Optimal Transmission Expansion Planning in Deregulated Power Markets Using AI-Enhanced Cost-Based Pricing

Transmission expansion planning plays a critical role in ensuring the reliability and efficiency of power systems in deregulated markets. In such markets, optimal expansion planning becomes complex due to uncertainties in electricity demand, generation technologies, and market dynamics. This research paper reviews and analyses some research papers that focus on the utilization of Artificial Intelligence (AI)-enhanced cost-based pricing strategies for achieving optimal transmission expansion planning in deregulated power markets. The paper categorizes and evaluates these studies based on methodologies, case studies, AI techniques employed, and their contributions to the field tested on radial 5-bus system. The synthesis of these works highlights the growing significance of AI techniques in addressing the intricate challenges posed by transmission expansion planning within deregulated power markets.