Energy efficiency projects involving solar water heating systems in homes of low-income families: Measurement and verification and stochastic modelling applied to prediction of electricity saving. Menita, B., Domingos, J., Domingues, E., Alves, A., Calixto, W., Faria, A., & Miguel, M. In 2016.
Energy efficiency projects involving solar water heating systems in homes of low-income families: Measurement and verification and stochastic modelling applied to prediction of electricity saving [link]Paper  doi  abstract   bibtex   
Solar water heating in homes of low-income families as Energy Efficiency Action enables energetic benefits from points of view of the consumer and the Brazilian electrical system, thereby reducing environmental impacts associated with generation, transmission and distribution of electricity. The purpose of the present study is to evaluate these gains through measurement and verification methodology adapted from the International Performance Measurement and Verification Protocol, from case studies involving Energy Efficiency Projects in the Goiás State, Brazil. This paper also presents the stochastic modelling for the generation of future scenarios of electricity saving resulted by these Energy Efficiency Projects. The model is developed by using the Geometric Brownian Motion Stochastic Process with Mean Reversion associated with the Monte Carlo simulation technique. Results show that the electricity saved from the replacement of electric showers by solar water heating systems in homes of low-income families has great potential to bring financial benefits to such families, and that the reduction in peak demand obtained from this Energy Efficiency Action is advantageous to the Brazilian electrical system. Results contemplate also the future scenarios of electricity saving and a sensitivity analysis in order to verify how values of some parameters influence on the results, once there is no historical data available for obtaining these values. © 2016 IEEE.
@inproceedings{menita_energy_2016,
	title = {Energy efficiency projects involving solar water heating systems in homes of low-income families: {Measurement} and verification and stochastic modelling applied to prediction of electricity saving},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988365237&doi=10.1109%2fEEEIC.2016.7555407&partnerID=40&md5=3fb5a363801613dea2e31cce9b78c8af},
	doi = {10.1109/EEEIC.2016.7555407},
	abstract = {Solar water heating in homes of low-income families as Energy Efficiency Action enables energetic benefits from points of view of the consumer and the Brazilian electrical system, thereby reducing environmental impacts associated with generation, transmission and distribution of electricity. The purpose of the present study is to evaluate these gains through measurement and verification methodology adapted from the International Performance Measurement and Verification Protocol, from case studies involving Energy Efficiency Projects in the Goiás State, Brazil. This paper also presents the stochastic modelling for the generation of future scenarios of electricity saving resulted by these Energy Efficiency Projects. The model is developed by using the Geometric Brownian Motion Stochastic Process with Mean Reversion associated with the Monte Carlo simulation technique. Results show that the electricity saved from the replacement of electric showers by solar water heating systems in homes of low-income families has great potential to bring financial benefits to such families, and that the reduction in peak demand obtained from this Energy Efficiency Action is advantageous to the Brazilian electrical system. Results contemplate also the future scenarios of electricity saving and a sensitivity analysis in order to verify how values of some parameters influence on the results, once there is no historical data available for obtaining these values. © 2016 IEEE.},
	author = {Menita, B.G. and Domingos, J.L. and Domingues, E.G. and Alves, A.J. and Calixto, W.P. and Faria, A.F.D. and Miguel, M.L.S.},
	year = {2016},
	keywords = {Monte Carlo simulation, energy efficiency, geometric brownian motion, performance measurement and verification, solar water heating}
}
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