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Strategic multiyear transmission expansion planning under severe uncertainties by a combination of melody search algorithm and Powell heuristic method

Shivaie, Mojtaba, Ameli, Mohammad T.
Energy 2016 v.115 pp. 338-352
algorithms, decision making, electricity, markets, models, planning, risk, system optimization, uncertainty
In this paper, a new strategic multiyear model is presented for Transmission Expansion Planning (TEP) in deregulated environments. This methodology is based on a tri-level decision making whose fundamental elements are pool-based electricity market and strategic behavior of market participants. In addition, to minimize risks of planning arising from severe uncertainties, an information gap decision theory (IGDT) is used. By using the IGDT, the TEP model is formulated for the risk-averse and risk-seeker decision makers through the robustness and opportunity models, respectively. The offered model is formulated as a non-convex mixed-integer non-linear optimization problem. With this regards, a combination of melody search algorithm and improved Powell heuristic method is widely used to determine the optimal solution. The planning methodology has been applied to the IEEE 30-bus test system and to the large-scale Iranian 400-kV transmission grid. Simulation results demonstrate the feasibility and effectiveness of the proposed model, and the fact that it can be profitable for the real-world networks.