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dc.contributor.supervisor Filizadeh, Shaahin (Electrical and Computer Engineering) Gole, Aniruddha M. (Electrical and Computer Engineering) en_US
dc.contributor.author Yazdanpanah Goharrizi, Ali
dc.date.accessioned 2016-04-05T21:10:01Z
dc.date.available 2016-04-05T21:10:01Z
dc.date.issued 2015
dc.identifier.uri http://hdl.handle.net/1993/31175
dc.description.abstract This thesis proposes a novel algorithm to optimize multi-modal, nonlinear, black-box objective functions for electric power system design using an electromagnetic transients (EMT) simulator. The algorithm discovers multiple local optimal solutions for a given complex power system, and then generates accurate surrogate models of an objective function around each discovered local optimal solution. These surrogate models represent the local behaviour of the objective function that can be used in the subsequent stages of sensitivity analyses. Using surrogate models instead of intensive transient simulation during sensitivity analysis reduces computational intensity and simulation time. This makes the proposed algorithm particularly suited for optimization of computationally expensive black-box functions. The stages of the algorithm can be implemented independently and hence the computations can be done in parallel. Therefore, the algorithm is implemented in a parallel environment to gain significant speed-up in the design of electric power systems. Comparative studies in terms of objective function evaluation and computation time are provided. Using several multi-modal benchmark objective functions, the superiority of the proposed algorithm compared to other recently developed algorithms is demonstrated. Additionally, the application of the algorithm in the design process of complex electric power system demonstrated through several examples. The case studies show that the parallelized algorithm provides computational savings up to 39 times compared to the conventional sequential approach. en_US
dc.publisher IEEE Transaction on Power Delivery en_US
dc.subject power system en_US
dc.subject optimization en_US
dc.subject surrogate model en_US
dc.subject sensitivity assessment en_US
dc.subject parallel algorithm en_US
dc.subject high voltage direct current en_US
dc.subject drive system en_US
dc.title Parallel multi-modal optimal design and sensitivity assessment for electric power systems en_US
dc.degree.discipline Electrical and Computer Engineering en_US
dc.contributor.examiningcommittee McNeill, D (Electrical and Computer Engineering) Anderson, J (Computer Science) Mahseredjian, J (Electrical and Computer Engineering, École Polytechnique de Montréal) en_US
dc.degree.level Doctor of Philosophy (Ph.D.) en_US
dc.description.note May 2016 en_US


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