Optimized Robust Controller Design Based on CPSOGSA Optimization Algorithm andH₂/H_∞Weights Distribution Method for Load Frequency Control of Micro-Grid

Abstract

In this paper, a mixed H 2 /H ∞ robust control strategy that considers the weights of the H 2 and H ∞ 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 ∞ 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 ∞ 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 ∞ 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 ∞ robust controller, H 2 robust controller, and traditional H 2 /H ∞ robust controller, and the results are very satisfactory.INDEX TERMS Load-frequency control, Islanded micro-grid, Intelligent H 2 /H ∞ robust control, Intelligent optimization algorithm

Adaptive Droop Control Strategy for Load Sharing in Hybrid Micro Grids

“…In order to solve various problems, including stability issues related to microgrid systems, as mentioned earlier, several efforts have been proposed in various papers. Mostly, microgrid systems are integrated with various renewable energy sources and power electronic devices; improved energy storage elements have been incorporated for compensating energy deviations [17]. [15] [16] In this paper, using a combination of two powerful neural network tools and fuzzy logic, intelligentization and adaptation of droop control along with voltage and current control is done as one of the most common methods of decentralized control.…”

Multi-Objective Optimisation-based Robust H∞ Controller Design Approach for a Multi-Level DC-DC Voltage Regulator

“…These approaches with a singleobjective function only optimise parameters depending on the error signal of the measured variable. A H 2 −H∞ robust control method is proposed to optimise the weights of the method using the hybrid particle swarm optimisation and the gravitational search algorithm [30]. A chaos optimisation algorithm-based robust H∞ control design with mixed sensitivity approach is proposed for a piezoelectric actuator system [31].…”

Model Predictive Control–Based Load-Frequency Regulation of Grid-Forming Inverter–Based Power Systems

“…By the virtue of such a digitalization process, various control algorithms (Obaid et al, 2019;Fernández-Guillamón et al, 2019) have been investigated to maintain frequency stability (a priority in power system control). For example, Lyapunov-based stability analysis methods (Jin et al, 2019;Luo et al, 2020;Shang-Guan et al, 2020) are developed to guarantee frequency stability; the H 2 /H ∞ controller (Zou et al, 2021) is designed to optimize the frequency dynamics performance; and a fuzzy event-triggered scheme (Shangguan et al, 2021) is employed to improve frequency control stability with limited communication expense. Moreover, different kinds of control properties can be satisfied in frequency control, that is, asymptotic (Guerrero et al, 2010;Xu et al, 2018;Singhal et al, 2022), finite-time (Zuo et al, 2016;Ge et al, 2020), and fixed-time (Ni et al, 2016), if we can model the system dynamics appropriately.…”

“…On the other hand, owing to the fast response of feedback control methods (Zou et al, 2021;Shangguan et al, 2021;Zuo et al, 2016), control input saturations are considered in the actuation, which would not lead to optimized input sequences. Hence, practical operation constraints, for example, frequency nadir and RoCoF (rate of change of frequency), are essential to be considered in frequency regulation.…”