Solar PV Penetration Scenarios for a University Campus in KSA
Abstract
:1. Introduction
2. Site Characteristics, Methodology, and Analytics
2.1. University of Jeddah Campus
2.2. Methodology Framework
- Input data
- Site location and weather data: Site location allows estimation of the solar resource such as the direct solar irradiance (DNI) and global horizontal irradiance (GHI). The weather data were from the weather station at King Abdulaziz University [10]. Data included ambient temperature, wind speed, and humidity.
- Campus electrical consumption: This was obtained from the smart meter at the JU campus in kW/half-hour.
- Data analyses
- Electrical load profile: Consumption data (1 B) only covered 3 months. The load profile was then built using a linear relationship to estimate the missing data. The full-year load profile (kW/half-hour) was established using the known ambient temperature obtained from the weather data in step (1 A) to forecast the electrical consumption through the linear relationship.
- Campus seasonality: The analysis covered here identified term dates and holiday intervals on campus to clarify campus electrical load behaviour. Building linear relationships between the ambient temperature and consumption for each interval (fall and spring terms, summer holiday, Eid holiday) resulted in a set of linear relationships that can be used to forecast the electrical consumption for each given interval in the campus.
- Load segregation: Using the cooling degree-days method to identify the cooling loads (AC loads) of the campus and the noncooling loads (non-AC loads). This resulted in a relationship between the monthly electrical consumption and the cooling degree-days per month, providing an indication of the air condition share of the consumption in the campus.
- Modelling and Analysis
- Evaluating electrical supply: This covered the business-as-usual (BAU) scenario and building more scenarios for the PV grid connected with different export tariff options, as well as an additional standalone PV battery combination scenario. All scenarios were set to fully supply the load (no short fall of supply is allowed).
- Economic assessment: The impact of implementing the different scenarios were evaluated based on total net present cost (NPC) and Levelized Cost of Energy (LCOE). The assessment was undertaken in Homer over the 25-year lifetime of the project. The grid tariff, PV Capex, and battery cost were adjusted to reflect current Saudi Arabia prices.
- Environmental assessment: Under all the different scenarios, the total carbon dioxide sulphur dioxide (SO2) and nitrogen oxides (N2O) emissions were evaluated using Homer.
2.3. Analytics
3. Load Profile Determination
3.1. Addressing Missing Data
3.2. Campus Load Profile
4. Modelled Energy Supply Scenarios
- (a)
- S1—address the current situation where the power is supplied from the fossil fuel grid (business as usual (BAU)).
- (b)
- S2—same as S1 but with “future scheduled tariff” of USD 17 c/kWh applied between 11 am and 4pm daily. The “future scheduled tariff” represents the case for a future electricity tariff increase.
- (c)
- S3—same as S1 augmented by power from an installed PV system connected to the grid with zero value of export electricity to the grid.
- (d)
- S4—same as S3 but with export to the grid at export tariff of USD 1.8 c/kWh.
- (e)
- S5—autonomous power supply to the campus based on standalone PV and battery systems with no grid import or export.
- (f)
- S6—same as S3 connected to the grid but with reduced PV capex cost (capex reduced by 20%) with zero export of electricity to the grid. The 20% PV price reduction represents a future expectation of the PV capex reduction.
- (g)
- S7—same as S6, but export to the grid at a tariff of USD 1.8 c/kWh.
5. Results and Discussion
5.1. Energy Considerations
5.2. Economic Considerations
5.3. Environmental Considerations
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- IEA. Global Energy Review 2019. 2019. Available online: https://www.iea.org/reports/global-energy-review-2019/electricity#abstract (accessed on 1 April 2020).
- ECRA. Electrcity and Cogeneration Regulatory Authority. 2018. Available online: https://www.ecra.gov.sa/en-us/DataAndStatistics/NationalRecord/HistoricalData/Pages/Home.aspx (accessed on 10 February 2019).
- KAPSARC. King Abdullah Petroleum Studies and Research Center. Available online: https://www.kapsarc.org/research/publications/what-is-behind-the-recent-fall-in-saudi-arabias-co2-emissions/ (accessed on 1 February 2020).
- Zell, E.; Gasim, S.; Wilcox, S.; Katamoura, S.; Stoffel, T.; Shibli, H.; Engel-Cox, J.; Al Subie, M. Assessment of solar radiation resources in Saudi Arabia. Sol. Energy 2015, 119, 422–438. [Google Scholar] [CrossRef] [Green Version]
- Saudi Ministry of Energy. Energy & Sustainability. In Proceedings of the 9th International Conference on Energy and Sustainability, Online Conference, 6–8 October 2021. [Google Scholar]
- Rahman, M.; Khan, M.-U.-H.; Ullah, M.A.; Zhang, X.; Kumar, A. A hybrid renewable energy system for a North American off-grid community. Energy 2016, 97, 151–160. [Google Scholar] [CrossRef]
- Rohani, G.; Nour, M. Techno-economical analysis of stand-alone hybrid renewable power system for Ras Musherib in United Arab Emirates. Energy 2014, 64, 828–841. [Google Scholar] [CrossRef]
- Dudley, D. Abu Dhabi Lays Claim To World’s Cheapest Solar Power, After Revealing Bids For 2GW Mega-Plant. Forbes. Available online: https://www.forbes.com/sites/dominicdudley/2020/04/28/ (accessed on 6 October 2021).
- Zubair, A.; Tanvir, A.A.; Hasan, M. Optimal Planning of Standalone Solar-Wind-Diesel Hybrid Energy System for a Coastal Area of Bangladesh. Int. J. Electr. Comput. Eng. 2012, 2, 731–738. [Google Scholar] [CrossRef]
- King Abdulaziz University. King Salman Bin Abdulaziz Chair for Energy Research. Available online: https://kscer.org/#:~:text=King%Salam%Bin%Abdulaziz%2C%Chair,undertaken%research%in%solar%energy (accessed on 5 March 2022).
- NREL. HOMER Software. Available online: https://www.homerenergy.com/products/pro/index.html (accessed on 5 March 2022).
- Matzarakis, A.; Balafoutis, C. Heating degree-days over Greece as an index of energy consumption. Int. J. Clim. 2004, 24, 1817–1828. [Google Scholar] [CrossRef]
- Lam, J.C.; Tsang, C.; Li, D.H. Long term ambient temperature analysis and energy use implications in Hong Kong. Energy Convers. Manag. 2004, 45, 315–327. [Google Scholar] [CrossRef]
- Bizee. Bizee Degree Days. World Degree Days. 2019. Available online: https://www.degreedays.net/# (accessed on 28 February 2019).
- Lambert, T.; Gilman, P.; Lilienthal, P. Micropower system modeling with HOMER. In Integration of Alternative Sources of Energy; Farret, F.A., Simões, M.G., Eds.; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2006; pp. 379–418. [Google Scholar]
- NREL. Lifetime of PV Panels. 2018. Available online: https://www.nrel.gov/state-local-tribal/blog/posts/stat-faqs-part2-lifetime-of-pv-panels.html (accessed on 2 March 2022).
- Statista. Cumulative Installed Solar Pv Capacity Worldwide from 2000 to 2020. Available online: https://www.statista.com/statistics/280220/global-cumulative-installed-solar-pv-capacity/#:~:text=Global%cumulative%installed%solar%PV%capacity%2000-2020&text=Global%cumulative%solar%photovoltaic%capacity,installed%in%that%same%year (accessed on 20 March 2022).
Start Date | End Date | No of Days | Consumption (kWh) | AC Share of Total Load (%) |
---|---|---|---|---|
15 July 2018 | 13 August 2018 | 29 | 1,013,672 | 83 |
14 August 2018 | 15 September 2018 | 32 | 1,083,927 | 82 |
16 September 2018 | 15 October 2018 | 29 | 1,093,963 | 84 |
16 October 2018 | 14 November 2018 | 29 | 883,200 | 80 |
15 November 2018 | 15 December 2018 | 30 | 772,800 | 77 |
16 December 2018 | 13 January 2019 | 28 | 632,291 | 74 |
14 January 2019 | 17 February 2019 | 34 | 782,836 | 74 |
18 February 2019 | 19 March 2019 | 29 | 652,363 | 74 |
Interval | Start Date | End Date |
---|---|---|
A—Spring academic term | 8 January 2019 | 3 May 2019 |
Missing data period | January, February, March | |
B—Summer holiday | 4 May 2019 | 1 September 2019 |
Missing data period | June, July, August | |
C—Eid Alfitr holiday | 30 May 2019 | 9 June 2019 |
Missing data period | none | |
D—Eid Aladha holiday | 5 August 2019 | 18 August 2019 |
Missing data period | none | |
E—Fall academic term | 2 September 2019 | 30 December 2019 |
Missing data period | November, December |
Scenario of Designed PV System Deployment at Different Export Tariffs and CAPEX | Installed PV, Size, Output, Export to Grid, and Share of Supply to Campus | Annual Grid Import to Campus (MWh) | |||
---|---|---|---|---|---|
Capacity (MWp) | Energy (MWh/Annum) | Energy Export (MWh/Annum) | Supply Share to Campus (%) | ||
S3 Grid supply + PV system, export at zero tariff | 4.5 | 7321 | 1403 | 60 | 4018 |
S4 Grid supply + PV system, export at USD 1.8 c/kWh | 5.3 | 8549 | 2351 | 62 | 3741 |
S5 PV system + Battery standalone | 12.12 | 19,557 | 8408 | 100 | none |
S6 Grid supply + PV system, export at zero tariff, with 20% reduction in PV Capex | 4.8 | 7779 | 1566 | 63 | 3726 |
S7 Grid supply + PV system, export at USD 1.8 c/kWh, 20% reduction in PV Capex | 6.1 | 9838 | 3326 | 66 | 3326 |
PV System Deployment Scenarios (S) for Different Tariffs | PV Capacity (MWp) | Net Present Cost USD (Millions) | LCOE (USD c/kWh) |
---|---|---|---|
S1 business as usual. | -Grid | 31.7 | 9.77 |
S2 same as S1, but with “future scheduled tariff” (see text) | -Grid | 40.5 | 12.5 |
S3 Grid supply + PV system, export tariff zero | 4.5 | 22.7 | 6.13 |
S4 Grid supply + PV system, export tariff USD 1.8 c/kWh | 5.3 | 21.6 | 5.39 |
S5 standalone PV and battery systems no grid import or export. | 60.6 | 19.1 | |
S6 Grid supply + PV system, export at zero tariff, with 20% reduction in PV Capex | 4.8 | 21.8 | 5.79 |
S7 Grid supply + PV system, export at USD 1.8 c/kWh tariff, with 20% reduction in PV Capex | 6 | 20.5 | 4.73 |
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Alsulamy, S.; Bahaj, A.S.; James, P.; Alghamdi, N. Solar PV Penetration Scenarios for a University Campus in KSA. Energies 2022, 15, 3150. https://doi.org/10.3390/en15093150
Alsulamy S, Bahaj AS, James P, Alghamdi N. Solar PV Penetration Scenarios for a University Campus in KSA. Energies. 2022; 15(9):3150. https://doi.org/10.3390/en15093150
Chicago/Turabian StyleAlsulamy, Sager, AbuBakr S. Bahaj, Patrick James, and Nasser Alghamdi. 2022. "Solar PV Penetration Scenarios for a University Campus in KSA" Energies 15, no. 9: 3150. https://doi.org/10.3390/en15093150