Conventional vehicles, having internal combustion engines, use lead-acid batteries (LABs) for starting, lighting, and ignition purposes. However, because of new additional features (i.e., enhanced electronics and start/stop functionalities) in these vehicles, LABs undergo deep discharges due to frequent engine cranking, which in turn affect their lifespan. Therefore, this research study seeks to improve LABs’ performance in terms of meeting the required vehicle cold cranking current (CCC) and long lifespan. The performance improvement is achieved by hybridizing a lead-acid with a lithium-ion battery at a pack level using a fully active topology approach. This topology approach connects the individual energy storage systems to their bidirectional DC-DC converter for ease of control. Besides, a battery management strategy based on fuzzy logic and a triple-loop proportional-integral (PI) controller is implemented for these conversion systems to ensure effective current sharing between lead-acid and lithium-ion batteries. A fuzzy logic controller provides a percentage reference current needed from the battery and regulates the batteries’ state-of-charge (SoC) within the desired limits. A triple-loop controller monitors and limits the hybridized system’s current sharing and voltage within the required range during cycling. The hybridized system is developed and validated using Matlab/Simulink. The battery packs are developed using the battery manufacturers’ data sheets. The results of the research, compared with a single LAB, show that by controlling the current flow and maintaining the SoC within the desired limits, the hybrid energy storage system can meet the desired vehicle cold cranking current at a reduced weight. Furthermore, the lead-acid battery lifespan based on a fatigue cycle-model is improved from two years to 8.5 years, thus improving its performance in terms of long lifespan.

The increasing demand to reduce the high consumption of end-use energy in office buildings framed the objective of this work, which was to design an intelligent system management that could be utilized to minimize office buildings’ energy consumption from the national electricity grid. Heating, Ventilation and Air Conditioning (HVAC) and lighting are the two main consumers of electricity in office buildings. Advanced automation and control systems for buildings and their components have been developed by researchers to achieve low energy consumption in office buildings without considering integrating the load consumed and the Photovoltaic system (PV) input to the controller. This study investigated the use of PV to power the HVAC and lighting equipped with a suitable control strategy to improve energy saving within a building, especially in office buildings where there are reports of high misuse of electricity. The intelligent system was modelled using occupant activities, weather condition changes, load consumed and PV energy changes, as input to the control system of lighting and HVAC. The model was verified and tested using specialized simulation tools (Simulink®) and was subsequently used to investigate the impact of an integrated system on energy consumption, based on three scenarios. In addition, the direct impact on reduced energy cost was also analysed. The first scenario was tested in simulation of four offices building in a civil building in South Africa of a single occupant’s activities, weather conditions, temperature and the simulation resulted in savings of HVAC energy and lighting energy of 13% and 29%, respectively. In the second scenario, the four offices were tested in simulation due to the loads’ management plus temperature and occupancy and it resulted in a saving of 20% of HVAC energy and 29% of lighting electrical energy. The third scenario, which tested integrating PV energy (thus, the approach utilized) with the above-mentioned scenarios, resulted in, respectively, 64% and 73% of HVAC energy and lighting electrical energy saved. This saving was greater than that of the first two scenarios. The results of the system developed demonstrated that the loads’ control and the PV integration combined with the occupancy, weather and temperature control, could lead to a significant saving of energy within office buildings.

Modern vehicles have increased functioning necessities, including more energy/power, storage for recovering decelerating energy, start/stop criteria, etc. However, lead-acid batteries (LABs) possess a shorter lifetime than lithium-ion and supercapacitors energy storage systems. The use of LABs harms the operation of transport vehicles. Therefore, this research paper pursues to improve the operating performance of LABs in association with their lifetime. Integrated LAB and supercapacitor improve the battery lifetime and efficiently provide for transport vehicles’ operational requirements and implementation. The study adopts an active-parallel topology approach to hybridise LAB and supercapacitor. A fully active-parallel topology structure comprises two DC-to-DC conversion systems. LAB and supercapacitor are connected as inputs to these converters to allow effective and easy control of energy and power. A cascaded proportional integrate-derivative (PID) controller regulates the DC-to-DC converters to manage the charge/release of combined energy storage systems. The PID controls energy share between energy storage systems, hence assisting in enhancing LAB lifetime. The study presents two case studies, including the sole battery application using different capacities, and the second, by combining a battery with a supercapacitor of varying capacity sizes. A simulation software tool, Matlab/Simulink, is used to develop the model and validate the results of the system. The simulation outcomes show that the battery alone cannot serve the typical transport vehicle (TV) requirements. The battery and output voltage of the DC-to-DC conversion systems stabilises at 12 V, which ensures consistent DC bus link voltage. The energy storage (battery) state-of-charge (SoC) is reserved in the range of 90% to 96%, thus increasing its lifespan by 8200 cycles. The battery is kept at the desired voltage to supply all connected loads on the DC bus at rated device voltage. The fully active topology model for hybrid LAB and supercapacitor provides a complete degree of control for individual energy sources, thus allowing the energy storage systems to operate as they prefer.

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.

This paper examines different off-grid renewable energy-based electrification schemes for an informal settlement in Windhoek, Namibia. It presents a techno-economic comparison between the deployment of solar home systems to each residence and the supplying power from either a centralized roof-mounted or ground-mounted hybrid microgrid. The objective is to find a feasible energy system that satisfies technical and user constraints at a minimum levelized cost of energy (LCOE) and net present cost (NPC). Sensitivity analyses are performed on the ground-mounted microgrid to evaluate the impact of varying diesel fuel price, load demand, and solar photovoltaic module cost on system costs. HOMER Pro software is used for system sizing and optimization. The results show that a hybrid system comprising a solar photovoltaic, a diesel generator, and batteries offers the lowest NPC and LCOE for both electrification schemes. The LCOE for the smallest residential load of 1.7 kWh/day and the largest microgrid load of 5.5 MWh/day is USD 0.443/kWh and USD 0.380/kWh, respectively. Respective NPCs are USD 4738 and USD 90.8 million. A sensitivity analysis reveals that variation in the fuel price and load demand changes linearly with system costs and capacities. However, reducing the PV module price in an energy system that includes wind and diesel power sources does not offer significant benefits. Furthermore, deploying an energy system that relies on fossil fuels to each residence in an informal settlement is not environmentally responsible. Unintended negative environmental impacts may result from the mass and simultaneous use of diesel generators. Therefore, a microgrid is recommended for its ability to control the dispatch of diesel generation, and its scalability, reliability of supply, and property security. A roof-mounted microgrid can be considered for piloting due to its lower initial investment. The electricity tariff also needs to be subsidized to make it affordable to end-users. Equally, government and community involvement should be prioritized to achieve long-term economic sustainability of the microgrid.