Optimal feeder configuration in expansion planning using simulated annealing - Julian, Gonzalo B. Jr. (2006., 2006)
The distribution planning problem with due consideration of existing network configuration is formulated as non-linear constrained, non-differential optimization problem. This is true as there exist already a distribution system and the need for additional capacity requires the provision of new substation and distribution line to meet the forecasted load growth. A new approach for optimal network development in distribution planning will be presented in this research study. The main objective is to minimize the overall cost which is the summation of reliability costs, cost of feeder resistive loss, investment and maintenance costs in order to obtain an optimum feeder configuration for main primary line of the distribution system. Minimum cost analysis requires not only the minimization of feeder losses but should also include an assessment of the costs of providing reliable service and the quantification of the worth having it. The annual expected values of the customer cost of interruption can be added to the annual capital, feeder resistive loss and maintenance costs to form a total cost index for the specified project. Compared to other optimization models, the important task in this work is the inclusion of the worth or value of system reliability to the distribution expansion planning problem. The problem will be modelled as a non-linear, non-differential and constrained optimization problem. A general purpose combinatorial optimization algorithm, simulated annealing will be used to solve the problem. The main advantages of this algorithm are the easiness of the implementation and the ability to include many realistic constraints and non-linear objectives which is true in the case of the distribution planning problem to obtain a global optimal solution. Presented in the thesis is a description of the implementation of this algorithm using various routine codes under the MATLAB environment. Comparison of alternatives are then made on the basis of the total cost. A simple yet effective perturbation mechanism will be introduced to capture all possible configurations of the system within the search space. Control parameters of the simulated annealing algorithm will be initialized and will undergo sensitivity analysis to study their behavior and effect on the convergence to the optimum solution.
"November 2006."
Thesis (M.S. Electrical Engineering)--University of the Philippines Diliman.
Keywords: Electric power systems -- Management -- Simulation methods -- Philippines; Electric power distribution -- Philippines; Electric power system -- Combinatorial optimization; Simulated annealing (Mathematics)