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Hajar Bagheri Tolabi

Bio: Hajar Bagheri Tolabi is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Genetic algorithm & Control reconfiguration. The author has an hindex of 6, co-authored 14 publications receiving 274 citations.

Papers
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Journal ArticleDOI
TL;DR: The results proved that simultaneous reconfiguration and optimal allocation of PV array and DSTATCOM unit leads to significantly reduced losses, improved VP, and increased LB.
Abstract: In this paper, a combination of a fuzzy multiobjective approach and ant colony optimization (ACO) as a metaheuristic algorithm is used to solve the simultaneous reconfiguration and optimal allocation (size and location) of photovoltaic (PV) arrays as a distributed generation (DG) and distribution static compensator (DSTATCOM) as a distribution flexible ac transmission system (DFACT) device in a distribution system. The purpose of this research includes loss reduction, voltage profile (VP) improvement, and increase in the feeder load balancing (LB). The proposed method is validated using the IEEE 33-bus test system and a Tai-Power 11.4-kV distribution system as a real distribution network. The results proved that simultaneous reconfiguration and optimal allocation of PV array and DSTATCOM unit leads to significantly reduced losses, improved VP, and increased LB. Obtained results have been compared with the base value and found that simultaneous placement of PV and DSTATCOM along with reconfiguration is more beneficial than separate single-objective optimization. Also, the proposed fuzzy-ACO approach is more accurate as compared to ACO and other intelligent techniques like fuzzy-genetic algorithm (GA) and fuzzy-particle swarm optimization (PSO).

204 citations

Journal ArticleDOI
15 Jul 2020-Energy
TL;DR: The TPA performance was assessed by solving a discrete-continuous optimization problem in distribution networks and the results reveals that the TPA outperforms its counterparts in solving the mentioned problem.

40 citations

Journal ArticleDOI
15 Jul 2014-Energy
TL;DR: In this article, a hybrid optimal multi-objective reconfiguration method was proposed to determine an optimal size and location of multiple-distributed generation (DG) in a distribution feeder.

35 citations

Journal ArticleDOI
TL;DR: A novelty bees algorithm estimation based on a linear empirical model is developed that eliminates the training stage and therefore reduces the complexity rather than simulated models yet offers high accuracy estimation.
Abstract: SUMMARY This paper introduces a new classification scheme for the solar radiation estimation techniques based on three categories: empirical models (based on statistical regression techniques), simulated models (based on training), and optimized models (based on optimization algorithms). For the optimized model category, a novelty bees algorithm estimation based on a linear empirical model is developed. Eight different methods from three classes have been tested on three sample geographic positions of Iran in order to compare the efficiency, complexity, sensed parameters, and required prior training of each category with others by implementing in the Matlab software. Among all tested models, the best properties are obtained for optimized empirical models by optimization algorithms. The main advantages of this model type are that it eliminates the training stage and therefore reduces the complexity rather than simulated models yet offers high accuracy estimation. Copyright © 2014 John Wiley & Sons, Ltd.

19 citations

Journal ArticleDOI
TL;DR: In this paper, a new method based on the empirical equations is introduced to estimate the monthly average daily global solar radiation (GSR) on a horizontal surface, which uses Bees algorithm as a heuristic and population-based search technique.
Abstract: Measurement of solar radiance demands expensive devices to be used. Alternatively, estimator models are used instead. In this article, a new method based on the empirical equations is introduced to estimate the monthly average daily global solar radiation (GSR) on a horizontal surface. The proposed method uses Bees algorithm as a heuristic and population-based search technique. The best coefficients of linear and nonlinear empirical models and GSR are calculated for seven different climate regions of Iran using proposed algorithm written in MATLAB software. The results of the proposed method are compared with other techniques. The result shows that the proposed method is more accurate in estimating the monthly average daily GSR. © 2013 American Institute of Chemical Engineers Environ Prog, 33: 1042–1050, 2014

14 citations


Cited by
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01 Jan 2015

976 citations

Journal ArticleDOI
TL;DR: In this article, a comprehensive review and critical discussion of state-of-the-art analytical techniques for optimal planning of renewable distributed generation is conducted, and a comparative analysis of analytical techniques is presented to show their suitability for distributed generation planning in terms of various optimization criteria.

327 citations

Journal ArticleDOI
TL;DR: The results proved that simultaneous reconfiguration and optimal allocation of PV array and DSTATCOM unit leads to significantly reduced losses, improved VP, and increased LB.
Abstract: In this paper, a combination of a fuzzy multiobjective approach and ant colony optimization (ACO) as a metaheuristic algorithm is used to solve the simultaneous reconfiguration and optimal allocation (size and location) of photovoltaic (PV) arrays as a distributed generation (DG) and distribution static compensator (DSTATCOM) as a distribution flexible ac transmission system (DFACT) device in a distribution system. The purpose of this research includes loss reduction, voltage profile (VP) improvement, and increase in the feeder load balancing (LB). The proposed method is validated using the IEEE 33-bus test system and a Tai-Power 11.4-kV distribution system as a real distribution network. The results proved that simultaneous reconfiguration and optimal allocation of PV array and DSTATCOM unit leads to significantly reduced losses, improved VP, and increased LB. Obtained results have been compared with the base value and found that simultaneous placement of PV and DSTATCOM along with reconfiguration is more beneficial than separate single-objective optimization. Also, the proposed fuzzy-ACO approach is more accurate as compared to ACO and other intelligent techniques like fuzzy-genetic algorithm (GA) and fuzzy-particle swarm optimization (PSO).

204 citations

Journal ArticleDOI
TL;DR: It can be observed on benchmark test functions that PFA is able to converge global optimum and avoid the local optima effectively and show that it can approximate to true Pareto optimal solutions.

200 citations

Journal ArticleDOI
TL;DR: In this article, the existing research works on DG allocation problem are reviewed from viewpoint of their used optimisation algorithms, objectives, decision variables, DG type, applied constraints and kind of uncertainty modelling.
Abstract: Distributed generation can be defined as power generation by small scale generating units that are installed at distribution systems. The penetration of distributed generation (DG) units in electric distribution systems is continually increasing. The process of finding optimal type, location and size of DG units is called “DG allocation”. DG allocation is a hot area of research and represents a difficult problem in electrical power engineering. In this paper, the existing research works on DG allocation problem are reviewed from viewpoint of their used optimisation algorithms, objectives, decision variables, DG type, applied constraints and kind of uncertainty modelling. Based on the review of existing research works, the research gaps are identified and some helpful recommendations for future research on DG allocation will be provided. The author strongly believes that this paper can be helpful for researchers and engineers in the related field.

182 citations