Ebrahim Zare juybari

Work place: Mazandaran university of science and technology (USTMB), Babol, Mazandaran,Iran

E-mail: ebrahim.zare.juybari@gmail.com


Research Interests: Engineering


Ebrahim Zare juybari received B.Sc degree from University of Mazandaran, Iran in 2011, he received M.Sc degree from University of Science and Technology, iran in 2013 . Currently, he is Research on calculation of transient flow in high-voltage lines.

Author Articles
Optimization of Microgrid Using Quantum Inspired Evolutionary Algorithm

By Ebrahim Zare juybari Seyed Mehdi Hosseini

DOI: https://doi.org/10.5815/ijisa.2014.09.06, Pub. Date: 8 Aug. 2014

This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization scheme as well as reducing the emissions of a MicroGrid (MG). In this article a microgrid including a wind turbine, pv array and a CHP system consisting of fuel cells and a microturbine is studied and then the modeling of various DERs is conducted and the objective functions and constraints are developed. The model takes into consideration the operation and maintenance costs as well as the reduction in emissions of NOx, SO2, and CO2 In the end the Quantum-Inspired Evolutionary Algorithm is employed to solved the optimal model and an operation scheme is achieved while meeting various constraints on the basis of tariff details, equipment performance, weather conditions and forecasts, load details and forecasts and other necessary information and then the economic costs and environmental impacts are analyzed and a conclusion that the QEA can achieve high environmental benefits and spend as low operation cost as possible. according to power Output functions and cost function of the various units , can be achieve to minimize cost.

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Scheduling of Generating unit commitment by Quantum-Inspired Evolutionary Algorithm

By Ebrahim Zare juybari Seyed Mehdi Hosseini

DOI: https://doi.org/10.5815/ijmecs.2014.07.08, Pub. Date: 8 Jul. 2014

An Quantum-Inspired Evolutionary Algorithm (QEA) is presented for solving the unit commitment problem. The proposed method has been used to achieve the schedule of system units by considering optimal economic dispatch. The QEA method based on the quantum concepts such as Q-bit, present a better population diversity compared with previous evolutionary approaches, and uses quantum gates to achieve better solutions. The proposed method has been tested on a system with 10 generating units, and the results shows the effectiveness of algorithm compared with Other previous references. Furthermore, it can be used to solve the large-scale generating unit commitment problem.

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