Affiliation:
1. School of Electric Power Engineering South China University of Technology Guangzhou China
Abstract
AbstractAs the proportion of renewable energy penetrated in power systems further increases, the optimal operation faces a large obstacle to satisfying various conflict interests simultaneously. This paper first formulates a many‐objective optimal operation problem of the new power system considering a comprehensive set of economic, environmental, and reliable objectives. To figure out this problem efficiently, this paper proposes a probability confidence correlation analysis method (PCCA) utilizing a t‐distributed stochastic neighbor embedding (T‐SNE) standard to greatly preserve the distribution information and separability of the objectives. Consequently, the objectives can be aggregated and the objective dimension is reduced based on the important sorting and correlation of the objectives. Based on the outcome of the T‐SNE, the adopted optimal operation problem with low dimensional objectives is solved by a multiple producer group search optimizer (GSOMP) with less computation burden, to obtain the Pareto‐optimal solution set. Simulation studies are conducted on IEEE 30‐bus, 39‐bus and 57‐bus systems to investigate the performance of the proposed PCCA in terms of efficiency and accuracy, making comparisons of the existing many‐objective optimization algorithms.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
Publisher
Institution of Engineering and Technology (IET)
Subject
Renewable Energy, Sustainability and the Environment
Reference54 articles.
1. IEA:World energy outlook 2022(2022)
2. Optimal design for a multi‐level energy exploitation unit based on hydrogen storage combining methane reactor and carbon capture, utilization and storage;Zheng J.;J. Storage Mater.,2023
3. Multi‐objective optimal dispatch in wind power integrated system incorporating energy‐environmental efficiency;Chen D.;Proc. CSEE,2011
4. A gradient descent direction based‐cumulants method for probabilistic energy flow analysis of individual‐based integrated energy systems;Zheng J.;Energy,2023
5. A fuzzy‐optimization approach for generation scheduling with wind and solar energy systems;Liang R.‐H.;IEEE Trans. Power Syst.,2007