In a significant stride towards optimizing power systems and integrating renewable energy sources, researchers have developed a novel approach to tackle two critical power system optimization problems simultaneously: Combined Heat and Power Economic Dispatch (CHPED) and Optimal Power Flow (OPF). This breakthrough, published in the journal *Nature Scientific Reports*, could have profound implications for the energy sector, particularly in enhancing efficiency and sustainability.
The study, led by Susanta Dutta from the Department of Electrical Engineering at Dr. B. C. Roy Engineering College, focuses on the IEEE-57 bus and IEEE 118-bus power networks. The primary objective was to determine the OPF of the CHPED problem on these systems. By integrating renewable energy sources such as wind, solar, and electric vehicles (EVs), the researchers aimed to reduce fuel costs, emissions, active power loss (APL), aggregated voltage deviation (AVD), and voltage stability index (VSI).
The researchers employed a sine-cosine algorithm (SCA) embedded with quasi-oppositional based learning (QOBL), termed QOSCA, to balance exploration and exploitation abilities. This method was chosen to overcome the shortcomings of traditional optimization techniques and provide global optimal solutions. “The QOSCA method has shown remarkable robustness and efficiency in handling complex power systems,” Dutta explained. “It not only reduces the computational time but also ensures a more sustainable and cost-effective operation of the power grid.”
The numerical analysis revealed impressive results. For the IEEE 57 bus and IEEE 118-bus systems, the integration of wind, solar, and EV led to a 21% reduction in generation cost, a 17.5% reduction in emissions, and a 0.17% to 2.59% reduction in APL. When applied to a multiobjective function considering AVD and VSI, the QOSCA method achieved a 0.37% reduction in AVD and a 0.24% reduction in VSI. “These reductions are significant and demonstrate the superiority of the QOSCA method over conventional optimization techniques,” Dutta added.
The study also highlighted the computational efficiency of the QOSCA method, which was found to be 24% faster than traditional methods in complex systems. This efficiency is crucial for real-time decision-making and operational planning in the energy sector.
The implications of this research are far-reaching. By optimizing power flow and integrating renewable energy sources, the energy sector can achieve greater sustainability and cost-effectiveness. The QOSCA method offers a robust and efficient solution for managing the complexities of modern power systems, paving the way for a more resilient and environmentally friendly energy infrastructure.
As the energy sector continues to evolve, the integration of renewable energy sources and advanced optimization techniques will play a pivotal role in shaping the future of power generation and distribution. This research not only contributes to the academic community but also provides practical insights for industry professionals seeking to enhance the performance and sustainability of their operations.