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Power to the city: Assessing the rooftop solar photovoltaic potential in multiple cities of Ecuador

  • Mariela Tapia ORCID logo EMAIL logo , Leonard Ramos , Detlev Heinemann and Edwin Zondervan
Published/Copyright: June 20, 2022
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Physical Sciences Reviews
From the journal Physical Sciences Reviews Volume 8 Issue 9

Abstract

Solar energy plays a crucial role in helping cities to decentralize energy production and thus decarbonize the energy mix. Reliable resource assessments are needed to support the deployment of solar power systems, especially in cities of developing countries where large solar potential remains untapped. The aim of this work is to assess the potential of rooftop solar photovoltaic (PV) in three populated cities in Ecuador’s mainland (Quito, Guayaquil and Cuenca) and in the Galapagos Islands. The assessment involves (i) the estimation of the available rooftop area based on geographic information system data, (ii) the calculation of energy yield based on hourly satellite-derived irradiance and meteorological data, and (iii) the economic feasibility assessment in terms of levelized cost of electricity (LCOE) compared to representative electricity tariffs. In addition, a sensitivity analysis is carried out to assess the variability of the estimated technical and economic potential with respect to changes in the input parameters. The results reveal a total available rooftop area of about 144 km2, mainly concentrated in urban parishes. The estimated energy yield is 16.94 ± 3.38 TWh/a, which could cover almost twice the annual energy consumption in 2019 of the study areas. The economic assessment shows that the LCOE ranges between 7.65 and 21.12 USD cents/kWh. However, the comparison of LCOE against representative residential tariff suggests that rooftop PV technology is not cost-competitive under most of the financial scenarios. The findings from this study will be of interest for local authorities and other decision makers to design policies and financing strategies to increase the penetration of rooftop PV and thus exploiting the large potential assessed in the study areas. The described methodology can be used for assessing the potential in other regions of Ecuador and thereby support the diversification and decarbonization of the energy mix in the country.

Keywords: Ecuador; geographic information systems; resource assessment; rooftop photovoltaic potential; urban solar potential
Corresponding author: Mariela Tapia, Resilient Energy Systems Research Group, University of Bremen, Enrique-Schmidt-Str. 7, 28359, Bremen, Germany, E-mail:

Acknowledgments

This manuscript is based on the master’s thesis by Leonard Ramos, conceptualized and supervised by Mariela Tapia. We thank the High-Performance Computing Team from the University of Oldenburg for their computing facilities. The first author dedicates this work in memory of Prof. Dr. Stefan Gößling-Reisemann.

  1. Author contributions: Mariela Tapia: Conceptualization, methodology, formal analysis, writing – original draft, writing – review and editing. Leonard Ramos: Methodology, software, visualization, formal analysis, validation, writing – original draft. Detlev Heinemann: writing – review and editing. Edwin Zondervan: Writing – review and editing.

  2. Research funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

  3. Conflict of interest statement: The authors declare no conflict of interest.

Appendix A
Table A1:

Main input parameters for the SAPM model of the selected PV module (SunPower SPR 220 BLK-U). Source: ref. [61].

Parameter Unit Value Parameter Unit Value
Vintage – 2008 I x0 – 5.4651
Material – Mono-c-Si I xx0 – 3.7619
Area m2 1.244 α Isc – 0.000179
Cells in series – 72 α Imp – −0.000435
I so0 A 5.468 β Voc0 – −0.145022
V oc0 V 47.832 β Vmp0 – −0.1492
I mp0 A 5.086 m βVoc0 – 0
V mp0 V 39.335 m βVmp0 – 0
Appendix B
Table B1:

Overview of main parameters for the economic assessment of rooftop PV systems used in recent studies regarding PV assessment in different regions of Ecuador.

Author, Year Region Capacity [kWp] Type CAPEX [USD/kWp] OPEX [USD/kWp] Discount rate [%] Lifetime [years] Reference
Benalcazar et al., 2020 Quito 3 Single system 1970 0.5–1% of CAPEX 7.00 25 [39]
5 1840
10 1780
Bermeo et al., 2021 Azogues 62.4 Single system 1110 – 7.15 20 [41]
Barragán et al., 2019 Cuenca 314,270 Aggregated at a city level 1433 17.2 10.00 25 [11]
Dávila and vallejo, 2019 Quito 557,100 Aggregated at a city level 750a – 10.71 25 [10]
Trejo, 2021 Ibarra 7.68 Single system 3042b 0 8.68 25 [42]

  1. aThis value was not considered for the selection because according to ref. [10] it represents an hypothetical scenario,bthis value was not considered for the selection because the calculations uses prices of flexible PV modules [42], which are more expensive compared to the modules used in our study.

Appendix C
Figure C.1: Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in urban and rural parishes of Quito disaggregated by consumption groups (residential, commercial, industrial and others). Source: Own calculations and consumption statistics in 2019 taken from ref. [45].
Figure C.1:

Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in urban and rural parishes of Quito disaggregated by consumption groups (residential, commercial, industrial and others).

Source: Own calculations and consumption statistics in 2019 taken from ref. [45].

Figure C.2: Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in urban and rural parishes of Guayaquil disaggregated by consumption groups (residential, commercial, industrial and others). Source: Own calculations and consumption statistics in 2019 taken from ref. [45].
Figure C.2:

Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in urban and rural parishes of Guayaquil disaggregated by consumption groups (residential, commercial, industrial and others).

Source: Own calculations and consumption statistics in 2019 taken from ref. [45].

Figure C.3: Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in urban and rural parishes of Cuenca disaggregated by consumption groups (residential, commercial, industrial and others). Source: Own calculations and consumption statistics in 2019 taken from ref. [45].
Figure C.3:

Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in urban and rural parishes of Cuenca disaggregated by consumption groups (residential, commercial, industrial and others).

Source: Own calculations and consumption statistics in 2019 taken from ref. [45].

Figure C.4: Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in parishes of the Galapagos Islands disaggregated by consumption groups (residential, commercial, industrial and others). Source: Own calculations and consumption statistics in 2019 taken from ref. [45].
Figure C.4:

Comparison of the estimated annual energy yield under the base case assumptions and electricity consumption in parishes of the Galapagos Islands disaggregated by consumption groups (residential, commercial, industrial and others).

Source: Own calculations and consumption statistics in 2019 taken from ref. [45].

Appendix D
Figure D.1: Long-term hourly averages of solar irradiance components from 1998 to 2018 in Quito. Data retrieved from the NSRDB.
Figure D.1: Long-term hourly averages of solar irradiance components from 1998 to 2018 in Quito. Data retrieved from the NSRDB.
Figure D.1:

Long-term hourly averages of solar irradiance components from 1998 to 2018 in Quito. Data retrieved from the NSRDB.

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Received: 2022-04-21
Accepted: 2022-05-17
Published Online: 2022-06-20

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/psr-2020-0061
Keywords for this article
Ecuador; geographic information systems; resource assessment; rooftop photovoltaic potential; urban solar potential

Articles in the same Issue

  1. Frontmatter
  2. Reviews
  3. Magnetic characterization of magnetoactive elastomers containing magnetic hard particles using first-order reversal curve analysis
  4. Microscopic understanding of particle-matrix interaction in magnetic hybrid materials by element-specific spectroscopy
  5. Biodeinking: an eco-friendly alternative for chemicals based recycled fiber processing
  6. Bio-based polyurethane aqueous dispersions
  7. Cellulose-based polymers
  8. Biodegradable shape-memory polymers and composites
  9. Natural substances in cancer—do they work?
  10. Personalized and targeted therapies
  11. Identification of potential histone deacetylase inhibitory biflavonoids from Garcinia kola (Guttiferae) using in silico protein-ligand interaction
  12. Chemical computational approaches for optimization of effective surfactants in enhanced oil recovery
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  15. Occurrence, fate, and toxicity of emerging contaminants in a diverse ecosystem
  16. Updates on the versatile quinoline heterocycles as anticancer agents
  17. Trends in microbial degradation and bioremediation of emerging contaminants
  18. Power to the city: Assessing the rooftop solar photovoltaic potential in multiple cities of Ecuador
  19. Phytoremediation as an effective tool to handle emerging contaminants
  20. Recent advances and prospects for industrial waste management and product recovery for environmental appliances: a review
  21. Integrating multi-objective superstructure optimization and multi-criteria assessment: a novel methodology for sustainable process design
  22. A conversation on the quartic equation of the secular determinant of methylenecyclopropene
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  26. Advances in heterocycles as DNA intercalating cancer drugs
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  29. Membrane technologies for sports supplementation
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