Energy and Built Environment (Jul 2022)
Assessment of renewable energy: Status, challenges, COVID-19 impacts, opportunities, and sustainable energy solutions in Africa
Abstract
Today's more focus and efforts are being put by all the energy leaders towards power generation using renewable energy resources. Fortunately, these resources are becoming affordable to facilitate a swift shift towards green and clean energy. Possible strategic assets are an add-on for all the developing nations in terms of economy. The technological advancement and power market revolution resulting in an adequate reduction of renewable energy cost and affordability. This paper mainly focusing on Covid-19 impacts in the African energy sector. Also, analyzing recent developments in African renewable energy generation that holds the immense capacity for improvisation. This paper highlighting the recommendations in response to the COVID-19 pandemic for the African renewable energy sector. This paper is a result of rigorous analysis based on major issues governing sustainable solutions for Africa. This review paper comes up with effective conclusions to address the challenges in the current pandemic situation. In Africa abundance of resources is found with huge potential for the generation of power. But still, Africa undergoing a phase of serious crises because they are not able to tap its huge capital of renewable energies. There is a subsequent need for power grid restructuring, energy storage technologies, and parallel mitigation of environmental factors with seasonal variations. Proposed review analysis bringing a better opportunity for all issues towards sustainable solutions, that will ease the renewable energy status in Africa. It is observed that there is an inevitable need to focus on having strong government policy frameworks and proper regulations. The various recommendations are required to swing towards renewable energy development. Combined efforts are required in luring foreign investments and to address feasible issues like setting-up targets. This paper demonstrated a smart energy system using a proposed machine learning-based framework for enhancing the PV forecasting and up-gradation in available technologies.
