Z. Hamid

Optimum tuning of Unified Power Flow Controller via Ant Colony Optimization technique

Unified Power Flow Controller (UPFC) is a Flexible Alternating Current Transmission System (FACTS) device that can control the power flow in transmission lines by injecting active and reactive voltage components in series with the lines using power converter modules, based on an externally dc-link voltage. As the power flow has been controlled, this device is capable of minimizing the overall system losses and simultaneously improves the voltage stability. To be able effectively control the power flow so that losses and voltage stability are at optimum level, UPFC parameters need to be tuned by using optimization algorithm. This paper describes how Ant Colony Optimization (ACO) technique can be used to tune the parameters of FACTS device in order to improve power system performance. ACO is a new cooperative agents approach, which is inspired by the observation of the behaviours of real ant colonies on the topics of ant trial formation and foraging method. The algorithm is implemented in MATLAB applied to the IEEE-30 Bus Reliability Test System (RTS). The results obtained from the study revealed that the proposed technique gave promising results.

Optimal Fuzzy Inference System incorporated with stability index tracing: An application for effective load shedding

The application of fuzzy logic as a decision maker has been widely implemented for solving various engineering problems, especially in the field of voltage stability improvement. Because of this sophisticated tool is very suitable for non-linear system and easy for implementation, many researchers have taken initiative to formulate it according to their point of view. In the meantime, the electricity tracing techniques have also been developed through various theories, nevertheless, only transmission service pricing and electricity deregulation become the subjects of discussion when implementing it. In virtue of that, this paper proposes a new technique for locating the suitable load buses for the purpose of load shedding considering multi-contingencies, that is, by means of stability index tracing. The amount of load power to be shed is determined via a modified version of fuzzy system, which consists of improved membership functions by optimization algorithm. Experiment on IEEE 57-bus and 118-bus reliability test systems (RTS) validates the feasibility of the proposed technique for real system application.

Computational intelligence approach for SVC-PID controller in angle stability improvement

This paper presents a new optimization approach for tuning conventional PID controller parameters of a static var compensator (SVC) which controls a synchronous machine. SVC is designed and implemented to improve the damping of a synchronous generator. Particle Swarm Optimization (PSO) method based PID controller using SVC is implemented in this study. The study involves the optimization of proportional gain, KP, interval gain, KI and derivative gain, KD of PID controller. Validation with respect to eigenvalues determination and damping ratio confirmed that the proposed technique is effective to improve the angle stability problem.

A novel technique for generation tracing via Evolutionary Programming

On account of the inability of transaction based charging method to provide fair and non-discriminatory transmission service pricing, tracing the flow of electricity becomes an essential part in deregulated power system and has attracted many researchers regarding on how to improve and streamline the method of charge allocation. The existing power tracing techniques still necessitate for an assumption and also demands for matrix inversion operation, which has limited their usage especially when the matrix to be inversed is not singular. This paper presents a novel technique for allocating the losses and load powers to all generators by means of Evolutionary Programming (EP) algorithm. The developed algorithm has been experimented on IEEE 57-bus RTS and the results revealed that EP can also be a sophisticated tool to be applied in power tracing field with tolerable computation time.

An evolutionary algorithm approach to design SVC-PI controller for angle stability improvement

This paper presents Evolutionary Programming (EP) based optimization technique for estimating PI controller parameters of a static var compensator (SVC) which controls a synchronous machine. SVC is one type of Flexible AC Transmission Systems (FACTS) device, designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. This paper introduced Evolutionary Programming (EP) optimization method based SVC-PI controller. The study includes the placement of SVC with PI controller, while computational intelligence technique is used in optimizing the parameter values of PI controller: proportional gain, KP and interval gain, KI. Validation with respect to eigenvalues determination and synchronizing and damping torque coefficients (KS and KD) value confirmed that the proposed technique is effective to improve the angle stability problem.

Fuzzy bee colony approach to mitigate congestion problems through TCSC installation for voltage corrective strategy

Application of the viable technologies in the new millennium has discovered successfulness in reducing undesirable problems related to power system operation. The advent of computational intelligence methods are mostly assisting to achieve high efficiency for controlling the changing of sophisticated process flow in industrials. Congestion problem in power system is a crucial issue as it leads to the smoothness of power delivery to the consumer. One of the techniques to alleviate this problem is the installation of Flexible Alternating Current Thyristor into the existing power system network. This paper presents fuzzy bee colony approach to mitigate congestion problems through TCSC installation for voltage control strategy. The bee colony optimization technique (BCO) is used for searching the optimal sizing for TCSC. Validation was conducted using the IEEE 26 Bus Reliable Test System (RTS), particle swarm optimization is used for verification purposes.

Stability index tracing for determining FACTS devices placement locations

Locating the suitable locations in power system for the purpose of Flexible Alternating Current Transmission System (FACTS) devices installation can be realized via wide variety of techniques, and commonly applied by many researchers are sensitivity analysis and optimization approach. On the other hand, there are also various power tracing techniques have been invented by researchers, but their application is only for transmission service pricing. To try a new method for locating the most suitable locations for FACTS devices placement, this paper has invented a new method for ranking the priority of buses, namely Fast Voltage Stability Index Load Tracing (FVSI-LT) via a new hybrid algorithm, Blended Crossover Continuous Ant Colony Optimization (BX-CACO). The method reflects reliable ranking results after comparison with other methods.

Comparative studies between various power tracing techniques for reactive power allocation

The inability of traditional methods in providing fair and non-discriminatory transmission service pricing has attracted many researchers to streamline the existing methods, or invent some methods that can improve the weakness. Transaction based allocation like MW mile, contract path, and postage stamp allocation are the examples of traditional technique applied by many transmission service providers (TRANSCO) for allocating transmission usage cost among consumers; the generation (GENCO) and distribution (DISCO) companies. Unfortunately, such methods ignore the physical power system constraints such as flow, sink and source constraints that should be taken into account when performing the cost allocation. Thus, a method that can accurately determine the cost of utilizing transmission service while satisfying those constraints has been developed, known as power tracing. This paper tries to conduct an investigation on various power tracing techniques that are based on Artificial Intelligence (AI) based optimization, proportional sharing principle (PSP), and circuit theory. Validation has been performed on IEEE 14 bus reliability test system (RTS) and it is revealed that different power tracing techniques provide different reactive power allocation on consumers.

PSS-LL based power system stability enhancement using IPSO approach

This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed with Lead-Lag (LL) controller is introduced to elevate the damping capability of the generator in the low frequency mode. For tuning three PSS-LL parameters, a new Particle Swarm Optimization (PSO) technique called Iteration PSO (IPSO) is proposed. In this method, a new iteration best index is implemented into conventional PSO in order to enhance the quality of the solution. Based on eigenvalues and damping ratio results, it is confirmed that the proposed technique is more efficient than conventional PSO in improving the angle stability of the system. Comparison between IPSO, PSO and Evolutionary Programming (EP) optimization techniques showed that the proposed computation approach give better solution and faster computation time.

Optimal Tuning of SVC-PI Controller using Whale Optimization Algorithm for Angle Stability Improvement

Applied Computing Technology (ACT), Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Department of Management Information Systems, College of Commerce and Business Administrations, Dhofar University, Salalah, Oman.