Search

This paper proposes an improved biogeography-based optimization (BBO) algorithm to effectively solve the economic and environmental dispatch (EED) problem in power systems. The EED problem is a crucial optimization challenge in power system operations, which aims to balance the minimization of operating costs and environmental impacts. Various metaheuristic algorithms have been explored in the literature to address this problem, including the original BBO algorithm. However, the complex constraints and non-linearities associated with the EED problem, such as ramp-rate limits (RRLs), prohibited operating Zones (POZs), and valve point loading effects (VPLEs), pose significant challenges for the original BBO approach. The EED problem is subject to a range of practical constraints that significantly impact the optimal dispatch solution. Addressing these constraints accurately and efficiently is essential for realistic power system optimization. In this work, we present an enhanced BBO algorithm that incorporates several innovative features to improve its performance and overcome the limitations of the original approach. The key enhancement is the incorporation of the Cauchy distribution as the mutation operator, which helps the algorithm to better explore the search space and escape local optima. Comprehensive experiments were conducted on standard 10-bus and 40-bus test systems to evaluate the effectiveness of the proposed algorithm. The results demonstrate that the improved BBO algorithm outperforms other state-of-the-art optimization techniques in terms of convergence speed, solution quality, and robustness. Specifically, the enhanced BBO algorithm achieved a 12% reduction in operating costs and a 15% decrease in emissions compared to the original BBO method. The proposed improved BBO algorithm provides a promising solution for effectively addressing the EED problem in power systems, considering the practical constraints and non-linearities that are commonly encountered in real-world scenarios. [ABSTRACT FROM AUTHOR]

Combined economic emission dispatch (CEED) problems are among the most crucial problems in electrical power systems. The purpose of the CEED is to plan the outputs of all production units available in the electrical power system in such a way that the cost of fuel and polluted emissions are minimized while respecting the equality and inequality constraints of the system and efficiently responding to the power load required. The rapid depletion of these sources causes limitation and increases the price of fuel. It is therefore very important that scientific research in the last few decades has been oriented toward the integration of renewable energy systems (RES) such as wind and PV as an alternative source. Furthermore, the CEED problem including RES is the most important problem with regard to electrical power field optimization. In this study, a classification of optimization techniques that are widely used, such as traditional methods, non-conventional methods, and hybrid methods, is summarized. Many optimization methods have been presented and each of them has its own advantages and disadvantages for solving this complex CEED problem, including renewable energy. A review of different optimization techniques for solving this CEED problem is explored in this present paper. This review will encourage researchers in the future to gain knowledge of the best approaches applicable to solve CEED problems for practical electrical systems. [ABSTRACT FROM AUTHOR]