학술논문

Optimized Robust Controller Design Based on CPSOGSA Optimization Algorithm and H2/H∞ Weights Distribution Method for Load Frequency Control of Micro-Grid
Document Type
Periodical
Source
IEEE Access Access, IEEE. 9:162093-162107 2021
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Frequency control
Optimization
Frequency modulation
Time-frequency analysis
Robust control
Power supplies
Generators
Load-frequency control
islanded micro-grid
H<%2Fitalic>₂%2FH<%2Fitalic>∞+robust+control%22">intelligent H₂/H∞ robust control
intelligent optimization algorithm
Language
ISSN
2169-3536
Abstract
In this paper, a mixed $H_{2}/H_{\infty }$ robust control strategy that considers the weights of the $H_{2}$ and $H_{\infty }$ norm in the optimization process is proposed, and it is used to solve the load frequency control (LFC) problem of the micro-grid (MG). The MG load frequency model established in this paper includes battery energy storage system (BESS), fuel cell (FC), wind turbine (WT), photo-voltaic (PV), and diesel engine generator (DEG). The optimal mixed $H_{2}/H_{\infty }$ robust controller takes the minimum square integral of the system’s frequency fluctuation as the goal of control optimization by integrating the robust performance expressed by the $H_{2}/H_{\infty }$ two norms. The hybrid particle swarm optimization and gravitational search algorithm with chaotic map algorithm (CPSOGSA) is used to optimize the weight value reflecting the $H_{2}$ and $H_{\infty }$ performance of the system and the evaluation function’s weighting matrix of the output performance so that the controller can reach the optimum under the constraints. Simulation experiments show that the robust controller designed by the proposed method has better dynamic performance when compared with $H_{\infty }$ robust controller, $H_{2}$ robust controller, and traditional $H_{2}/H_{\infty }$ robust controller, and the results are very satisfactory.