Solving Optimal Power Flow Control Problem Using Honey Formation Optimization Algorithm

This paper introduces three new variations of the HFO-1 (Honey Formation Optimization with Single Component) algorithm, namely HFO-1a, HFO-1b and HFO-1c, adapted to address the optimal power flow (OPF) problem. The original HFO-1 algorithm has shown success in solving various numerical problems in recent years; however, it assumes a single search range for all dimensions of the solution space, making it unsuitable for direct application to the OPF problem. Modifications to both the honey formation and mixing phases of the HFO-1 algorithm were made to improve solution quality and convergence speed, resulting in three new variants of HFO-1. The newly developed variants aim to minimize even the most challenging objective functions of the complex OPF problem, which has been further complicated by the integration of renewable energy sources into power systems. The paper provides a comprehensive and transparent comparison of the three types of IEEE 30-bus test systems and 118-bus test systems with existing methods, meticulously adhering to practical, technical, operational, and safety constraints. Following successful results on the CEC 2021 standard benchmark functions, the proposed HFO-1 variants have been thoroughly validated through extensive analysis. Experimental results demonstrate that the proposed approach can achieve lower costs ($800.5972/hour and $800.3871/hour) in two types of IEEE 30-bus systems without integrating renewable resources while maintaining system constraints. Furthermore, HFO-1a (achieving 3.0776261 MW) and HFO-1b achieve the lowest values in the literature with a multi-fuel cost of (646.375893$/h) and a valve point effective fuel cost of (823.981360$/h), respectively, while HFO-1c exhibits a voltage deviation of (0.083498 p.u.) and Prohibited Operating Zones (POZ) cost of generator (800.665078 /h).