4.8 Article

Improved Sliding Mode Design for Load Frequency Control of Power System Integrated an Adaptive Learning Strategy

Journal

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 64, Issue 8, Pages 6742-6751

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2017.2694396

Keywords

Adaptive dynamic programming (ADP); disturbances and uncertainties; load frequency control (LFC); particle swarm optimization (PSO); slidingmode control (SMC)

Funding

  1. National Natural Science Foundation of China [51529701, 61520106009]
  2. U.S. National Science Foundation [ECCS 1053717, CMMI 1526835]
  3. Tianjin Natural Science Foundation [14JCQNJC05400]

Ask authors/readers for more resources

Randomness from the power load demand and renewable generations causes frequency oscillations among interconnected power systems. Due to the requirement of synchronism of the whole grid, load frequency control (LFC) has become one of the essential challenges for power system stability and security. In this paper, by modeling the disturbances and parameter uncertainties into the LFC model, we propose an adaptive supplementary control scheme for the power system frequency regulation. An improved slidingmode control (SMC) is employed as the basic controller, where a new sliding mode variable is specifically proposed for the LFC problem. The adaptive dynamic programming strategy is used to provide the supplementary control signal, which is beneficial to the frequency regulation by adapting to the real-time disturbances and uncertainties. The stability analysis is also provided to guarantee the reliability of the proposed control strategy. For comparison, a particle swarm optimization-based SMC scheme is developed as the optimal parameter controller for the frequency regulation problem. Simulation studies are performed on single-area and multiarea benchmark systems, and comparative results illustrate the favorable performance of the proposed adaptive approach for the frequency regulation under load disturbances and parameter uncertainties.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available