Modified Teaching-Learning Based Optimisation for Resilience and Sustainability in the Renewable Energy Industry

Renewable energy sector resilience ensures sustainability and reliability together with cybersecurity features for present-day power networks. Growing wind and solar and hybrid distributed generation (RHDG) systems create numerous network problems, including power system instability, cyber security risks, and operational efficiency problems. The implementation of Modified Teaching-Learning Based Optimisation (MTLBO) serves as an improvement method for resolving power flow management issues and enhancing fault tolerance while ensuring energy security. MTLBO serves to maximize renewable energy deployment while minimizing power losses and improving resistance against cyber-physical security threats. The integration of decentralized microgrid design, realtime monitoring, and artificial intelligence to identify anomalies enhances system resilience. Multiple smart grid security measures are implemented through Blockchain technology to combat potential cyberattacks which endanger grid operations. The research demonstrates how implementing MTLBO and advanced cybersecurity strategies for OPF enables sustainable development of renewable energy infrastructure. The proposed method delivers secure, efficient, and adaptive power management that enables a resilient renewable energy power infrastructure for future readiness.