Ismail Musirin

Novel fast voltage stability index (FVSI) for voltage stability analysis in power transmission system

Since a couple of decades ago, voltage stability assessment has received increasing attention due to the complexity of power systems. With the increase in power demand and limited power sources has caused the system to operate at its maximum capacity. Therefore, a study that is able to determine the maximum capacity limit before voltage collapse must be carried out so that necessary precaution can be taken to avoid system capacity violation. This paper presents a novel fast voltage stability index (FVSI) simplified from a pre-developed voltage stability index referred to a line initiated from the voltage quadratic equation at the sending end of a representation of a 2-bus system. The line index in the interconnected system in which the value that is closed to 1.00 indicates that the line has reached its instability limit which could cause sudden voltage drop to the corresponding bus caused by the reactive load variation. The formulated index was tested on the IEEE reliability test system in order to verify the performance of the proposed indicator. Results showed that the proposed technique is indicative in predicting the occurrence of system collapse and hence necessary action can be taken to avoid such incident.

Optimal allocation and sizing of embedded generators

Recent years, the number of embedded generators installed in distribution system has been increasing in many parts of the world. Depending on their operating characteristics and locations, embedded generators could significantly affect the voltage profile, network losses and fault level in a distribution system. This paper presents a new technique for determining optimal allocation and sizing of embedded generator in a distribution system. Sensitivity indices based on voltage stability improvement with respect to change in injected active and reactive power at a load bus were derived and used to identify the suitable location for the embedded generators. In order to determine the optimal output of the embedded generators, an evolutionary programming optimization technique was developed with an objective to minimize the distribution losses while satisfying the voltage constraint in the system. The proposed technique was tested on the 69 bus distribution system and the results shown a significant reduction in distribution losses and voltage profile improvement in the system with the implementation of the embedded generation at the suitable location and optimal sizing.

On-line voltage stability based contingency ranking using fast voltage stability index (FVSI)

Voltage instability is one phenomenon that could happen in a power system due to its stressed condition. The result would be the occurrence of voltage collapse which leads to total blackout to the whole system. Therefore voltage collapse prediction is important in power system planning and operation so that the occurrence of voltage collapse due to voltage instability could be avoided. Line outage in a power system could also lead to the event of voltage collapse which implies the contingency in the system. Line outage contingencies are ranked so that the line which highly affects voltage stability of the system when there is an outage occurs in this line could be identified. The contingency ranking process can be conducted by computing the line stability index of each line for a particular line outage and sort them in descending order. The contingency which is ranked highest implies that it contributes to system instability. This paper presents a new voltage stability index refers to a line namely fast voltage stability index (FVSI). The values of the line indices indicate the voltage stability condition in the system and it is used to rank the line outage contingency. The information from the contingency ranking denotes the severity of the voltage stability condition in a power system due to line outage. The proposed contingency ranking technique was tested on an IEEE reliability test system.

Optimal sizing and operational strategy of hybrid renewable energy system using homer

Nowadays, the power system utility has started to consider the green power technology in order for the world to have a healthier environment. The wind energy and solar energy system are chosen in designing a hybrid renewable power system as they do not release any emission to the atmosphere. In addition, by maximizing the use of the renewable energy, the diesel generator used in the system could also be reduced. Therefore, this paper will discuss on the optimization of the renewable energy hybrid system based on the sizing and operational strategy of generating system. The optimization software used in this analysis is the Hybrid Optimization Model for Electric Renewable (HOMER). The sensitivity analysis is also performed to obtain the optimal configuration of hybrid renewable energy based on different combinations of generating system.

Artificial immune-based optimization technique for solving economic dispatch in power system

This paper presents an Artificial Immune-based optimization technique for solving the economic dispatch problem in a power system. The main role of electrical power utility is to ensure that electrical energy requirement from the customer is served. However in doing so, the power utility has also to ensure that the electrical power is generated with minimum cost. Hence, for economic operation of the system, the total demand must be appropriately shared among the generating units with an objective to minimize the total generation cost for the system. Economic Dispatch is a procedure to determine the electrical power to be generated by the committed generating units in a power system so that the total generation cost of the system is minimized, while satisfying the load demand simultaneously. The proposed technique implemented Clonal Selection algorithm with several cloning, mutation and selection approaches. These approaches were tested and compared in order to determine the best strategy for solving the economic dispatch problem. The feasibility of the proposed techniques was demonstrated on a system with 18 generating units at various loading conditions. The results show that Artificial Immune System optimization technique that employed adaptive cloning, selective mutation and pair-wise tournament selection has provided the best result in terms of cost minimization and least execution time. A comparative study with λ-iteration optimization method and Genetic Algorithm was also presented.

Fuzzy logic controller on DC/DC boost converter

This paper describes the design of a fuzzy logic controller using voltage output as feedback for significantly improving the dynamic performance of boost dc-dc converter by using MATLAB@Simulink software. The objective of this proposed methodology is to develop fuzzy logic controller on control boost dc-dc converter using MATLAB@Simulink software. The fuzzy logic controller has been implemented to the system by developing fuzzy logic control algorithm. The design and calculation of the components especially for the inductor has been done to ensure the converter operates in continuous conduction mode. The evaluation of the output has been carried out and compared by software simulation using MATLAB software between the open loop and closed loop circuit. The simulation results are shown that voltage output is able to be control in steady state condition for boost dc-dc converter by using this methodology.

Transmission loss minimization using SVC based on Particle Swarm Optimization

This paper describes optimal sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. Particle Swarm Optimization (PSO) is one of the artificial intelligent search approaches which has the potential to solve such a problem. For this study, static var compensator (SVC) is chosen as the compensation device. Validation through the implementation on the IEEE 26-bus system shows that the PSO is found feasible to achieve the task. The simulations results are compared with those obtained from the Bee Algorithm (BA) technique in the attempt to highlight its merit.

Optimal Location and Sizing of SVC Using Particle Swarm Optimization Technique

This paper describes optimal location and sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. Particle Swarm Optimization (PSO) is population-based stochastic search algorithms approaches as the potential techniques to solving such a problem. For this study, static var compensator (SVC) is chosen as the compensation device. Validation through the implementation on the IEEE 30-bus system indicated that PSO is feasible to achieve the task. The simulation results are compared with those obtained from Evolutionary Programming (EP) technique in the attempt to highlight its merit.

Sizing grid-connected photovoltaic system using genetic algorithm

This paper presents an intelligent-based algorithm for sizing grid-connected photovoltaic (GCPV) system using Genetic Algorithm (GA). GA had been used to determine the optimal PV module and inverter from pre-developed PV module and inverter databases such that the expected technical performance of the design could be optimized. In addition, the technical sizing outputs such as the number of photovoltaic (PV) modules, PV array configuration and inverter-to-PV array sizing factor were computed. The GA had outperformed the Evolutionary Strategies (ES) during the sizing process in terms of producing better optimum results. Low error had also been produced by GA when compared to a benchmark sizing algorithm using iterative sizing approach.

PSO based technique for loss minimization considering voltage profile and cost function

This paper describes optimal sizing of FACTS devices based on Particle Swarm Optimization for minimization of transmission loss considering voltage profile and cost function. Particle Swarm Optimization (PSO) is one of the artificial intelligent search approaches which have the potential in solving such a problem. In this study one of FACTS devices is used as a scheme for transmission loss. For this study, static var compensator (SVC) is chosen as the compensation device. The effect of population size during the optimization process towards achieving the solution is also investigated. Validation through the implementation on the IEEE 30-bus RTS indicated that PSO is feasible to achieve the task.