Evaluating India's 2030 Electricity Demand Target: A Multi-Criteria Decision-Making Approach

Abstract

The aim of this research study is to assess the feasibility of meeting India's forecasted electricity demand by generating half of it from renewable sources by 2030 with minimal cost and greenhouse gas (GHG) emissions. To achieve this objective, the study examines alternative options for generating the projected electricity demand for 2030 using a multi-objective optimization approach. The study utilizes GHG emissions estimated using a life cycle approach and Levelized Cost of Electricity projected by the International Energy Agency as input parameters for optimization. The genetic algorithm in MATLAB is used to examine alternative energy pathways under various scenarios, with constraints imposed by the availability of energy resources and the share of renewable energy. The best option is selected using a Multi-Criteria Decision Making (MCDM) method called TOPSIS. The results of the study suggest that the most cost-effective and emission-reducing approach to meet India's 2030 electricity demand is to increase the share of renewable energy sources. Even with the share of renewable energy remaining at the current level of 2022, optimization can still reduce costs by 26.5% and emissions by 87% compared to the business-as-usual scenario. Additionally, the study provides various options for meeting the 2030 target for electricity generation at lower cost and emission levels. The findings of this study have important implications for understanding the feasibility of India's renewable energy target and its potential impact on cost and emission reductions.