Hybridized gravitational search algorithm tuned sliding mode controller design for load frequency control system with doubly fed induction generator wind turbine

Abstract

Summary In this paper, the load frequency regulation problem of 2‐area interconnected power system is resolved using the sliding mode control (SMC) methodology. Interconnected 2‐area power systems with and without doubly fed induction generator wind turbines are considered for implementing the proposed optimal control methodology. Here, a heuristic gravitational search algorithm (GSA) and its variants such as opposition learning–based GSA (OGSA), disruption‐based GSA (DGSA), and disruption based oppositional GSA (DOGSA) are employed to optimize the switching vector and feedback gains of SMC. In order to overcome the inherent chattering problem in SMC, the control signals are considered in the objective function. The robustness of optimized SMC is analyzed by the inclusion of nonlinearities such as generation rate constraint (GRC), governor deadband, and time delay during the signal processing between the control areas, which are present in the real‐time power system. The insensitiveness of the optimal controller is shown by variation in system parameters like loading condition, speed governor constant, turbine constant, and tie‐line power coefficient. Further, the optimal SMC has been studied with significant load variations and wind power penetration levels in the control areas. The potential of proposed SMC design with chattering reduction feature is shown and validated by comparing the results obtained with the other reported methods in the literature.

Load frequency predictive control for power systems concerning wind turbine and communication delay

“…Based on all above derivations, the optimization problem in this article is accessible to be formulated as below min 𝛾,K,P,X,S 𝛾 k , s.t. (13), ( 21), (24).…”

A Super Twisting Fractional Order Terminal Sliding Mode Control for DFIG-Based Wind Energy Conversion System

“…where P is the active power injected into the grid given in Equation (35) and is shown in Figure 6a. The wind, P w , is calculated as follows:…”

“…Classical adapted non-overlapped, fixed, and adjacent horizon adaptation time windows have been revisited with an appropriate receding horizon to model the disturbances and uncertainties due to gusty wind effects. A hybrid SMC has been proposed in [35] through the combination of gravitational search algorithm, its variants, and SMC for DFIG-based WECS. In order to reduce the inherent chattering in the conventional SMC, the author considered the control signals as an objective function [36].…”

“…power injected into the grid given in Equation(35) and is shown in Figure6a. The wind, , is calculated as follows:= (51)where is the density of air, is the wind speed, and is the wind turbine rotor area.…”

Design and performance analysis of elephant herding optimization based controller for load frequency control in thermal interconnected power system

“…Several meta‐heuristic optimization methods are applied as the tuning methods for the controllers of LFC and are reported in different literature. Some of the relevant methods are genetic algorithm, 18 particle swarm optimization (PSO), 19 differential evolution (DE), 11 firefly algorithm, 20 bacteria foraging optimization algorithm, 21 bat algorithm, 22 teacher‐learner‐based optimization (TLBO), 23 Jaya algorithm, 10 gray wolf optimization (GWO), 24 ant‐lion optimization, 25 gravitational search algorithm, 26 moth‐flame optimization, 27 and so on. Some reports in literature concentrated on load side primary frequency control 28‐30 while some others on distributed frequency control 31,32 and optimal frequency control 33 .…”