In the ever-evolving landscape of energy production, balancing the generated power with load demand remains a significant challenge, particularly as renewable energy sources like photovoltaic (PV) systems become more integrated into power grids. A recent study led by Serdar Ekinci from the Department of Computer Engineering at Batman University, Turkey, introduces a promising solution to this issue through a novel hybrid algorithm designed for load frequency control (LFC) in a two-area power system.
The research, published in the journal “Results in Engineering,” presents the hybrid educational competition optimizer with pattern search (hECO-PS) algorithm. This innovative approach aims to fine-tune a cascaded proportional-derivative with filter and proportional-integral (PDN-PI) controller, enhancing the stability and reliability of power systems that incorporate both PV and reheat thermal power sources.
Ekinci’s study demonstrates that the hECO-PS algorithm significantly improves the performance of the PDN-PI controller during various operational scenarios, including sudden load changes and fluctuations in solar radiation. In tests, the hECO-PS-tuned controller achieved an integral of time-weighted absolute error (ITAE) value of just 0.4464, markedly better than traditional methods, such as the modified whale optimization algorithm and the sea horse algorithm, which recorded ITAE values of 2.6198 and 0.8598, respectively.
The implications of this research are substantial for the energy sector. By reducing settling time by as much as 46% and minimizing overshoot by up to 40%, the hECO-PS algorithm not only enhances frequency regulation but also contributes to more efficient management of energy resources. This efficiency is particularly crucial as the world transitions towards greater reliance on renewable energy, where fluctuations in power generation can lead to instability.
Ekinci states, “The results confirm the efficacy of the proposed approach in enhancing system stability and reliability under dynamic operating conditions.” This indicates that the hECO-PS algorithm could be a game-changer for energy companies looking to optimize their operations in a market increasingly driven by renewable energy integration.
As power systems continue to evolve, the commercial opportunities for adopting such advanced control strategies are significant. Energy providers can leverage these findings to improve grid reliability, reduce operational costs, and enhance the overall performance of renewable energy systems. The advancements presented in this study not only pave the way for more resilient energy infrastructure but also highlight the importance of innovative algorithms in addressing the complexities of modern power systems.
