HYBRID METAHEURISTIC APPROACH FOR LOCATIONAL MARGINAL PRICE COMPUTATION IN ACTIVE DISTRIBUTION SYSTEMS: INTEGRATING BELUGA WHALE OPTIMIZATION, ARTIFICIAL BEE COLONY, AND CUCKOO SEARCH

Abstract

This paper introduces a novel hybrid metaheuristic algorithm, combining Beluga Whale Optimization, Artificial Bee Colony, and Cuckoo Search algorithms, for the efficient computation of Locational Marginal Prices in active distribution systems. This novel methodology addresses the complex interplay of factors influencing LMPs, including system loss minimization, line loading optimization, and generator voltage angle adjustments. The proposed approach offers a more accurate and comprehensive framework for LMP calculation by considering harmonic effects, which are often overlooked in conventional optimal power flow methods. Specifically, it develops a mathematical model for Locational Marginal Price within wholesale electricity markets for distributed generation participants, addressing the crucial yet often understated impact of DG placement on system costs rather than solely focusing on loss calculation. This paper thereby extends previous methodologies that primarily focused on loss minimization or voltage profile improvement, integrating a comprehensive consideration of distributed generation's economic impact on market operations. The integration of these algorithms aims to overcome the limitations of individual metaheuristics, providing a robust solution for optimizing power flow and precisely determining LMPs in deregulated electricity markets .