling of the power system and the development of the neural network for this method have been conducted in the MATLAB/Simulink environment. The simulation results illustrated in this paper manifests that the proposed model is promising in performance.