Multi-Objective Green Expansion Planning of Transmission and Generation Networks under Renewable Uncertainty Using Hybrid Intelligent Metaheuristic Framework

The rapid integration of large-scale wind and solar photovoltaic (PV) generation introduces significant uncertainty and planning complexity in modern power systems, necessitating coordinated and environmentally sustainable expansion strategies. This paper presents a hybrid multi-objective optimization framework for coordinated Generation and Transmission Network Expansion Planning (GTEP) in a modified IEEE 39-bus test system incorporating thermal, wind, and solar PV units under stochastic uncertainty. The proposed framework simultaneously minimizes total investment and operational costs, transmission congestion costs, and carbon emission penalties modeled through a Carbon Tax mechanism, ensuring an economically viable and environmentally compliant expansion plan. To address the strong nonlinearity, mixed-integer nature, and conflicting objectives of the GTEP problem, a hybrid Modified Artificial Bee Colony (MOABC) and NSGA-II algorithm is developed. MOABC enhances global exploration and solution diversity due to reinforcement learning adoption, while NSGA-II ensures fast non-dominated sorting and elitist convergence. Wind and solar uncertainties are modeled using scenario-based stochastic representations derived from probabilistic forecast distributions. AC optimal power flow constraints, generator operational limits, line thermal limits, and renewable penetration constraints are rigorously enforced. The carbon emission objective is formulated using a Carbon Tax–based emission cost model, which internalizes environmental impact directly into the planning decisions. The proposed framework generates a high-quality Pareto front capturing trade-offs among economic cost, network reinforcement, and emission reduction. A decision-making strategy based on fuzzy membership is employed to extract the Best Compromise Solution (BCS). Simulation results on the modified IEEE-39 bus system demonstrate that the proposed hybrid MOABC–NSGA-II approach significantly reduces total expansion cost and carbon emissions while improving network adequacy under renewable uncertainty. The results confirm the robustness, scalability, and practical suitability of the proposed framework for low-carbon power system expansion planning.