Optimum sustainable distributed hybrid generation using forecasting and multi-criteria decision making: demonstration for an Indian village

Abstract

The global energy demand is ever increasing. Industrialization, urbanization and growth of population are the primary reasons for the rise in energy demand. About 75% of the total energy in the global power mix is catered by non-renewable energy resources. The transition in the energy sector is towards increasing share of renewable energy. Renewable resources are mostly intermittent. There are Uncertainties in energy demand too as it depends on human activities. A precise forecasting of load demand with selection of combinations of local energy resources to meet that demand will be a feasible solution for distributed energy installations. The objective of this study is to perform an accurate forecasting of the load demand and evaluate its benefit with techno-economic analysis and environmental impact assessment of a hybrid renewable energy system. The load demand of the system was estimated by three different machine learning based forecasting approaches. With the most accurate forecasted result different hybrid energy combinations were verified for an uninterrupted power supply. The best performance for technical, economic and environmental parameters of the integrated hybrid system may not converge at the same combination. To determine the optimum energy system approach is adopted. Multi-criteria decision-making approach is used to determine the optimum solution. The methodology is demonstrated with the data of a remote village in Odisha, India. Forecasting of load demand using fuzzy based method has the least error. Using multi-criteria decisionmaking approach, it is concluded that the hybrid energy combination with solar photovoltaic - diesel generator–converter - lead acid battery combination is the decided optimum solution for acceptable overall techno-economic and environmental sustainability. This combination of SPV-DG-C-LA has a COE of $0.100/kWh, NPC of -$5374 and EE- 21.7%, resources- 386120 USD2013, ecosystems- 0.002 species.yr and human health- 1.14 DALY with respect to sustainability