Editorial
Optimization of Deep Peak Shaving Methods for Fossil Fuel-Based Power Units Using the Improved Energy Consumption Framework
@ARTICLE{10.4108/ew.9811, author={Xing Zhang and Yunlong Zhou}, title={Optimization of Deep Peak Shaving Methods for Fossil Fuel-Based Power Units Using the Improved Energy Consumption Framework}, journal={EAI Endorsed Transactions on Energy Web}, volume={12}, number={1}, publisher={EAI}, journal_a={EW}, year={2025}, month={12}, keywords={Fox Optimization Algorithm, Fossil Fuel-Based Power Units, Demand Response, Thermal Storage, Load Shifting, Peak Demand Management}, doi={10.4108/ew.9811} }- Xing Zhang
Yunlong Zhou
Year: 2025
Optimization of Deep Peak Shaving Methods for Fossil Fuel-Based Power Units Using the Improved Energy Consumption Framework
EW
EAI
DOI: 10.4108/ew.9811
Abstract
The design optimisation of Fossil Fuel-Based Power Plants is critical for improving energy efficiency and minimising environmental impact, particularly amid the increasing global demand for electricity. Fossil fuel plants are vital for supplying energy needs, but are hindered by fuel inefficiency and emissions. The main aim of this research is to improve the performance of such power plants during peak demand hours and to reduce fuel consumption and emissions. The emphasis is placed on maximizing energy generation, enhancing operational effectiveness, and sustainability. The suggested work combines two advanced optimization methods.
Copyright © 2025 Xing Zhang et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
