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Jahromi M.E.,Islamic Azad University at Tehran | Ehsan M.,Sharif University of Technology | Meyabadi A.F.,Hamadan University of Technology | Niknam T.,Shiraz University of Technology
International Journal of Innovative Computing, Information and Control | Year: 2012

This paper presents a short term multi-objective planning model for Distributed Generators (DGs) deployment in an electrical network. "Total Cost" and "Emission Cost" are two objective functions which have been going to be minimized in this model by finding the optimal schemes of sizing, placement and DG technologies over a short planning period (static planning). The proposed model can be used for a long term planning period (dynamic planning) in order to consider the timing concept. An interactive fuzzy satisfying method based on Chaotic Local Search and Modified Honey Bee Mating Optimization (CLS-MHBMO) is used to choose the final solution. The effectiveness of the proposed model and search method are assessed and demonstrated by various studies on an actual distribution network. © 2012 ICIC International. Source


Meyabadi A.F.,Hamadan University of Technology | Ehsan M.,Sharif University of Technology
Journal of Intelligent and Fuzzy Systems | Year: 2013

This paper proposes a new technique to manage congestion in a short-run market model. The method consists of an iterative algorithm to search and apply a sequence of bilateral power exchanges among the generators that would optimally reduce and completely remove the congestions. A combination of fuzzy decision principle and sensitivity analysis is developed to choose the best exchange and AC load flow is used to apply it on the network in the iterations. The effectiveness of the proposed approach is illustrated in a case study on IEEE 118-bus system, and results are discussed in the paper in comparison with the mathematical and evolutionary-based optimization techniques. © 2013 - IOS Press and the authors. All rights reserved. Source


Medi B.,Hamadan University of Technology | Monzure-Khoda K.,Qatar University | Amanullah M.,Qatar University
Industrial and Engineering Chemistry Research | Year: 2015

This work presents experimental implementation of an improved single-column chromatographic (ISCC) separation process and its optimizing controller. A mixture of guaifenesin enantiomers has been used to evaluate the performance and integrity of (i) the ISCC process and its online monitoring system in open-loop experiments and (ii) the model predictive optimizing controller for closed-loop operation. The open-loop operation has been particularly aimed at assessing the accuracy and precision of the online monitoring system. In the closed-loop operation, the performance of the developed model predictive control (MPC) scheme has been tested for set point tracking and disturbance rejection with an objective function that reflects the process economics. The online optimal operating condition was also compared to the offline optimum condition obtained using a genetic algorithm. Results confirm that the optimizing controller is adequate to operate and maintain the ISCC process at an optimal operating point while fulfilling the product requirements. © 2015 American Chemical Society. Source


Modirrousta A.,Hamadan University of Technology | Sohrab M.,Malek-Ashtar University of Technology | Dehghan S.M.M.,Malek-Ashtar University of Technology
Transactions of the Institute of Measurement and Control | Year: 2016

In this paper, a solution for the problem of uncertainty presence in the estimated position of a target is indicated. The dynamic error of ground moving target tracking with special unknown bounded uncertainty has been described. To solve this problem, a class of the second-order sliding mode has been proposed. In order to increase the robustness of the proposed controller against unknown uncertainty, a set of adaptive rules has been added to the guidance law. New adaptive terms have been used to estimate the higher unknown bound of the uncertainty. The offered method, based on the sliding mode strategy, has reduced the chattering phenomena, which is harmful for the production of the command states. Finally, a fast adaptive guidance law has been added and its stability has been proved by the Lyapunov criterion. The designed adaptive fast guidance law improves the classical sliding mode control guidance law. Various simulations and comparison studies have been applied to verify the efficiency of the modified guidance law despite the disturbance and uncertainty. The results show that the uncertain terms have been compensated and the tracking position has been satisfied accurately. © SAGE Publications. Source


Rafiee Z.,Bu - Ali Sina University | Meyabadi A.F.,Hamadan University of Technology
International Journal of Power and Energy Conversion | Year: 2012

In power system, the application of the power system stabiliser (PSS) has been proved to overcome the stability of power system. It is necessary to determine the appropriate PSS parameters. In this paper, a new cost function is presented for the tuning of PSS parameters. Optimisation of PSS parameters has been done by particle swarm optimisation algorithm. The power plant system that is simulated in this paper is one machine to infinite bus system. The responses of the PSS tuned with PSO and conventional power system stabiliser (CPSS) are compared with together. Copyright © 2012 Inderscience Enterprises Ltd. Source

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