Technological Maturation and Methodological Bias Mitigation in the Renewable Energy Ecosystem: A Strategic Review of Indian R&D Institutions

Abstract India's transition toward its Net-Zero 2070 target requires not only technological innovation but also improved decision-making within the renewable energy ecosystem. This paper investigates how cognitive biases, including overconfidence, confirmation bias, anchoring bias, and availability bias, influence entrepreneurial decisions in renewable energy ventures. It further examines the role of India's leading renewable energy research institutions—National Institute of Solar Energy (NISE), National Institute of Wind Energy (NIWE), and Sardar Swaran Singh National Institute of Bio-Energy (SSS-NIBE)—in mitigating these biases through standardized testing, scientific validation, and data-driven decision support. Using a qualitative analysis of the Ministry of New and Renewable Energy (MNRE) Annual Report (2023–2024), this study maps institutional research outputs to behavioral economic principles and demonstrates how these organizations function as technological debiasing mechanisms. The paper also explores the integration of machine learning and analytics for objective forecasting while highlighting the potential risk of automation bias. Based on these findings, a Technological Debiasing System (TDS) framework is proposed to support evidence-based innovation and improve the reliability of renewable energy entrepreneurship. The study concludes that combining institutional infrastructure, advanced analytics, and behavioral insights can significantly strengthen decision-making, reduce cognitive bias, and accelerate sustainable renewable energy innovation in India.