MCDM for simultaneous optimum economy, investment risk and environmental impact for distributed renewable power: Demonstration with an Indian village data

Increasing renewable share in power supply is currently a global mission. Decentralized renewable power with locally available resources is an emerging preferred sustainable energy solution. This is even more recommended for remote locations where reliable grid power is neither available nor feasible. However, insufficient availability and intermittency of local renewable resources, cost of unit electricity and reluctance of investors due to uncertainty in return on investment in new technologies are some of the critical issues to be addressed. A detailed environmental impact assessment is also needed. Considering the research gap, this study aims to find technically efficient, economically optimal with less uncertainty on return on investment and environmentally benign energy combinations for distributed generation. The methodology proposed in this paper integrates techno-economic optimization with uncertainty analysis in return on investment through Monte Carlo analysis and environmental impact assessment using life cycle assessment to explore an even better sustainable solution. A multi criteria decision making approach is then adopted to decide a final optimum solution for three multi criteria of cost, uncertainty in return on investment and environmental impact. Such a comprehensive analysis for an optimum solution is demonstrated for a remote village of India. The analysis result shows that the combination of solar photovoltaic-diesel generator-Battery system is the possible optimum solution with a cost of electricity of $0.21/kW.h, a standard deviation of 0.07 for risk on investment and a moderate environmental impact.

Automated summary

Increasing the share of renewable energy in power supply is a global priority, especially in remote areas where reliable grid power is not available. However, issues such as limited availability of local renewable resources, high unit electricity cost, and investors' uncertainty in return on investment pose challenges. This study aims to find technically efficient, economically optimal, and environmentally friendly energy combinations for distributed generation, using a comprehensive analysis that integrates techno-economic optimization, uncertainty analysis, and environmental impact assessment. The analysis results suggest that a solar photovoltaic-diesel generator-battery system combination is the possible optimum solution, with a cost of electricity of $0.21/kW.h, a standard deviation of 0.07 for investment risk, and moderate environmental impact.