Lahore, Researchers at The University of Lahore (UOL) have developed a ground-breaking algorithm to enhance the integration of renewable energy sources (RESs) into power grids, offering a significant advancement in addressing the combined economic emission load dispatch (CEELD) problem. This development represents a key stride in optimising energy systems for both efficiency and environmental sustainability.
According to The University of Lahore, the research team, led by Dr. Ghulam Abbas, Professor and Head of the Department of Electrical Engineering at UOL, and Mr. Muhammad Waleed Tahir, Lecturer in the Department of Technology at UOL, collaborated with researchers from Taif University, Saudi Arabia, and Qatar University. The team’s work centers on a sophisticated optimization technique known as the flower pollination algorithm (FPA), a bio-inspired metaheuristic algorithm.
The study’s focus was on single CEELD and multi-objective CEELD (MO-CEELD) optimization scenarios. It involved complex test cases with eleven and fifteen thermal units, both with and without the integration of RESs. The challenge was to optimize conflicting objectives of cost and emission simultaneously, which the team addressed effectively using the FPA. Their results demonstrated that the FPA outperformed other established optimization techniques like PSO, DE, GSA, AEO, BA, and dBA in terms of overall fuel and emission cost reduction.
The researchers’ findings indicate that the FPA has superior capabilities in addressing constrained economic emission dispatch problems, especially in scenarios that include conventional thermal generators and non-synchronous energy sources such as RESs. The algorithm’s unique characteristics, including levy-flights-based step size, were pivotal in overcoming premature convergence issues and achieving faster convergence.
Looking ahead, the UOL team suggested further refinement of the algorithm parameters and its application in more realistic scenarios. These include multi-fuel generators, transmission line losses, battery storage systems, and optimal power flow problems. The research also holds potential for extension to scenarios involving doubly-fed induction generators for wind turbines, stand-alone photovoltaic (PV) systems with or without maximum power point trackers, and Flexible AC Transmission (FACT) devices.
This research, funded by Qatar National Library and supported by Taif University, signifies a major breakthrough in energy optimization, with profound implications for developing more efficient and sustainable power grids in the future.