Recent research published in ‘Scientific Reports’ presents an innovative approach to enhancing power quality in renewable energy systems. The study, led by Koganti Srilakshmi from the Department of Electrical and Electronics Engineering at Sreenidhi Institute of Science & Technology, focuses on the integration of renewable energy sources—specifically wind and solar power—into the distribution network. This integration is crucial as the growing reliance on renewable sources can lead to power quality (PQ) challenges that affect the stability and efficiency of electrical systems.
The research introduces a hybrid system that combines a shunt active power filter with an Energy Storage System (ESS), a Wind Energy Generation System (WEGS), and a Solar Energy System. Unlike many previous methods that employ complex techniques like the synchronous reference frame (SRF) and active-reactive power (pq) approaches, this study simplifies the process by utilizing a neural network (NN) for generating reference signals. This not only streamlines the integration of renewable sources but also enhances performance.
One of the standout features of this research is the use of the horse herd optimization algorithm to optimally select parameters for the system, including those for the proportional-integral controller (PIC) and various converters. This optimization leads to improved performance in stabilizing the voltage across the DC bus capacitor, reducing total harmonic distortion (THD), and enhancing the overall power factor. The study reports impressive THD values of 3.69%, 3.76%, and 4.0%, all of which are significantly lower than those achieved by traditional methods and are well within IEEE standards.
The implications of this research are substantial for commercial sectors involved in renewable energy and power electronics. As governments and industries increasingly prioritize sustainable energy solutions, the ability to efficiently integrate these sources while maintaining high power quality will be essential. The proposed system not only addresses current challenges but also opens avenues for further innovation in energy management systems.
Koganti Srilakshmi emphasizes the significance of their findings, stating, “The proposed method achieves superior performance under varying demand and PV irradiation conditions, which is critical for real-world applications.” This adaptability is particularly important for businesses looking to invest in renewable energy technologies, as it ensures reliable performance even in fluctuating environmental conditions.
As the demand for cleaner energy solutions continues to rise, the methodologies and technologies developed in this research could play a pivotal role in shaping the future of energy systems, providing commercial opportunities for companies engaged in developing and deploying renewable energy technologies.
