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In recent years, heightened environmental concerns have brought a renewed focus to the Economic Dispatch (ED) problem. The contemporary objective of ED is to guide power systems towards minimizing both pollution and costs. For electrical power systems, multi-objective generation dispatch strives to harmonize economic and environmental impacts, presenting a dual-goal challenge for optimal solutions. This study aims to identify optimal strategies for power system networks, optimizing parameters like power flow equations and equipment limits to achieve desired outcomes. The core objective of this paper is to strike a balance between economically favorable energy choices and ecologically sound actions.This work addresses the Economic and Emission Dispatch (EED) issue, considering Valve Point Loading and Load Flow Analysis for both a 6-node and IEEE 30-node network. The research leverages Genetic Algorithm (GA), Simulated Annealing algorithm (SA), Honey Bee algorithm (HB), and a Hybrid Honey Bee and Simulated Annealing algorithm (HBSA) to simulate load flow and resolve the joint EED challenge in power systems. These versatile, population-based optimization techniques offer real-world problem-solving potential. The incorporation of these optimization approaches reveals HBSA is superiority in terms of cost-effectiveness and environmental impact, establishing its efficacy. |
