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Transmission Expansion Planning for Implementing Distant Wind Power Plants

Moeini Aghtaie, Moein | 2010

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 40823 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Abbaspour Tehrani Fard, Ali; Fotuhi Firuzabad, Mahmud
  7. Abstract:
  8. Increasing the fuel cost and concerns about pollutions have facilitated the use of renewable energies. Wind power as a renewable energy has been considered as a good representative for conventional resources of electrical energy. The biggest obstacles for efficient use of the wind energy are changeability and uncontrollability in wind farm generation and to be far from the demand center. Also, conventional approaches cannot be applied to analyze the effects of this energy on power system. With increment in the penetration of the wind energy in power system, the necessity of considering its effects, especially large scale wind farm, in transmission expansion planning (TEP) studies is inevitable. Transmission lines are one of the most important components of power system. In deregulated environments, they have a very impressive role in competition between market members. Therefore, planning studies for expansion of transmission network should improve the competitiveness of the market. In this thesis, a multi-objective (MO) optimization TEP algorithm is proposed in deregulated electrical market environment considering wind farm generation and load as probabilistic uncertainties. The objective functions used in this study are investment cost, customer outage cost and total congestion cost. The combination of Monte Carlo simulation and Point Estimation Method are implemented to consider the effects of the network uncertainties including wind farm generation and load in optimal power flow (OPF) studies. For evaluation of the MO optimization problem, the non-dominated sorting genetic algorithm (NSGA II) is used because of its comparative assessment potential, good handling of the non-convex problems and non-commensurable objective functions. Eventually, for selecting of the final optimal solution, a Fuzzy decision making approach has been used base on decision maker view. In order to analyze the effects of the large scale wind farm generation changes in TEP and feasibility of proposed algorithm, three different cases has been considered for the IEEE 24-Bus test system and in each case, this algorithm has been applied after implementing the required changes.
  9. Keywords:
  10. Multiobjective Optimization ; Uncertainty ; Active Learning ; Wind Farms ; Transmission Expansion Planning ; Non-Dominate Sorting Genetic Algorithm (NSGAII) Method

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