Document Type


Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.


Environmental Engineering | Environmental Sciences | Natural Resource Economics | Natural Resources Management and Policy | Oil, Gas, and Energy | Operations Research, Systems Engineering and Industrial Engineering | Other Engineering | Other Operations Research, Systems Engineering and Industrial Engineering

CIT Disciplines

1.5 EARTH AND RELATED ENVIRONMENTAL SCIENCES; Environmental sciences; Climatic research; 2. ENGINEERING AND TECHNOLOGY; Automation and control systems; 2.7 ENVIRONMENTAL ENGINEERING

Publication Details



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.