Forecast of solar power: a key to power management and environmental protection

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• 作者：Shravanth M. Vasisht ; Sheela K. Ramasesha
• 关键词：Prediction of yield ; Solar photovoltaic system ; Multivariate regression ; Power management
• 刊名：Clean Technologies and Environmental Policy
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：19
• 期：1
• 页码：279-286
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Sustainable Development; Industrial Chemistry/Chemical Engineering; Industrial and Production Engineering; Environmental Engineering/Biotechnology; Environmental Economics;
• 出版者：Springer Berlin Heidelberg
• ISSN：1618-9558
• 卷排序：19

文摘

Power management through the day and through different seasons in the year is a major challenge in cities around the world as the power generation is from a mix of resources. It is difficult to predict, a priori, the yield from renewable resources on a particular day to tune the fossil fuel fired generators leading to less control of atmospheric pollution from these plants. In this paper, we present a model to predict the yield from a solar photovoltaic (SPV) plant based on the weather forecast in the location. This model can be deployed in the management of distributed energy generation system consisting of SPV systems. The deviations of this model from the measured values are <15 % for most of the days. The methodology adopted in arriving at this model can be used in any location. This model is simple to use as it uses performance data from a SPV plant in a location and the weather forecast data available in the public domain. Hence, it would be a powerful tool for private solar power producers availing net-metering facility.