Globally, attention has majorly been focused on pollution and exhaustion of fossil fuels allied to the conventional energy sources while the non-conventional energy/renewable energy sources have always been considered clean and environmentally friendly. Of the two, the non-conventional (renewable) is being preferred because it is believed to be more environmentally friendly. Renewable Energy Technologies (RETs) especially Solar Photovoltaics have seen many plants being constructed to either supplement the grid or as alternatives for those far from the grid. Solar Photovoltaics plants occupy large tracts of land which would have been used for other economic activities for revenue generation such as agriculture, forestry or tourism in archaeological sites.  The negative impacts slow down the application of Solar PV , but a modelling tool that can easily and quantitively assess the impacts in monetary form would accelerate the Solar PV application. The work presents a developed modelling tool that is able to assess not only the techno-economic impacts but also the environmental impacts in monetary form, for one to be able to determine the viability of a plant in a given region. The results are compared with those of HOMER software.

The increasing number of electric vehicles (EVs) in today's transport sector is gradually leading to the phasing out of petroleum-based vehicles. However, the rapid deployment of EVs largely depends on the coordinated and fast expansion of EV charging stations (EVCSs). The integration of EVCSs in the modern distribution network characterized by increased penetration of randomly distributed photovoltaic (PV) systems is challenging as they can lead to excessive power losses and voltage deviations beyond acceptable limits. In this paper, a hybrid bacterial foraging optimization algorithm and particle swarm optimization (BFOA-PSO) technique is proposed for the optimal placement of EVCSs into the distribution network with high penetration of randomly distributed rooftop PV systems. The optimization problem is formulated as a multi-objective problem minimizing active and reactive power losses, average voltage deviation index, and maximizing voltage stability index. The IEEE 69 node distribution network is used as the case network. The simulation is done using MATLAB to integrate the EVCSs in five cases of randomly sized and placed PV systems in the distribution network. For all five cases, a minimal increase in power losses is recorded with minor changes in the voltage deviation and stability indices due to the placement of the EVCSs. But for the voltages of nodes 29 to 48, the other node voltages remain unchanged upon placement of the EVCSs. The largest increase in power losses due to the EVCSs being brought into the network with PVs was noticed in case 3 (from 142.27kW, and 62.90kVar to 147.65kW, and 72.48kVar).

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The world’s Sustainable Development Goals as clearly presented by the United Nations Department of economic and social affairs has zero hunger, and affordable clean energy. In the global struggle to meet both energy and sustainable agriculture, emerges the complex Energy-Water-Food (EWF) nexus. Kenya has initiated large-scale irrigation projects to ensure zero hunger. However, the energy required to run the pumps is very high, since diesel pumps and diesel generators are extensively used. This translates to high food production costs. In this research, optimized affordable clean energy systems required for irrigation were modeled and studied. Optimized hybrid wind and solar energy solutions for irrigation projects were presented. Five potential large-scale irrigation sites in Kenya were considered namely: Galana-Kulalu, Lotikipi, Rahole, Wei Wei, and Perkerra. The results showed that the energy requirement scenarios depended majorly on on-site conditions; crop water need cycles and rainfall patterns. Average Wind Speed to Global Horizontal Irradiance ratio influenced the structure of hybrid energy systems. Based on this ratio, longer cycle crops like sugarcane, maize, and cotton required systems with higher wind energy penetration compared to shorter cycle crops like radish and spinach. When this ratio changed in selected other irrigation sites, wind to solar power production was greater than one, and up to 500 times greater than one in sites with relatively stable sufficient wind like Lotikipi. Wind energy systems for areas with higher ratios contributed to smaller system structures as a result of a lower number of solar photovoltaic panels installed.

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