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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Main Authors: David J. Wright, James Ashwell, Janice Ashworth, Sana Badruddin, Moheb Ghali, Cameron Robertson-Gillis
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Cleaner Engineering and Technology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666790820300392
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spelling 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
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