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Florida Atlantic University
College of Engineering & Computer Science
Announces the
Ph.D. Dissertation Defense
of
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Hadis Moradi
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for the Degree of
Doctor of Philosophy (Ph.D.)
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DISSERTATION TITLE: "Optimal Energy Scheduling of a Hybrid Microgrid Considering Environmental Aspects"
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Tues., Nov. 7 at 10 a.m.
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Florida Atlantic University
777 Glades Road, EE 405
Boca Raton Campus
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DEPARTMENT: Computer and Electrical Engineering and Computer Science
CHAIR OF THE CANDIDATE’S PH.D. COMMITTEE: Amir Abtahi, Ph.D.
PH.D. SUPERVISORY COMMITTEE:
Ali Zilouchian, Ph.D.
Vichate Ungvichian, Ph.D.
Roger Messenger, Ph.D.
Dolores De Groff, Ph.D.
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ABSTRACT OF DISSERTATION
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Lower costs of clean energy generation, the need for a more secure grid, and environmental concerns are leading to create more opportunities for integration of renewable energy resources utilization in the power systems. The recent concept of Microgrid (MG), as a part of the development of smart grid, is required to integrate the renewable sources in the utility grid. An MG is described as a small-scale distribution grid that consists of diversified Distributed Energy Resources (DERs), Battery Energy Storage Systems (BESSs), and local flexible loads that typically can either be operated in islanded or grid-connected modes. The optimal utilization control of such an MG system is a challenging task due to the complexity of coordination among the DERs, BESSs and load management possibilities. Therefore, in this thesis, optimal component sizing and micro-gas turbines, fuel cells, batteries and other dispatchable generating units.
Firstly, a methodology to perform the optimal component sizing for DERs in island/grid-tied modes is developed. The proposed optimal algorithm aims to determine the appropriate configuration among a set of components by taking into consideration the system’s constraints. An Iterative optimization technique is proposed in order to minimize the annual cost of energy and cost of emissions including CO2, SO2, and NOx. A case study is selected from South Florida area, and local weather data and load demand are employed in the modeling. Using the results from optimal component sizes, a day-ahead optimization problem for the operation of an MG under different scenarios is introduced. Also, the objective function is formulated as a constrained non-linear problem. The uncertainties of stochastic variables (solar radiation, wind speed, and load) are modeled using probabilistic models and renewable generations and load demand are forecasted for the next day. An advanced dynamic programming procedure is proposed to assess various operational policies. The simulation results show the efficiency of the proposed method.
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BIOGRAPHICAL SKETCH
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- Born in Iran
- B.S. 2008, Ahvaz University, Ahvaz, Iran
- M.S. 2011, Tarbiat Modares University, Tehran, Iran
- Ph.D. 2017, Florida Atlantic University, Boca Raton, Florida
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CONCERNING PERIOD OF PREPARATION & QUALIFYING EXAMINATION
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Time in Preparation: 2014 - 2017
Qualifying Examination Passed: Spring 2014
Selected Published Papers:
H. Moradi, M. Esfahanian, A. Abtahi, and A. Zilouchian, "Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties", Energies, 10(9), 1430, 2017.
H. Moradi, A. Abtahi, and A. Zilouchian, "Optimization and energy management of a stand-alone hybrid microgrid in the presence of battery storage system", Energy Journal, Elsevier, 2017. (In press)
H. Moradi, A. Abtahi, and D. D. Groff, "Optimal Energy Scheduling of a Stand-alone Multi-Sourced Microgrid Considering Environmental Aspects", IEEE Innovative Smart Grid Technologies Conference, Washington DC, 2017.
H. Moradi, A. Abtahi, and R. Messenger, Annual Performance Comparison Between Two Solar Tracker and Fixed Grid-Tied Arrays, 43rd IEEE Photovoltaic Specialist Conference, Portland, USA, June 2016.
H. Moradi, A. Abtahi, and M. Esfahanian , Optimal Operation of a Multi-Sourced Microgrid to Achieve Cost and Emission Targets, IEEE Power and Energy Conference at Illinois (PECI), pp. 1-6, Urbana, IL, 2016.
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777 Glades Road, EE 308, Boca Raton, FL 33431-0991•
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