Abstract
The accurate prediction of the solar energy that can be generated using the rooftops of buildings is an essential tool for many researchers, decision makers, and investors for creating sustainable cities and societies. This study is focused on the development of an automated method to extract the useable areas of rooftops and optimize the solar PV panel layout based on the given electricity loading of a building. In this context, the authors of this article developed two crucial methods. First, a special pixel-based rooftop recognition methodology was developed to analyze detailed and complex rooftop types while avoiding the challenges associated with the nature of the particular building rooftops. Second, a multi-objective enveloped min–max optimization algorithm was developed to maximize solar energy generation and minimize energy cost in terms of payback based on the marginal price signals. This optimization algorithm facilitates the optimal integration of three controlled variables—tilt angle, azimuth angle, and inter-row spacing—under a non-linear optimization space. The performance of proposed algorithms is demonstrated using three campus buildings at the University of Alberta, Edmonton, Alberta, Canada as case studies. It is shown that the proposed algorithms can be used to optimize PV panel distribution while effectively maintaining system constraints.
Highlights
Publisher’s Note: MDPI stays neutralConsidering the energy and environmental crisis in recent years, many countries around the world are racing to use different approaches to energy issues to save energy and reduce energy consumption, control supply and demand, and reduce their carbon footprints
When dealing with building energy consumption data, we needed to consider the cost of purchasing electric energy to calculate the cost of supplying electric energy imported from the grid
Based on the information provided by the Energy Management and Sustainable Operations (EMSO) of the University of Alberta, the purchasing price of electricity was assumed to be equal for all hours of the year to the average one, which was $0.1015/kWh
Summary
Publisher’s Note: MDPI stays neutralConsidering the energy and environmental crisis in recent years, many countries around the world are racing to use different approaches to energy issues (including the replacement of fossil fuels with renewable sources of energy) to save energy and reduce energy consumption, control supply and demand, and reduce their carbon footprints. As buildings are one of the leading energy consumers, solar photovoltaics (PV) are considered a key technology for climate change mitigation and clean energy generation that offer sustainable energy and emission savings. From 30% to 40% of the total energy consumed in North America is dedicated to buildings, and the building sector can contribute more than 30% of the total carbon dioxide emissions each year [1]. Building energy consumption is affected by many factors and characteristics of the building envelope, including the layout of the building rooftops, the scale of the building, and the regional climate [2]. A building’s rooftop layout is considered one of the most critical factors and an integral part of the building because its design determines the response of the building to external factors such as solar irradiance intensity and weather with regard to jurisdictional claims in published maps and institutional affiliations
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