Optimizing Renewable Integration in Distribution Power Systems Using an Improved Artificial Bee Colony Algorithm

This paper presents a multi-objective optimization framework for the optimal integration of Renewable Energy Sources (RES) into Distribution Power Systems (DPS), aiming to simultaneously maximize RES utilization, minimize operational costs, and reduce greenhouse gas emissions. To address the complexity and nonlinearity of the problem, an improved Artificial Bee Colony (ABC) algorithm is proposed, incorporating a refined search strategy that effectively balances global exploration and local exploitation. The optimization model considers practical constraints such as generation capacity limits, voltage regulations, and power balance requirements. Extensive simulations on the IEEE 33-bus and 69-bus benchmark systems demonstrate that the proposed method outperforms conventional metaheuristic algorithms, achieving an average of 26.7% reduction in power losses, 22.5% decrease in CO2 emissions, and 57.9% DG penetration. These results underscore the proposed method's robustness and practical applicability for sustainable and intelligent energy planning in modern distribution networks.