Decision Support System for Solar Energy Adoption

Carlos Lopes, Diogo Martino, Nuno Bandeira, Fernando Almeida


A decision support system (DSS) is a computerized information system that combines models and data to solve unstructured or semi-structured problems, with intense user involvement. DSSs have high applicability in several business areas and enable users without technical knowledge in computing to manipulate the information needed for a more assertive decision-making process. This study presents a DSS to support the decision process of installing a photovoltaic solution that considers the contracted power, the monthly expenses in electricity, and the location of the installation. The return on investment is estimated considering the annual savings in electricity and the return on investment. The findings indicate the relevance of the application to support the user in choosing the best solution and reveal that geographical location is a determining factor in the potential energy savings. Furthermore, the payback period decreases by increasing users' monthly consumption and is also potentiated by the increase in contracted power.


photovoltaic panels; renewable energy; sustainability; decision-making process; solar radiation; investment return

Full Text:



T. Peterson, J. Stephens, and E. Wilson, “Public perception of and engagement with emerging low-carbon energy technologies: A literature review”, MRS Energy & Sustainability, vol. 2, no. 11, pp. 1-14, 2015.

A. Greiner, L. Gruene, and W. Semmler, “Economic growth and the transition from non-renewable to renewable energy”, Environment and Development Economics, vol. 19, no. 4, pp. 417-439, 2014.

IEA, “Renewables 2019 - Market analysis and forecast from 2019 to 2024”. Available: [Accessed May 30, 2020].

J. P. Dunlop. Photovoltaic Systems. Orland Park, Illinois: American Technical Publishers, 2009.

D. C. Jordan, and S. R. Kurtz, “Photovoltaic Degradation Rates - an Analytical Review”, Progress in Photovoltaics, vol. 21, no. 1, pp. 12-29, 2013.

R. McAtee, “Sustainable Energy Is More Cost-Efficient Than You Think: Three Ways That Renewable Energy Is Becoming Cheaper for Companies”, Solar Magazine, May 19, 2019. Available:

S. K. Yadav, and U. Bajpai, “Energy, economic and environmental performance of a solar rooftop photovoltaic system in India”, International Journal of Sustainable Energy, vol. 39, no. 1, pp. 51-66, 2020.

D. Arnott, and G. Pervan, “A critical analysis of decision support systems research,” in Formulating Research Methods for Information Systems, L. P. Willcocks, C. Sauer, and M. C. Lacity, Eds. London, UK: Palgrave Macmillan, 2015, pp. 127-168.

E. L. Cano, J. M. Moguerza, and T. Ermolieva, “A strategic decision support system framework for energy-efficient technology investments”, TOP, vol. 25, pp. 249-270, 2017.

F. Carton, T. Hynes, and F. Adam, “A business value oriented approach to decision support systems”, Journal of Decision Systems, vol. 25, no. 1, pp. 85-95, 2016.

M. Omidvar, and F. Bordbar, “Advanced decision support systems for managers”, European Online Journal of Natural and Social Sciences, vol. 2, no. 3, pp. 700-708, 2013.

K. Chung, R. Boutaba, and S. Hariri, “Knowledge based decision support system”, Information Technology and Management, vol. 17, pp. 1-3, 2016.

R. Sharda, D. Delen, and E. Turban, Business Intelligence and Analytics: Systems for Decision Support. London, UK: Pearson, 2014.

D. Schwartz, Decision Support Systems. New York: Clanrye International, 2015.

G. Marakas, and J. O’Brien, Introduction to Information Systems. New York: McGraw-Hill Education, 2012.

R. Banerjee, B. Inamdar, S. Phulluke, and B. Pateriya, “Decision Support System for Energy Planning in a District: Residential Module”, Economic and Political Weekly, vol. 34, no. 5, pp. 3545-3552, 1999.

S. Hettinga, P. Nijkamp, and H. Scholten, “A multi-stakeholder decision support system for local neighbourhood energy planning”, Energy Policy, vol. 116, pp. 277-288, 2018.

M. Eremia, L. Toma, and M. Sanduleac, “The Smart City Concept in the 21st Century”, Procedia Engineering, vol. 181, pp. 12-19, 2017.

I. Papastamatiou, V. Marinakis, H. Doukas, and J. Psarras, “A decision support framework for smart cities energy assessment and optimization”, Energy Procedia, vol. 111, pp. 800-809, 2017.

I. Stamatescu, N. Arghira, I. Fagarasan, G. Stamatescu, S. Iliescu, and V. Calofir, “Decision Support System for a Low Voltage Renewable Energy System”, Energies, vol. 10, no. 1, pp. 1-15, 2017.

M. Silverio-Fernández, S. Renukappa, and S. Suresh, “What is a smart device? – a conceptualisation within the paradigm of the internet of things”, Visualization in Engineering, vol. 6, no. 3, pp. 1-10, 2018.

F. Almeida, “Concept and Dimensions of Web 4.0”, International Journal of Computers & Technology, vol. 16, no. 7, pp. 7040-7046, 2017.

V. Marinakis, and H. Doukas, “An Advanced IoT-based System for Intelligent Energy Management in Buildings”, Sensors, vol. 18, pp. 1-16, 2018.

A. Miles, A. Zaslavsky, and C. Browne, “IoT-based decision support system for monitoring and mitigating atmospheric pollution in smart cities”, Journal of Decision Systems, vol. 27, no. 1, pp. 56-67, 2018.

D. A. Mohamed, and N. R. Darwish, “Extracting CRM Requirements – Waterfall or Agile: A Comparative Study”, International Research Journal of Advanced Engineering and Science, vol. 4, no. 3, pp. 1-5, 2019.

J. W. Cangussu, R. A. DeCarlo, and A. P. Mathur, “A formal model of the software test process”, IEEE Transactions on Software Engineering, vol. 28, no. 8, pp. 782-796, 2002.

NASA, “Power Project Data Sets”. Available: [Accessed April 23, 2020].

R. Pardeshi, Decision Tree Modeling: Decision Science Series – A Practical Handbook For Decision Tree Analysis. Seattle: Services LLC, 2019.

M. D. Hamad, A. Elsayed, M. El-Borai, and W. M. Abdelmoez, “Software Product Requirements Prioritization Techniques: Hardly Easy”, International Journal of Artificial Intelligence and Mechatronics, vol. 4, no. 6, pp. 198-209, 2016.

I. Sommerville, Software Engineering. London, UK: Pearson, 2015.

K. Elk, SQL Server with C#. Seattle: Services LLC, 2018.

C. Rusu, V. Rusu, S. Roncagliolo, and C. González, “Usability and User Experience: What Should We Care About?”, International Journal of Information Technologies and Systems Approach, vol. 8, no. 2, pp. 1-12, 2015.

F. Almeida, and J. Monteiro, “Approaches and Principles for UX Web Experiences: A Case Study Approach”, International Journal of Information Technology and Web Engineering, vol. 12, no. 2, pp. 49-65, 2017.

O. Ozcan, and F. Ersoz, “Project and cost-based evaluation of solar energy performance in three different geographical regions of Turkey: Investment analysis application”, Engineering Science and Technology, an International Journal, vol. 22, no. 4, pp. 1098-1106, 2019.

Z. Zhou, and M. Carbajales-Dale, “Assessing the photovoltaic technology landscape: efficiency and energy return on investment (EROI)”, Energy & Environmental Science, vol. 11, pp. 603-608, 2018.

J. Thornhill, “Under new rules for selling solar power, is it still worth it?”, The Guardian. Available: [Accessed May 5, 2020].

C. Castillo, F. B. Silva, and C. Lavalle, “An assessment of the regional potential for solar power generation in EU-28”, Energy Policy, vol. 88, pp. 86-89, 2016.



  • There are currently no refbacks.

Copyright (c) 2020 Carlos Lopes, Diogo Martino, Nuno Bandeira, Fernando Almeida

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Renewable Energy and Sustainable Development

E-ISSN: 2356-8569

P-ISSN: 2356-8518


Published by:

Academy Publishing Center (APC)

Arab Academy for Science, Technology and Maritime Transport (AASTMT)