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Thesis (Master's)

Reykjavík University > Tæknisvið / School of Technology > Med/MPM/MSc Tækni- og verkfræðideild (-2019) / School of Science and Engineering >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1946/31397

  • Smart Reconfiguration of Electric Power Distribution Networks for Power Loss Minimization and Voltage Profile Optimization
  • Master's
  • voltage profile, and increase the power quality. DNR studies require implementation of the power flow analysis and complex optimization procedures capable of handling large combinatorial problems. The size of the distribution network influences the type of the optimization methodtobeapplied. Inparticular,straightforwardapproachescanbecomputationallyexpensive or even prohibitive whereas heuristic or meta-heuristic approaches can yield acceptable results with less computation cost. In this thesis work, a customized evolutionary algorithm hasbeenintroducedandappliedtopowerdistributionnetworkreconiguration. Therecombination operators of the algorithm are designed to preserve feasibility of solutions here, the radial structureofthenetworkthusconsiderablyreducingthesizeofthesearchspace. Consequently, an improved repeatability of results as well as lower overall computational complexity of the optimization process have been achieved. The proposed technique is referred to as feasibility preserving evolutionary optimization FPEO. Another approach is adopted to solve DNR. The method is based on sequential stochastic optimization that utilizes mechanisms adopted from simulated annealing to avoid getting stuck in local minima), and customized network modication procedures that aim at improving the cost function while maintaining the radial architecture of the distribution system. The proposed technique is referred to as feasibilitypreserving simulated annealing(FPSA). Both, FPEO and FPSA are comprehensively validated using three IEEE test cases, 33, 69 and 119-bus systems. At last, a novel algorithm for power loss reduction through distribution network reconguration(DNR) and optimization based allocation of distributed generation (DG) sources is reported. Here, DNR is solved simultaneously with DG allocation. The problem at hand is a complex mixed-integer task. A customized evolutionary algorithm has been developed with recombination operators preserving a radial structure of the network, integer-based operators for DG placement, and floating point operators for handling their power output capacities. Comprehensive numerical validation performed on standard IEEE 33- and 69-bus systems indicates that our methodology outperforms state of the art algorithms available in the literature in terms of the obtained power loss reduction. Furthermore, it features good repeatability of results as demonstrated through statistical analysis of multiple algorithm runs.

  • Mexico´s National Council for Science and Technology-Sustentabilidad Energetica SENER-CONACYT (2016).
  • Jun 21, 2018
  • http://hdl.handle.net/1946/31397

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