Multi-area economic emission dispatch for large-scale multi-fueled power plants contemplating inter-connected grid tie-lines power flow limitations. (15th December 2022)

• Record Type: Journal Article
• Authors: Ahmed, Ijaz; Rehan, Muhammad; Basit, Abdul; Malik, Saddam Hussain; Alvi, Um-E-Habiba; Hong, Keum-Shik
• Is Part Of: Energy. Volume 261:Part B(2022)
• Publication Date: 2022-12-15
• Subjects: Valve-point loading effects (VLEs) -- Meta-heuristic approaches -- Fuel cost and emission -- Multiple fueling options (MFOs) -- Prohibited operating zones (POZs) -- Economic load dispatch (ELDs) -- Economic environmental load dispatch (EELDs) -- Multiple area power transfer -- Tie-lines; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.125178
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The purpose of this research is to investigate the multi-area economic emission dispatch problem (MEEDP) in the presence of renewable energy resources (RES) to improve the energy sustainability and climatic benefits. MEEDP is a multi-objective problem in smart grids, with the purpose of minimizing the operating costs and emissions of thermal units. RES have made a substantial contribution to greenhouse gases emission control and environmental sustainability. The integration of RES into conventional grids, which is becoming increasingly prevalent, spread the research scope of MEEDP and needs to be re-examined. This work considers two renewable sources (wind and solar) along with thermal plants subjected to significant number of previously uncombined system level limitations such as power capacity limit, prohibited zones, transmission network losses, dynamic ramp limits, tie-line limits and multiple fueling options. The operating cost is computed as summation of predictive and stochastic components. The predictive part is calculated by utilization of cumulative distribution function for each wind and solar system. A swarm intelligence-based crow search optimization algorithm (CSOA) is modeled to handle the complex constrained MEEDP with adjusted predictive part of RES. Six benchmark test systems with multi-dimensional constraints have been chosen to validate the adaptability and efficacy of the presented approach. Regardless of the complexity of the problem, the proposed approach provides the best feasible solution with a finer convergence rate. Finally, the simulation results depict that the integration of the corresponding system constraints gives legitimacy to the system and delivers reliable output. Highlights: A complex multi-area economic emission dispatch problem is considered. Crow search optimization is applied with straightforward parameter adjustment. Improved results are attained in terms of convergence rate and stability. Low emission profiles in guidance to emission regulatory authorities. Integration of renewable system with conventional thermal plants is considered.