Reducing Carbon Footprint Using Renewable Energy, Distributed Generation and Smart Government Policies

With continued and increased global outcry to the insidious effects of continued exploitation of fossil fuels and gas flaringon the environment as evidenced by climate change, attention has in recent times be turned to alternative and more efficientmeans of energy generation that pose less threats or damage to the environment. Utilizing such alternative means of energygeneration has seen an increase in technological advancements as regards exploitation of such natural elements as sunlight,wind, tides, hydro etc. in meeting our varied energy demands. These alternative energy sources commonly referred to asrenewable energy sources (RES) now constitute the global trend as not only are they providing access to clean energy indistant and remote areas, but also redefining the way our electricity grid now works. With the enormous problems associatedwith centralized generation and transmission of electricity vis-à-vis line losses and system reliability, coupled with theinability of the grid to effectively cover every nook and cranny of the country, attention is being put on practical andeffective means and ways of integrating these RES into our electricity network. One of such means that have been evolved isDistributed Generation (DG) which seeks to decentralize electricity generation and displace demand by generating at loadcentres. Acting as stand-alone systems, their presence in Nigeria is gradually beginning to be felt. This paper seeks toexamine the impact of RES and DG in select cities around the world in addressing issues of poverty eradication, climatechange, transmission line losses etc., while also appraising the impact government policies have had in influencing theirgrowth. Existing policies on renewable energy and DG (if any) in Nigeria would be reviewed while solutions would also beproffered as Nigeria strives to meet the objectives of the Millennium Development Goals (MDGs), 2015, especially endingextreme hunger and poverty.Keywords: insidious, environment, climate change, renewable energy, distributed generation, policies, poverty, hunger

Demand Side Management potentials for mitigating energy poverty in South Africa

© 2017 Elsevier Ltd South Africa is severally posited to be Africa's most industrialized nation with an economy heavily reliant on energy. With depleted electricity reserve margin which led to massive load shedding and rationing of electricity in 2008, Eskom has stepped up the construction of additional power plants to cover for growing supply deficits. Emerging trends however favour Demand Side Management (DSM) initiatives as alternatives to building additional supply capacity due to environmental and economic constraints. This research evaluates the electricity per capita for 2007, 2011 and 2016 on provincial basis assuming 100% and 36.8% residential sector consumption of generated electricity to show declining electricity per capita values. A scenario simulation (for 100%, 50% and 30% household participation) of cloth washers and cloth dryers optimal dispatch is then modelled to show the enormous DSM potentials in terms of electricity cost reduction and supply flexibility. A modified genetic algorithm (MGA) is used in the dispatch of participating loads on the Medupi power plant which has been modelled to operate with carbon capture and sequestration (CCS) technology. DSM potentials of 6938.34 MW, 3469.18 MW and 2081.51 MW are computed for 100%, 50% and 30% household participation for cloth washers and cloth dryers

A critical overview of the (Im)practicability of solar radiation forecasting models

To size solar energy facilities, the availability of solar radiation data on a horizontal surface is inevitable. Based on the vast applications of energy from the sun in electricity generation, quality research has been dedicated to developing models capable of estimating solar radiation for various purposes. Although tremendous successes have been recorded while developing these models, some researchers have questioned the relevance of such models for practical applications. Aside from presenting an overview of existing solar radiation forecasting models, this study presents a perspective and critical discourse on the practicability or otherwise of solar irradiation prediction models available in the literature. The existing models are classified as satellite-driven models, regression models, statistical models, artificial intelligence-driven models, and hybrid solar irradiation forecast models. This study also presents research gaps that need to be examined in the future. Insights from the review reveal that although the generalization capabilities of solar radiation forecast models specifically for locations without measuring instruments have turned out to be an uphill task, some promising researches are being implemented and improved to bridge the gap of generalization of models. The subject discussed in this paper will be valuable to researchers, practitioners, funders, and policymakers interested in developing and utilizing these models to foster the growth of the solar energy industry