Economic Assessment of Distributed Generation Technologies: A Feasibility Study and Comparison with the Literature

Ameena Saad Al-Sumaiti, Abdollah Kavousi-Fard, Magdy Salama, Motahareh Pourbehzadi, Srikanth Reddy and Muhammad Babar Rasheed
Additional contact information
Ameena Saad Al-Sumaiti: Advanced Power and Energy Center, Department of Electrical Engineering and Computer Science, Khalifa University, P.O. Box 127788 Abu Dhabi, UAE
Abdollah Kavousi-Fard: Department of Electronics and Electrical Engineering, University of Michigan, Ann Arbor, MI 48126, USA
Magdy Salama: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Motahareh Pourbehzadi: Department of Electrical Engineering, University of South Florida, Tampa, FL 33620, USA
Srikanth Reddy: Advanced Power and Energy Center, Department of Electrical Engineering and Computer Science, Khalifa University, P.O. Box 127788 Abu Dhabi, UAE
Muhammad Babar Rasheed: Department of Electronics and Electrical Systems, The University of Lahore, Lahore 54590, Pakistan

Energies, 2020, vol. 13, issue 11, 1-28

Abstract: With the negative climate impact of fossil fuel power generation and the requirement of global policy to shift towards a green mix of energy production, the investment in renewable energy is an opportunity in developing countries. However, poor economy associated with limited income, funds availability, and regulations governing project funding and development are key factors that challenge investors in the energy sector. Given the various power generation resources, including renewables, it is necessary to evaluate the possible power generation investment options from an economic perspective. To realize this objective, solar PV, wind and diesel power generations are economically compared, considering the incremental rate of return and incremental benefit to cost ratio techniques. The alternative investment options of distributed generation technologies are evaluated for Maharashtra, India under different depreciation methods, and the effect of the latter on selecting the best investment candidate is investigated. The paper also conducts sensitivity analysis to examine the impact of capital cost, operation and maintenance cost, and fuel cost variations on the selection decision considering a comparison of the different general projects’ cash flow structures discussed in the literature. The economic aspects of selecting a project among possible alternatives for an investment in the power sector are analyzed, and the presented review provides comprehensive comparisons with respect to the literature approaches. The results reveal that, in the benchmark case study, the PV project is rejected and disregarded from further comparisons with other candidate projects since its equity internal rate of return (10.25%) is less than the minimum accepted rate of return, leaving the selection between wind and diesel energy projects. The study reveals that the incremental rates of return under such a comparison are 37.88%, 45.94% and 37.50% when MACRS, declining balance and straight line depreciations techniques are applied, respectively. Thus, the wind energy project is the favored option in this case. For the economic assessment of other case studies, the application of both sensitivity analysis on the capital cost and operation and maintenance cost and literature approaches to structure the projects reveal that wind energy for Maharashtra, India is a more attractive and feasible option compared to other distribution generation projects, while diesel is only considered to be a good option when its fuel cost is reduced by 5%. Finally, the paper highlights policy implications that can influence the decision to move towards investment in distributed generation technologies as a future research direction.

Keywords: distributed generation technologies; modified accelerated cost recovery system; incremental rate of return analysis; benefit to cost ratio; depreciation methods; policy implications (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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