Impact of tariff structure on the economics of behind-the-meter solar microgrids
Within a single jurisdiction, electricity regulators may set varying tariff structures depending on the type of customer, to recover the cost of generating and delivering electricity. From this cost perspective, the various tariff structures are similar to one another. This paper however, demonstrat...
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doaj-242df84e5f684f79a19796e3e628950c2021-07-01T04:35:54ZengElsevierCleaner Engineering and Technology2666-79082021-06-012100039Impact of tariff structure on the economics of behind-the-meter solar microgridsDavid J. Wright0James Ashwell1Janice Ashworth2Sana Badruddin3Moheb Ghali4Cameron Robertson-Gillis5Telfer School of Management, University of Ottawa, ON, K1N 6N5, Canada; Corresponding author.Department of Economics, University of Ottawa, ON, K1N 6N5, CanadaOttawa Renewable Energy Cooperative, Ottawa, ON, K1R 6S3, CanadaInstitute of the Environment, University of Ottawa, ON, K1N 6N5, CanadaTelfer School of Management, University of Ottawa, ON, K1N 6N5, CanadaTelfer School of Management, University of Ottawa, ON, K1N 6N5, CanadaWithin a single jurisdiction, electricity regulators may set varying tariff structures depending on the type of customer, to recover the cost of generating and delivering electricity. From this cost perspective, the various tariff structures are similar to one another. This paper however, demonstrates that the tariff structures are very different from the point of view of determining the economics of behind-the-meter solar microgrids. Based on empirical data for Ontario we analyse three tariff structures: time-of-use (ToU), customer peak demand charges (DC) and system-wide peak charges (PC). The operation of the microgrid is first optimized and then the internal rate of return (IRR) of the system over its lifetime is maximized by choosing the optimal battery size. This analysis is projected into the future for project start dates 2019–2025 and results in IRRs of 2.7%–7.7% (ToU, residential) 5.6%–13.4% (DC, day/evening use commercial building), 7.5%–17.6% (DC, day-use commercial building). The PC tariff structure was determined to be unsuited to a solar microgrid partly because trends in the system peak hours have resulted in 9.2% per year decline in solar energy yield since its introduction in 2010.http://www.sciencedirect.com/science/article/pii/S2666790820300392SolarMicrogridBehind-the-meterElectricity tariffEconomicsOptimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
David J. Wright James Ashwell Janice Ashworth Sana Badruddin Moheb Ghali Cameron Robertson-Gillis |
spellingShingle |
David J. Wright James Ashwell Janice Ashworth Sana Badruddin Moheb Ghali Cameron Robertson-Gillis Impact of tariff structure on the economics of behind-the-meter solar microgrids Cleaner Engineering and Technology Solar Microgrid Behind-the-meter Electricity tariff Economics Optimization |
author_facet |
David J. Wright James Ashwell Janice Ashworth Sana Badruddin Moheb Ghali Cameron Robertson-Gillis |
author_sort |
David J. Wright |
title |
Impact of tariff structure on the economics of behind-the-meter solar microgrids |
title_short |
Impact of tariff structure on the economics of behind-the-meter solar microgrids |
title_full |
Impact of tariff structure on the economics of behind-the-meter solar microgrids |
title_fullStr |
Impact of tariff structure on the economics of behind-the-meter solar microgrids |
title_full_unstemmed |
Impact of tariff structure on the economics of behind-the-meter solar microgrids |
title_sort |
impact of tariff structure on the economics of behind-the-meter solar microgrids |
publisher |
Elsevier |
series |
Cleaner Engineering and Technology |
issn |
2666-7908 |
publishDate |
2021-06-01 |
description |
Within a single jurisdiction, electricity regulators may set varying tariff structures depending on the type of customer, to recover the cost of generating and delivering electricity. From this cost perspective, the various tariff structures are similar to one another. This paper however, demonstrates that the tariff structures are very different from the point of view of determining the economics of behind-the-meter solar microgrids. Based on empirical data for Ontario we analyse three tariff structures: time-of-use (ToU), customer peak demand charges (DC) and system-wide peak charges (PC). The operation of the microgrid is first optimized and then the internal rate of return (IRR) of the system over its lifetime is maximized by choosing the optimal battery size. This analysis is projected into the future for project start dates 2019–2025 and results in IRRs of 2.7%–7.7% (ToU, residential) 5.6%–13.4% (DC, day/evening use commercial building), 7.5%–17.6% (DC, day-use commercial building). The PC tariff structure was determined to be unsuited to a solar microgrid partly because trends in the system peak hours have resulted in 9.2% per year decline in solar energy yield since its introduction in 2010. |
topic |
Solar Microgrid Behind-the-meter Electricity tariff Economics Optimization |
url |
http://www.sciencedirect.com/science/article/pii/S2666790820300392 |
work_keys_str_mv |
AT davidjwright impactoftariffstructureontheeconomicsofbehindthemetersolarmicrogrids AT jamesashwell impactoftariffstructureontheeconomicsofbehindthemetersolarmicrogrids AT janiceashworth impactoftariffstructureontheeconomicsofbehindthemetersolarmicrogrids AT sanabadruddin impactoftariffstructureontheeconomicsofbehindthemetersolarmicrogrids AT mohebghali impactoftariffstructureontheeconomicsofbehindthemetersolarmicrogrids AT cameronrobertsongillis impactoftariffstructureontheeconomicsofbehindthemetersolarmicrogrids |
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