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Improved forecasting accuracy may make it easier to deal with energy imbalances between production and consumption. It also aids operations such as Demand Response (DR) management in Smart Grid architecture. This work aims to develop and test a new solution for EGF. It combines various methodologies running EGF tests on historical data from buildings. The experimentation yields different data resolutions (15\u00a0min, one hour, one day, etc.) while reporting accuracy errors. The optimal forecasting technique should be relevant to a variety of forecasting applications in a trial-and-error manner, while utilizing different forecasting strategies, ensemble approaches, and algorithms. 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