Renewable Energy Generation and Integration Sustainability Using Machine Learning

Abstract

newlineThe growing penetration of renewable energy sources (RESs) into the electricity power newlinegrid is profitable from a sustainable point of view and provides economic benefit for longterm newlineoperation. newlineNevertheless, newlinebalancing newlineproduction newlineand newlineconsumption newlineis newlineand newlinewill newlinealways newlinebe newline newlinea newlinecrucial newlinerequirement newlinefor newlinepower newlinesystem newlineoperation. newlineHowever, newlinethe newlinetrend newlinetowards newlineincreasing newline newlinerenewable newline newlineenergy penetration has raised concerns about the stability, reliability and newlinesecurity of future electricity grids. The clearest observation in this regard is the newlineintermittent nature of renewable generation sources, such as wind and solar generation. newlineMoreover, the location of renewable generation tends to be heavily defined by newlinemeteorological and geographical conditions. However, renewable sources of energy like newlinesolar and wind are extremely unpredictable, which can lead to a variation in the power newlinegrid electricity production. An inherent characteristic common to all renewable power newlineplants is that power generation is dependent on environmental parameters and thus cannot newlinebe fully controlled or planned for in advance. In a power grid, it is necessary to predict the newlineamount of power that will be generated in the future, including those from the renewable newlinesources, as fluctuations in capacity and/or quality can have negative impacts on the newlinephysical health of the entire grid as well as the quality of life of its users. Therefore, the newlineprediction of renewable energy production is important as it relies on several variables that newlinecannot be regulated by humans such as their environmental conditions. Predicting the newlineenergy generation and electricity consumption should help utilities improve planning newlinegeneration and demand side management, however this is not a trivial task as both newlinegeneration and consumption is highly irregular. This prediction protects the generation ofsecured power and enables the integration of renewable energy into electricity grids. newline newline