This study aims to assess the potential of coupling solar PV power plants with Battery energy storage System (BESS) to curtail load-shedding and provide a stable and reliable baseload power generation in Zimbabwe. Data from geographical surveys, power plant proposals, and investment information from related sources were reviewed and applied accordingly. Areas considered to be of good potential to employ the use of BESS were identified considering such factors as feasibility of PV plants, proximity to transmission lines, the size of a town or neighborhood, and energy demands for BESS Return On Investment (ROI) calculations. Previous studies have proven that 10% of the suitable land for PV systems has the capability to generate thirty times the current power demand of the nation operating even with the least efficiency. In recent years, coupling renewable energy sources with a suitable energy storage system yielded improved performances, giving consumers a reliable, stable, and predictable grid. BESS technologies on the utility scale have improved in recent years, giving more options with improved safety, and decreasing the purchase costs, too.

This study presents modeling and simulation of a stand-alone hybrid energy system for a base transceiverstation (BTS). The system is consisted of a wind and turbine photovoltaic (PV) panels as renewableresources, and also batteries to store excess energy in order to boost the system reliability. Two differenttypes of batteries are considered for storage purposes; lead-acid and vanadium redox-flow batteries (VRB)batteries. Most stand-alone energy systems for various applications take advantage of at least a singlestorage technology, generally lead-acid batteries. However, with recent advances in different Batterytechnologies, vanadium redox-flow batteries could be taken into account as reliable candidate. Thevanadium redox-flow Battery has a desirable prospect due to its extended life span and also the potentialfor separating and scaling up involved nominal power and nominal energy. The system is modelled andsimulated hourly (quasi-dynamically) in Matlab for an operational year. The model utilizes insolation,wind speed and air temperature data. The system performance has been assessed with a mobile telephoneBase Transceiver Stations (BTS) as the case study. Simulations results have shown that the suggestedmodel can be used to study the effect of the altering weather conditions on each charge/discharge cyclesand batteries voltage. Finally the proposed model yields the optimal Battery network design for a varietyof applications.

Among various storage technologies used for the energy storage systems, the supercapacitors, the Pb-acid-Batteries (PABs) and the lithium-Batteries (LBs) are widely used for microgrid applications. The supercapacitors with high-power density are suitable for fast power regulations; conversely, the PABs have high-energy density, which makes them suitable for long-term energy management. Since the PABs and the supercapacitor can complement each other deficiencies, their combination as a hybrid energy storage system is used. However, the LB has both high-energy and high-power densities. Therefore, an LB energy storage System (LBESS) can similarly function like a Pb-acid Battery-supercapacitor-hybrid-ESS (PSHESS). This paper tends to determine which one is technically and economically more suitable for applications in islanded microgrids. For this purpose, a frequency control and energy management scheme is proposed. It maintains the balance between demand and supply, and also keeps the microgrid frequency within safe operational limits using the least needed sizes for the energy storage systems. Simulation results reveal the costs of LIBESS and PSHESS would be $140325.93 and $209408.37, respectively, which shows that the cost of the PSHESS is $69082.44 or almost 49.2 % more than the cost of the LIBESS. This indicates that the LBESS is more cost-effective than the PSHESS.

This research paper comprehensively analyzes the advantages of integrating energy storage resources into an energy management system, highlighting how it can significantly improve profitability and overall energy quality. One of the key benefits is the ability to regulate charging and discharging cycles, which helps prolong the service life of storage devices. In addition, the study delves into the influence of consumer behavior and the Internet of Things (IoT) on energy storage charge management, identifying important insights for enhancing efficiency. The optimization process for this investigation utilizes the YALMIP and MOSEK toolboxes, ensuring rigorous and accurate results. The experimentation is conducted on an IEEE standard 33-bus network, offering a robust foundation for real-world applications. The research outcomes demonstrate remarkable enhancements in both technical and economic parameters, including energy storage resources. By harnessing the potential of energy storage, businesses and industries can achieve greater cost savings and operational efficiencies. Furthermore, the paper considers the longevity of storage resources, comprehensively comparing results. This factor is crucial in determining such systems' long-term benefits and sustainability. In conclusion, the study underscores the immense advantages that IoT technology brings to energy management and its positive impact on consumers. By leveraging IoT capabilities and integrating energy storage resources intelligently, optimal consumption management can be achieved, leading to a more sustainable and efficient energy ecosystem.

Economic dispatch (ED) is one of the key problem in power systems. ED tends to minimize the fuel/operating cost by optimal sizing of conventional generators (CG). Greenhouse/toxic gas emission is one of the major problem associated with the CG. Emission dispatch (EMD) deals with the reduction of greenhouse/toxic gas emissions by the optimal output of generators. The multi-objective economic emission dispatch (MOEED) problem has been formulated by considering both fuel cost and emission objectives. The main objective is optimization of fuel cost and environmental emissions from the CG in a compromised way. In this paper, CONOPT solver in General Algebraic modeling system (GAMS) has been proposed to find the the optimal solutions for ED, EMD, and MOEED problems of a microgrid. The microgrid consists of a wind turbine generator (WTG), a photovoltaic (PV) module, three CGs, and a Battery energy storage system (BESS) option. The proposed algorithm has been implemented in four case studies, including all energy sources, without WTG, without PV module, and without renewable energy sources (RES). To establish the effectiveness of the proposed algorithm, it has been compared with various algorithms. The comparison result shows that proposed algorithm is more effective, novel, and powerful. Finally, result shows the effectiveness of proposed approach to optimize the objective function for all aforementioned case studies and the CONOPT solver in GAMS outperformed all the approaches in comparison. The impact of BESS on the operating/fuel cost of the microgrid has also been presented for ED. Paradigm is changing in terms of demand response in µG. Demand flexibility (DF) model has also been established with consumers demand variation in optimization process. Result with DF shows the reduction in cost and better management from demand side.