During the past century, energy consumption have increased drastically due to a wide variety of factors including both technological and population based. Therefore, increasing our energy efficiency is of great importance in order to achieve overall sustainability. Forecasting the building energy consumption is important for a wide variety of applications including planning, management, optimization, and conservation. Data driven models for energy forecasting have grown significantly within the past few decades due to their increased performance, robustness and ease of deployment. Amongst the many different types of models, among the most popular data driven approaches applied to date. This paper offers a review of Electricity consumption forecasting in office buildings an artificial intelligence approach for forecasting building energy use and demand, with a particular focus on reviewing the applications, data, forecasting models, and performance metrics used in model evaluations. Based on this review, existing research gaps are identified and presented.
BY Aditya Sonar | Vinita Galande "Review on Electricity Consumption Forecasting in Buildings: using Artificial Intelligence"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd31303.pdf
Paper Url :https://www.ijtsrd.com/management/management-development/31303/review-on-electricity-consumption-forecasting-in-buildings-using-artificial-intelligence/aditya-sonar
callforpaperbiologicalscience, biologicalsciencejournal
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