Development of the life-cycle economic and environmental assessment model for establishing the optimal implementation strategy of the rooftop photovoltaic system
Abstract
To maximize the life-cycle economic and environmental performance of the rooftop photovoltaic (PV) system in real projects, it is necessary to consider several factors such as regional climate factors (i.e., geographical and meteorological factors) and building characteristics (i.e., on-site installation factors, rooftop area limit, and budget limit). Towards this end, this study aimed to develop the life-cycle economic and environmental assessment model for establishing the optimal implementation strategy of the rooftop PV system. The robustness and reliability of the developed model were evaluated in terms of two perspectives: (i) for the effectiveness of the optimal solution, the optimization results were generated by considering the regional climate factors and building characteristics. Namely, the results for SIR25 (saving to investment ratio at year 25), which was set at the optimization goal, were 2.540 (Busan, southern part of South Korea), 2.485 (Daejeon, central part of South Korea), and 2.266 (Seoul, northern part of South Korea), respectively; and (ii) for the efficient computation time, the time required for determining the optimal solution was only 27 seconds. The developed model can be used to easily and accurately assess the life-cycle economic and environmental performance of the rooftop PV system in the early design phase.
First published online 14 April 2016
Keyword : rooftop photovoltaic system, economic and environmental assessment, forecasting and simulation, optimization, sustainable development, life cycle cost analysis
How to Cite
Koo, C., Hong, T., & Park, J. (2018). Development of the life-cycle economic and environmental assessment model for establishing the optimal implementation strategy of the rooftop photovoltaic system. Technological and Economic Development of Economy, 24(1), 27–47. https://doi.org/10.3846/20294913.2015.1074127
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Bank of Korea Economic Statistics System (ECOS) [online]. 2013 [cited 7 May 2013]. Available from Internet: http://ecos.bok.or.kr
Bhatti, M. A. 2000. Practical optimization methods. New York: Springer-Verlag.
Bojić, M.; Bigot, D.; Miranville, F.; Parvedy-Patou, A.; Radulovic, J. 2012. Optimizing performance of photovoltaics in Reunion Island-tilt angle, Progress in Photovoltaics: Research and Applications 20(8): 923–935. http://dx.doi.org/10.1002/pip.1159
Braun, A.; Katz, E. A.; Gordon, J. M. 2013. Basic aspects of the temperature coefficients of concentrator solar cell performance parameters, Progress in Photovoltaics: Research and Applications 21(5): 1087–1094. http://dx.doi.org/10.1002/pip.2210
Brearley, D. 2009. C-Si photovoltaic trends: design, purchasing and 2009 specs, Solar Pro Magazine 2009 June/July, 49–74.
Construction Association of Korea (CAK). 2012. Monthly construction market price (October). Seoul, South Korea, CAK.
Dell’Isola, A. J.; Kirk, S. J. 2003. Life cycle costing for facilities. Kingston, United States: Reed Construction Data.
Department of State (DOS). 2010. U.S. climate action report 2010: Fifth national communication of the United States of America under the United Nations Framework Convention on Climate Change. DOS, Washington, DC.
Dincer, F.; Meral, M. E. 2010. Critical factors that affecting efficiency of solar cells, Smart Grid and Renewable Energy 1: 47–50.
European Environment Agency (EEA). 2011. Greenhouse gas emission trends and projections in Europe 2011: tracking progress towards Kyoto and 2020 targets. EEA, Copenhagen.
Gen, M.; Cheng, R. 2000. Genetic algorithms & engineering optimization. New York: Wiley-Interscience.
Gong, X.; KulKarni, M. 2005. Design optimization of a large scale rooftop photovoltaic system, Solar Energy 78(3): 362–374. http://dx.doi.org/10.1016/j.solener.2004.08.008
Harder, E.; Gibson, J. M. 2011. The costs and benefits of large-scale solar photovoltaic power production in Abu Dhabi: United Arab Emirates, Renewable Energy 36(2): 789–796. http://dx.doi.org/10.1016/j.renene.2010.08.006
Hoffmann, S.; Koehl, M. 2014. Effect of humidity and temperature on the potential-induced degradation, Progress in Photovoltaics: Research and Applications 22(2): 173–179. http://dx.doi.org/10.1002/pip.2238
Hong, T.; Koo, C.; Kwak, T. 2013. Framework for the implementation of a new renewable energy system in an educational facility, Applied Energy 103(3): 539–551. http://dx.doi.org/10.1016/j.apenergy.2012.10.013
Hong, T.; Koo, C.; Lee, S. 2014a. Benchmarks as a tool for free allocation through comparison with similar projects: focused on multi-family housing complex, Applied Energy 114(2): 663–675. http://dx.doi.org/10.1016/j.apenergy.2013.10.035
Hong, T.; Koo, C.; Kwak, T.; Park, H. 2014b. An economic and environmental assessment for selecting the optimum new renewable energy system for educational facility, Renewable and Sustainable Energy Reviews 29(1): 286–300. http://dx.doi.org/10.1016/j.rser.2013.08.061
Hong, T.; Koo, C.; Park, J.; Park, H. S. 2014c. A GIS (geographic information system)-based optimization model for estimating the electricity generation in the rooftop PV (photovoltaic) system, Energy 65: 190–199. http://dx.doi.org/10.1016/j.energy.2013.11.082
Intergovernmental Panel on Climate Change (IPCC). 2007. Climate Change 2007: Synthesis report. IPCC.
International Energy Agency (IEA). 2008a. Community-scale solar photovoltaics: housing and public development example. IEA.
International Energy Agency (IEA). 2008b. Urban BIPV in the new residential construction industry 2008. IEA.
International Energy Agency (IEA). 2010. World Energy Outlook 2010. IEA.
International Renewable Energy Agency (IRENA). 2012. Renewable energy technologies: cost analysis series, volume 1: power sector, issue 4/5 solar photovoltaics. IRENA, Abu Dhabi.
Joint Research Centre (JRC). 2011. PV status report 2011. JRC, Italy.
Kaldellis, J.; Zafirakis, D. 2012. Experimental investigation of the optimum photovoltaic panels’ tilt angle during the summer period, Energy 38(1): 305–314. http://dx.doi.org/10.1016/j.energy.2011.11.058
Koo, C.; Hong, T.; Lee, M.; Park, H. S. 2013. Estimation of the monthly average daily solar radiation using geographical information system and advanced case-based reasoning, Environmental Science & Technology 47: 4829–4839. http://dx.doi.org/10.1021/es303774a
Koo, C.; Hong, T.; Park, H. S.; Yun, G. 2014. Framework for the analysis of the potential of the rooftop photovoltaic system to achieve the net zero-energy solar buildings, Progress in Photovoltaics: Research and Applications 22(4): 462–478. http://dx.doi.org/10.1002/pip.2448
Korea Electric Association (KEA). 2000. Replacement fossil fuel by solar energy. KEA, Seoul, South Korea.
Korea Energy Management Corporation (KEMCO). 2013a. Registration and trade system for Korea voluntary emission reduction project [online]. KEMCO, Seoul, South Korea [cited 7 May 2013]. Available from Internet: https://kver.kemco.or.kr
Korea Energy Management Corporation (KEMCO). 2013b. Introduction to the 1 million green home project [online]. KEMCO, Seoul, South Korea [cited 7 May 2013]. Available from Internet: http://greenhome.kemco.or.kr
Korea Mech. Const. Contractors Association (KMCCA). 2011. Exploration of new regeneration energy. KMCCA, Seoul, South Korea.
Korean Statistical Information Service (KOSIS) [online]. 2013 [cited 7 May 2013]. Available from Internet: http://kosis.kr
Lee, M.; Koo, C.; Hong, T.; Park, H. S. 2014. Framework for the mapping of the monthly average daily solar radiation using an advanced case-based reasoning and a geostatistical technique, Environmental Science and Technology 48: 4604–4612. http://dx.doi.org/10.1021/es405293u
Levinson, R.; Akbari, H.; Pomerantz, M.; Gupta, S. 2009. Solar access of residential rooftops in four California cities, Solar Energy 83: 2120–2135. http://dx.doi.org/10.1016/j.solener.2009.07.016
Melbourne Energy Institute (MEI). 2011. Renewable energy technology cost review. MEI, Melbourne.
Minister of Natural Resources (MNR). 2010. Clean energy project analysis: RETScreen engineering & cases textbook. 3rd ed. MNR, Canada.
Ministry of Knowledge Economy (MKE). 2011. Composition of expanding through the research of solar power supply potential. MKE, Korea.
New and Renewable Energy Centre (NREC). 2013. Subsidies for general dissemination [online], [cited 7 May 2013]. Available from Internet: http://www.energy.or.kr/knrec/12/KNREC120200.asp
Ordonez, J.; Jadraque, E.; Alegre, J.; Martinez, G. 2010. Analysis of the photovoltaic solar energy capacity of residential rooftops in Andalusia, Renewable and Sustainable Energy Reviews 14(7): 2122– 2130. http://dx.doi.org/10.1016/j.rser.2010.01.001
Sarhaddi, F.; Farahat, S.; Ajam, H.; Behzadmehr, A. 2009. Exergetic optimization of a solar photovoltaic array, Journal of Thermodynamics. Article number 313561. http://dx.doi.org/10.1155/2009/313561
Siraki, A. G.; Pillay, P. 2012. Study of optimum tilt angles for solar panels in different latitudes for urban applications, Solar Energy 86: 1920–1928. http://dx.doi.org/10.1016/j.solener.2012.02.030
Tiris, M.; Tiris, C. 1998. Optimum collector slope and model evaluation: case study for Gebze, Turkey, Energy Conversion and Management 39(3–4): 167–172. http://dx.doi.org/10.1016/S0196-8904(96)00229-4
United Nations (UN). 1998. Kyoto Protocol to the United Nations Framework Convention on Climate Change. UN.
Weinstock, D.; Appelbaum, J. 2009. Optimization of solar photovoltaic fields, Journal of Solar Energy Engineering 131(3): 1–9. http://dx.doi.org/10.1115/1.3142705
World Energy Council (WEC). 2010. 2010 Survey of energy resources. WEC, U.K.
Zhao, Q.; Wang, P.; Goel, L. 2010. Optimal PV panel tilt angle based on solar radiation prediction, in IEEE 11th International Conference Probabilistic Methods Applied to Power Systems (PMAPS), 14–17 June 2010, Singapoure. http://dx.doi.org/10.1109/PMAPS.2010.5528960