The IJPEAI Journal
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| Home Volume 1 Volume 2 Volume 3 ISSN: 1985-6431 | |
| Volume > Volume 3, Number 1, December 2009 | |
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The IJPEAI Journal |
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Board of International Reviewers:
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Comparison of Particle Swarm Optimization
and Genetic Algorithm to
Optimal Control of Proton Exchange Membrane Fuel
Cell
A. Rezazadeh, M. Sedighizade, A. Askarzadeh | |
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Abstract: Since the operation of a Proton Exchange Membrane Fuel Cell (PEMFC) is extremely nonlinear process as well as its parameters change when it is operating, a designer can’t easily to control it; accordingly conventional controllers can not satisfy the control objectives as well as the intelligent controllers. Thus, in this paper an intelligent controller is proposed for fuel cell stack control system based on Particle Swarm Optimization (PSO). In order to analyze the efficiency of this method, the results are compared with other intelligent controller based on Genetic Algorithm (GA). The simulation results demonstrate the high-performance capability of both proposed controllers in terms of accuracy and convergence speed. Index Terms: |
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Implementation of Autoregressive (AR) Method to Pre-Filter the Set of Measurements |
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Abstract: This paper describes an approach to identify and change the measurement weights used in Weight Least Square (WLS) estimation method employed in State Estimation (SE). The individual measurement is assigned with their own weighting factor based on technical experience by the engineers. However, ents could occur in a real time system. Thus, the higher weighting factor or wrongly assigned weighting factor to the measurement could lead to flag the measurement as bad. This paper describes a pre-screening process to identify the bad measurements and the measurement weights before WLS estimation method employed in SE is performed. The autoregressive (AR) method proposed in this paper is used to predict the data and at the same time filtering the logical weighting factors that have been assigned to the identified bad measurements. The AR algorithms known as Burg and Modified Covariance (MC) are used to calculate the one-step-ahead of the predicted values of the state variables. The performance of the AR filter is tested using 5-bus, IEEE 14-bus, IEEE 24-bus, IEEE 57-bus, IEEE 118-bus, IEEE 300-bus system and local utility network consisting 103-bus. Simulation results are presented and compared with the measured values to validate the proposed method. Index Terms: State Estimation (SE), Weight Least Square (WLS), Autoregressive (AR), Burg algorithm, Modified Covariance (MC) algorithm. |
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An Improved Power Quality Scheme Using High Frequency Link AC/AC Converter K.Samidurai, K.Thanushkodi |
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Abstract: This Paper deals with the digital simulation of an electronic transformer based voltage regulator which improves the quality of power supplied by the utility. The regulator proposed is simulated using MATLAB / SIMULINK. It is found that the proposed scheme has superior operating and performance characteristics, particularly on the aspects of power quality, energy saving and efficiency unlike the conventional triac based schemes. Simulation results show that the improvement in performance with respect to input power factor and reduction of total harmonic distortion in output voltage resulting in improved power quality. The discontinuity caused by the conventional regulators in the load voltage to obtain variable AC voltage can be reduced to an appreciable extent using the proposed scheme. Index Terms: electronic voltage regulator (EVR), input power factor (PF), total harmonic distortion (THD), power quality (PQ) |
A Concept Relation Sub Graph in Semantic Web using Genetic Algorithm U.K.Sridevi, N.Nagaveni |
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Abstract : The development of search algorithms between web pages is motivated by the “related pages” queries of web search engines and web document classification. This paper proposes a method for preserving the relations between the concepts by using genetic algorithm based edge removal algorithm. The goal is to provide optimal concept relation graph based on keywords given by the user and comparing the solution from well known traditional keyword search method. The genetic algorithm based edge removal method removes the edges from the concept relation and generates the keyword relation pair. The retrieval model is based on the important factors of the structural elements, which are used to rerank the document retrieval by the standard weighting scheme. The structural field weights are combined with the annotation-weighting scheme to improve the relevance measures. The proposed method has been evaluated on USGS Science directory collection. Using Jena SPARQL query model and GATE Tool API, the documents can be retrieved from the corpora not only based on their textual content but also according to their annotation features and relations. The documents that are annotated with the concepts are retrieved with higher ranking. A preliminary experiment result shows that the proposed method may generate relevant document in the top rank. Index Terms : Semantic Web, Genetic Algorithm, Ontology, Information Retrieval, Semantic Annotation. |
Optimal Multi-type FACTS Allocations in Deregulated Electricity Market Using Bees Algorithm for Generation Cost Reduction R.Mohamad Idris, A.Khairuddin, M.W.Mustafa |
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Abstract : This paper presents the application of Bees Algorithms (BA) technique to find the optimal number and location of Flexible AC Transmission System (FACTS) devices to achieve the power system economic generation in deregulated electricity market. Using the proposed method, the location, types, and ratings of FACTS devices are optimized simultaneously. Different kinds of FACTS devices, namely TCSC, SVC and TCPST, are tested in this study. While finding the optimal location, line thermal limits, voltage limits and FACTS operation limits are taken as constraints in the operation of the system. In order to demonstrate the effectiveness of the algorithm in reducing the overall system cost function, IEEE9 Bus and IEEE30-Reliability Test system are used. A Genetic Algorithm (GA) technique is used for validation purposes. The simulation results validate the capability of this new approach in minimizing the overall system cost function, which comprises of the investments costs of FACTS devices and generation cost and are encouraging for further improvements for application in deregulated electricity market. Index Terms :
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Performance of Fast Voltage Stability Index (FVSI) as an indicator for Under Voltage Load Shedding Scheme in a Bulk Power System Network A. Ramasamy , R. Verayiah, H. I. Zainal Abidin,I. Musirin, A. A. Rahim |
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Abstract : The power system is always exposed to possible risk of instability including voltage stability. Voltage stability can be mitigated by various means which include switching in of reactive power support, tap changing transformers and also increase of generator excitation. However, these mitigating actions could also lead to a more detrimental voltage instability scenario. Hence the last possible mitigating action in this case would be using Under Voltage Load Shedding (UVLS) schemes. The research proposes to utilize an established index called FVSI (Fast Voltage Stability Index) to act as an indicator for Under Voltage Load Shedding (UVLS) locations for a large test system. The research work done shows that the FVSI index can be used as an indicator for UVLS relay location. The FVSI index is capable to identify critical areas in a large power system. Thus, load shedding at these points does improve the stability of the system and it is also shows the improvement of FVSI index during post shed conditions. Index Terms :
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Full Recovery of Transmission System Fixed Cost in Pool Electricity Market M.A. Almaktar, M. Y. Hassan, M. P. Abdullah, F. Hussin, M. S. Majid |
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Abstract: This paper presents the reliability of different usage-based methods for transmission cost allocation under open access. The study is based on generalized generation distribution factors algorithm (GGDF), Bialek and Kirschen tracing algorithms and graph theory. MW-Mile and Postage-Stamp (P.S) methods are also investigated to cover the total transmission system fixed cost among all network users. Numerical example based on 6-bus system is used to demonstrate the fairness of different usage allocation methods in recovery of the total transmission fixed cost in pool electricity market. The results obtained show that the GGDFs method can provide a good tool for dealing with transmission pricing for pool electricity market. Index Terms: Open access, pool market, usage allocation methods, transmission cost, MW-Mile method, Postage-Stamp method. |
Unit commitment by Lagrangian Relaxation Incorporating Optimal Power Flow by Particle Swarm Optimization K.Vaisakh, L. R. Srinivas |
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Abstract: In this paper Lagrangian Relaxation (LR) has been applied to unit commitment (UC) problem incorporating optimal power flow (OPF) by particle swarm optimization (PSO). The proposed method is a blend of LR and PSO. The UC problem is handled by LR, while PSO solves the OPF problem. Problem formulation takes into consideration the minimum up and down time constraints, start up cost, spinning reserve, generation limits, ramp rate constraints and power flow constraints. Problem formulation, representation and the simulation results for a 24 bus, 10 generator system are presented. Index Terms: Unit commitment (UC), Lagrangian Relaxation (LR), optimal power flow (OPF), particle swarm optimization (PSO). |
