In the rapidly evolving landscape of energy distribution, a groundbreaking study led by Bilal Naji Alhasnawi from the Department of Fuel and Energy Techniques Engineering at Al-Furat Al-Awsat Technical University in Kufa, Iraq, is set to revolutionize how we manage and optimize our power grids. The research, published in ‘Results in Engineering’, delves into the intricate world of Distribution Networks (DNs), focusing on the integration of renewable energy sources and energy storage systems with Distributed Generating Units (DGs).
At the heart of this study is the development of a smart charging method for Plug-in Hybrid Electric Vehicles (PHEVs) designed to maximize the use of Renewable Energy Resources (RERs) and Distributed Energy Resources (DERs). This innovative approach aims to reduce the reliance of Microgrids (MGs) on the main grid, a significant step towards more sustainable and efficient energy management. “The idea is to create a more autonomous and resilient energy system,” Alhasnawi explains, “one that can better integrate renewable energy sources and reduce our dependence on traditional power grids.”
The research doesn’t stop at smart charging. It also addresses the optimal operation of lithium-ion batteries, a critical component in modern energy storage systems. By enhancing the technical, financial, and environmental performance of both independent and grid-connected distribution networks, this study paves the way for more efficient and eco-friendly energy solutions.
One of the most compelling aspects of this research is the introduction of advanced optimization techniques. The study employs the Mountain Gazelle Optimizer (MGO), Improved Beluga Whale Optimization (IBWO), and Arithmetic Optimization Algorithm (AOA) to determine the optimal placement of DGs in radial distribution systems. These algorithms are not just theoretical constructs; they have been rigorously tested on real-world systems, namely the IEEE 33-bus and IEEE 85-bus networks.
The results are nothing short of impressive. In the IEEE 33-bus network, the MGO algorithm achieved a staggering 25.43% reduction in CO2 emissions and a 22.69% reduction in power losses. Similarly, in the IEEE 85-bus network, the MGO algorithm demonstrated a 23.27% reduction in CO2 emissions and a 19.48% reduction in power losses. These findings underscore the potential of these optimization techniques to significantly enhance the efficiency and sustainability of our energy infrastructure.
The commercial implications of this research are vast. For energy providers, the ability to optimize DG placement and reduce power losses translates to substantial cost savings and improved service reliability. For consumers, it means more stable and environmentally friendly energy supply. As Alhasnawi notes, “This research is a step towards a future where our energy systems are not only more efficient but also more sustainable and resilient.”
The study’s findings, published in ‘Results in Engineering’, offer a glimpse into the future of energy distribution. By integrating advanced optimization algorithms and smart charging methods, we can create a more efficient, sustainable, and resilient energy infrastructure. This research is a testament to the power of innovation in addressing some of the most pressing challenges in the energy sector. As we move towards a future dominated by renewable energy sources, studies like this will be instrumental in shaping the landscape of energy distribution.
