Optimisation of energy management in commercial buildings with weather forecasting inputs: A review

Dimitris Lazos, Alistair B. Sproul and Merlinde Kay

Renewable and Sustainable Energy Reviews, 2014, vol. 39, issue C, 587-603

Abstract: Information about the patterns that govern the energy demand and onsite generation can generate significant savings in the range of 15–30% in most cases and thus is essential for the management of commercial building energy systems. Predominantly, heating and cooling in a building as well as the availability of solar and wind energy are directly affected by variables such as temperature, humidity and solar radiation. This makes energy management decision making and planning sensitive to the prevalent and future weather conditions. Research attempts are being made using a variety of statistical or physical algorithms to predict the evolution of the building load or generation in order to optimise the building energy management. The response of the building energy system to changes in weather conditions is inherently challenging to predict; nevertheless numerous methods in the literature describe and utilise weather predictions. Such methods are being reviewed in this study and their strengths, weaknesses and applications in commercial buildings at different prediction horizons are discussed. Furthermore, the importance of considering weather forecasting inputs in energy management systems is established by highlighting the dependencies of various building components on weather conditions. The issues of the difficulty in implementation of integrated weather forecasts at commercial building level and the potential added value through energy management optimisation are also addressed. Finally, a novel framework is proposed that utilises a range of weather variable predictions in order to optimise certain commercial building systems.

Keywords: Weather forecasting; Load forecasting; Distributed generation; Energy management; Commercial buildings (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

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DOI: 10.1016/j.rser.2014.07.053

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