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Distribution systems analysis and optimization Ahmadi, Hamed


Distribution systems (DS) are the last stage of any large power system, delivering electricity to the end-users. Conventionally, simplicity of DS operation has been a priority over its optimality. However, with the recent advancements in the automation and measurement infrastructures, it is now possible to improve the efficiency of DS operation. In this dissertation, a load modeling procedure is proposed which takes advantage of the data available at the smart meters. An algorithm is proposed to decompose the load at each customer level using the smart meter measurements. The proposed load model represents the voltage dependence of loads according to the load composition. Based on the voltage-dependent load model, a linear power flow formulation is developed for DS analysis. The linear current flow equations are then proposed which calculate the branch flows directly without requiring the nodal voltages. Sensitivity factors in terms of current transfer and branch outage distribution factors are also derived using the linear power flow concept. The advantages of having a set of linear equations describing the system statics are demonstrated in a variety of DS optimization problems, such as topological reconfiguration, capacitor placement, and volt-VAR optimization. Using the linear current flow equations, the mixed-integer nonlinear programming problem of DS reconfiguration is reformulated into a mixed-integer quadratic/linear programming problem, which substantially reduces the computational burden of the nonlinear combinatorial problem. Besides developing a direct mathematical optimization approach, a fast heuristic method is also developed here for the minimum-loss network reconfiguration based on the minimum spanning tree problem. This heuristic method provides a good suboptimal solution to initialize the direct mathematical optimization approaches such as branch-and-cut algorithm used for solving combinatorial problems. Based on planar graph theory, an efficient mathematical formulation for the representation of the radiality constraint in reconfiguration problems is introduced. It is shown that this formulation is advantageous over the available methods in terms of accuracy and computational efficiency. The proposed algorithms are tested using a variety of DS benchmarks and promising results are achieved.

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