H. D. Mathur

A comprehensive analysis of intelligent controllers for load frequency control

This paper presents summaries of novel approaches of artificial intelligence (AI) techniques, like fuzzy logic, artificial neural network (ANN), hybrid fuzzy neural network (HFNN), genetic algorithm (GA) for the load frequency control of electrical power system. The limitations of conventional controls such as proportional, integral and derivative are slow and lack of efficiency in handling system nonlinearities. Since high frequency deviation may lead to system collapse, this necessitates an accurate and fast acting controller to maintain the constant nominal system frequency. The intelligent controllers are used for load frequency control for the single area system, multi area interconnected system. The performance of intelligent controllers with the conventional controllers has been thoroughly compared and analyzed

Frequency stabilization using fuzzy logic based controller for multi-area power system

In this paper, a fuzzy logic controller is proposed for load frequency control problem of electrical power system. The fuzzy controller is constructed as a set of control rules and the control signal is directly deduced from the knowledge base and the fuzzy inference. The study has been designed for a two area interconnected power system. A comparison among a conventional proportional integral (PI) controller, some other fuzzy gain scheduling controllers and the proposed fuzzy controller is presented and it has been shown that proposed controller can generate the best dynamic response following a step load change. Robustness of proposed controller is achieved by analyzing the system response with varying system parameters.

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.

A Novel Approach for Load Frequency Control of Interconnected Thermal Power Stations

This paper presents a fuzzy logic controller for load frequency control (LFC) of multi-area interconnected power system. The study has been designed for a three area interconnected thermal power stations with generation rate constraint (GRC). Simulation results of the proposed fuzzy controller are presented and it has been shown that proposed controller can generate the good dynamic response following a step load change. Robustness of proposed controller is achieved by analyzing the system response with varying system parameters.

Multi-objective differential evolution application to irrigation planning

In the present study, applicability of Multi-objective Differential Evolution (MODE) in irrigation planning perspective is demonstrated through a case study of Mahi Bajaj Sagar Project, Rajasthan, India. Three objectives, namely, net benefits, agricultural production and labour employment are analysed in the multi-objective environment. Non-dominated alternatives generated by MODE are reduced to a manageable subset with the help of K-means cluster analysis for effective decision making. Optimal number of groups is determined based on the cluster validation indices, namely, Davies–Bouldin and Dunns. It is concluded that selection of suitable parameters is necessary for effective implementation of above methodologies in real-world planning situations.

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.

Enhancement of power system quality using distributed generation

The global demand for energy is increasing at a breathtaking pace. This sharp increase in world energy demand will require significant investment in new power generating capacity and grid infrastructure. Considering the present energy scenario and the degrading environmental conditions, distributed generation seems to be a promising option. Distributed Generation generally refers to small-scale electric power generators that produce electricity at a site close to customers or that are tied to an electric distribution system. The power grid is currently facing tremendous changes in the way the energy is produced, transmitted and consumed. The increasing number of actors and the demand for more and more complex services to be provided by the grid exceed the capabilities of todays control systems. This paper gives an overview of the changes that the power system is undergoing and how these affect the aspects of communication, ancillary services, voltage regulation and losses and harmonics.

Extended Fuzzy Logic Based Integral Controller for Three Area Power System with Generation Rate Constraint

In this paper, a fuzzy logic controller is proposed for load frequency control problem of electrical power system. The fuzzy controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. The study has been designed for a three area interconnected power system with generation rate constraint. Simulation results of the proposed fuzzy controller are presented and it has been shown that proposed controller can generate the best dynamic response following a step load change. Robustness of proposed controller is achieved by analyzing the system response with varying system parameters.

Identification of optimal locations of PMUs for WAMPAC in smart grid environment

In recent years, implementation of smart grid technologies has been a prime focus in many countries. To have an accurate and precise information of vital power system parameters, PMUs play a major role in the wide area monitoring, protection and control (WAMPAC) of a smart grid. The placement of phasor measurement units (PMU) in electric transmission system has gained a lot of importance. This paper addresses the various aspects of optimal PMU placement using binary integer linear programming(BILP). Cases with and without zero injection buses have also been considered. Minimum PMU placement problem may have multiple solutions, therefore, two indices viz. BOI (Bus Observability Index) and SORI (System Observability Redundancy Index) have been proposed to further rank these solutions. Results on IEEE 14, 24, 30 and NE 39 bus systems have been presented. Simulation results show that the proposed algorithm can be used efficiently in optimal PMU placement.