Xiaoshun Zhang, Tian Tan, Tao Yu, 等. Bi-Objective Optimization of Real-Time AGC Dispatch in Performance-Based Frequency Regulation Market[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(6):2360-2370.
Xiaoshun Zhang, Tian Tan, Tao Yu, et al. Bi-Objective Optimization of Real-Time AGC Dispatch in Performance-Based Frequency Regulation Market[J]. CSEE Journal of Power and Energy Systems, 2024, 10(6): 2360-2370.
Xiaoshun Zhang, Tian Tan, Tao Yu, 等. Bi-Objective Optimization of Real-Time AGC Dispatch in Performance-Based Frequency Regulation Market[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(6):2360-2370.DOI: 10.17775/CSEEJPES.2020.01860.
Xiaoshun Zhang, Tian Tan, Tao Yu, et al. Bi-Objective Optimization of Real-Time AGC Dispatch in Performance-Based Frequency Regulation Market[J]. CSEE Journal of Power and Energy Systems, 2024, 10(6): 2360-2370.DOI: 10.17775/CSEEJPES.2020.01860.
Bi-Objective Optimization of Real-Time AGC Dispatch in Performance-Based Frequency Regulation Market
This paper illustrates a new bi-objective optimization model of real-time automatic generation control dispatch in a performance-based frequency regulation market. It attempts to simultaneously minimize the total power deviation and the regulation mileage payment via optimally distributing the real-time total generation command to different regulation units. To handle this problem
an efficient non-dominated sorting genetic algorithm II is adopted to rapidly obtain a high-quality Pareto front for real-time AGC dispatch. A dynamic ideal point based decision making technique is designed to select the best compromise solution from the obtained Pareto front according to the minimization of the total regulation variation
which can effectively avoid an excessive regulation variation for each unit. Finally
two testing systems are used to verify the performance of the proposed technique.