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Energies 2017, 10(11), 1765; doi:10.3390/en10111765

A Decision Support Tool for Building Integrated Renewable Energy Microgrids Connected to a Smart Grid

Department of Process, Energy and Transport Engineering, Cork Institute of Technology, Co. Cork T12 P928, Ireland
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Received: 11 August 2017 / Revised: 15 October 2017 / Accepted: 23 October 2017 / Published: 2 November 2017
(This article belongs to the Section Energy Sources)

Abstract

The objective of this study was to create a tool that will enable renewable energy microgrid (REμG) facility users to make informed decisions on the utilization of electrical power output from a building integrated REμG connected to a smart grid. A decision support tool for renewable energy microgrids (DSTREM) capable of predicting photovoltaic array and wind turbine power outputs was developed. The tool simulated users’ daily electricity consumption costs, avoided CO2 emissions and incurred monetary income relative to the usage of the building integrated REμG connected to the national electricity smart grid. DSTREM forecasted climate variables, which were used to predict REμG power output over a period of seven days. Control logic was used to prioritize supply of electricity to consumers from the renewable energy sources and the national smart grid. Across the evaluated REμG electricity supply options and during working days, electricity exported by the REμG to the national smart grid ranged from 0% to 61% of total daily generation. The results demonstrated that both monetary saving and CO2 offsets can be substantially improved through the application of DSTREM to a REμG connected to a building. View Full-Text
Keywords: renewable energy; microgrid; smart grid; localized weather forecasting; demand side management; electricity tariff; building energy renewable energy; microgrid; smart grid; localized weather forecasting; demand side management; electricity tariff; building energy
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Asaleye, D.A.; Breen, M.; Murphy, M.D. A Decision Support Tool for Building Integrated Renewable Energy Microgrids Connected to a Smart Grid. Energies 2017, 10, 1765.

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