Yogesh Krishan Bhateshvar

Frequency Stabilization for Multi-area Thermal–Hydro Power System Using Genetic Algorithm-optimized Fuzzy Logic Controller in Deregulated Environment

Abstract—This article develops a model of load frequency control for an interconnected two-area thermal–hydro power system under a deregulated environment. In this article, a fuzzy logic controller is optimized by a genetic algorithm in two steps. The first step of fuzzy logic controller optimization is for variable range optimization, and the second step is for the optimization of scaling and gain parameters. Further, the genetic algorithm-optimized fuzzy logic controller is compared against a conventional proportional-integral-derivative controller and a simple fuzzy logic controller. The proposed genetic algorithm-optimized fuzzy logic controller shows better dynamic response following a step-load change with combination of poolco and bilateral contracts in a deregulated environment. In this article, the effect of the governor dead band is also considered. In addition, performance of genetic algorithm-optimized fuzzy logic controller also has been examined for various step-load changes in different distribution unit demands and compared with the proportional-integral-derivative controller and simple fuzzy logic controller.

Study of impact of wind power penetration on frequency stabilization in multi-area power system

This paper presents a comprehensive study on the wind power impact with increasing penetration on frequency stabilization in restructured power system scenario. The focus of the study is on faster and smoother settlement of frequency and tie-line power. A large penetration of wind power generation causes imbalance in power system because of its intermittent output. The wind power generation system does not provide inertia and isolates from the grid during disturbances but this possibility becomes milder if wind power generators also contribute to system inertia. The proposed control scheme with fuzzy logic uses frequency deviations to provide fast active power support, which blocks the fall in frequency and tie-line power during transient conditions. The simulation studies have been conducted in a two-area interconnected power system in restructured environment.

Comparative dynamic analysis on frequency stabilization for multi-area power system in deregulated environment

This paper attempts to develop a linearized model of load frequency control (LFC) for an interconnected reheat type two-area thermal power system under deregulated environment. A conventional Integral controller is optimized using ISE optimization technique. A comparison between a conventional optimized integral controller and a fuzzy logic based controller is presented and the proposed fuzzy based controller is shown to generate the improved dynamic response following a step load change with combination of poolco and bilateral contracts in deregulated environment. In addition, performance of conventional integral controller and a fuzzy logic based controller is also examined under various changes up to ±30% in system parameters.

Frequency Stabilization for Thermal-Hydro Power System with Fuzzy Logic Controlled SMES Unit in Deregulated Environment

This paper deals with the Automatic Generation Control (AGC) of two-area power system with SMES unit under deregulated environment. PID controller is used for AGC, three different tuning and optimization techniques are analyzed for effectively stabilize the frequency and tie-line power oscillations and these techniques are Ziegler - Nichols tuning (ZN), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Results show PSO is more effective techniques to produce desired response. Superconducting Magnetic Energy Storage (SMES) is also emerging solution for suppression of frequency and tie-line oscillations. This paper also presents fuzzy logic controlled SMES in order to effectively suppress frequency and tie-line power oscillations. The effectiveness of proposed fuzzy logic controlled SMES justified in comparison of proportional plus integral (PI) controlled SMES.

Wind power inertial support for inter-area oscillations suppression with fuzzy controller in varying load conditions

Wind power is emerging renewable energy technology in the recent power system scenario and can be developed as viable options for electricity generation in future. The wind power generation system does not provide inertia and isolates from the grid during disturbances but this possibility will be mitigated if wind power generators also contribute to system inertia. This paper analyses the participation of a doubly fed induction generator based wind turbine in inertial support for reducing frequency and tie-line power oscillations. The proposed control scheme with fuzzy logic uses frequency deviations to provide fast active power support, which arrests the fall in frequency and tie-line power during transient conditions. The simulation studies have been conducted in a two-area interconnected power system in restructured environment to demonstrate the contribution of the doubly fed induction generator in inter-area oscillation suppression.

Ant Colony Optimized Fuzzy Control Solution for Frequency Oscillation Suppression

Abstract This paper presents a novel approach in addressing a critical power system issue, i.e., automatic generation control (AGC) in a smart grid scenario. It proposes the design and implementation of an optimized fuzzy logic controller (FLC) for AGC of interconnected power network. There are three different sources of power generation considered in the two-area interconnected model of power system network. First area is equipped with a single reheat thermal unit and a superconducting magnetic energy storage (SMES) unit, while another area has a hydro-unit with SMES. A multi-stage optimization strategy for the optimal solution of FLC for tie-line and frequency oscillation suppression is proposed in this paper using an ant colony optimization technique. The optimization of FLC is carried out in four different stages. The first stage is the optimization of range of input and output variables; the second stage is the optimization of membership function; the third and fourth stages are the optimization for rule base and rule weight optimization, respectively. The performance of the proposed controller is also compared with another control approaches to stabilize Ptie-line and Δf oscillations; these are the Ziegler–Nichols-tuned proportional–integral–derivative (PID) controller and genetic algorithm optimized PID controller. A comprehensive analysis of the traditional techniques and proposed techniques is presented on the basis of major dynamic performance parameters, i.e., settling time and peak overshoot.

Power-Frequency Balance in Multi-generation System Using Optimized Fuzzy Logic Controller

Abstract This paper emphasizes the development of control strategy for inter-area oscillation suppression for a unified two-area hydro–thermal deregulated power system. A proportional derivative-type fuzzy logic controller with integral (PDFLC+I) controller was proposed for automatic generation control. Further comparisons among conventional integral controller, proportional integral derivative controller, and PDFLC+I are carried out, where the PDFLC+I controller is optimized by four different optimization techniques namely, algorithm, ant colony optimization, classical particle swarm optimization, and adaptive particle swarm optimization. In PDFLC+I controller optimization, scaling parameters of controllers are optimized. A comparative study shows that the proposed PDFLC+I controller has a better dynamic response following a step load change for the combination of PoolCo and bilateral contract-type transaction in deregulated environment. Proposed controller performance has also been examined for ±30% variation in system parameters. Non-linearity in the form of governor dead band is taken into account during simulation.

Power Frequency Oscillation Suppression Using Two-Stage Optimized Fuzzy Logic Controller for Multigeneration System

This paper attempts to develop a linearized model of automatic generation control AGC for an interconnected two-area reheat type thermal power system in deregulated environment. A comparison between genetic algorithm optimized PID controller GA-PID, particle swarm optimized PID controller PSO-PID, and proposed two-stage based PSO optimized fuzzy logic controller TSO-FLC is presented. The proposed fuzzy based controller is optimized at two stages: one is rule base optimization and other is scaling factor and gain factor optimization. This shows the best dynamic response following a step load change with different cases of bilateral contracts in deregulated environment. In addition, performance of proposed TSO-FLC is also examined for ±30% changes in system parameters with different type of contractual demands between control areas and compared with GA-PID and PSO-PID. MATLAB/Simulink® is used for all simulations.

Power frequency balance in multi-generation smart grid system with V2G option

In smart grid scenario, penetration of large scale renewable energy sources are increasing rapidly. This causes uncertainty among various power system parameters, mainly frequency in interconnected power system. When automatic generation control (AGC) is not sufficient to manage balance between demand and supply, battery energy storage is considered a viable option for short term active power support in order to bring frequency back to normal. In energy storage possibilities, super conducting magnetic energy storage, ultra-capacitor etc. are primarily discussed. This paper focuses on integrated model of vehicle to grid (V2G) and wind power as an alternative to supply instant power to regulate frequency when system is subjected to sudden perturbation. GA (Genetic algorithm) optimized fuzzy logic controller is used to intelligently suppress frequency and tie-line power oscillations. Results obtained are comprehensively presented and discussed in achieving power-frequency balance. MATLAB/Simulink is used for the simulation purpose.