Cad system for perspective power supply network development task solution

The process of urban power supply network development is connected with need calculation and accounting a large number of parameters, possible development ways and complexity of their assessment. These circumstances require the introduction of new technologies for solving specified task. Declaration of author’s developed computer-aided design system (CAD system) ELNET for the task solution automation of perspective urban power supply network development is presented in article. Description of models, methods and algorithms based in the CAD system are given. CAD allows to create, correct, calculate parameters, look through and print models of urban power supply networks. ELNET consists of six connected modules: graphic module, control module (dispatcher), input/output module, solutions module, calculations module, reference data base. System possesses the friendly graphical interface allowing ease using. In CAD ELNET mathematical basis puts designed by author mathematical model of urban power supply network presentation as directed weighted graph and two methods of solving urban power supply network development task: the reduction method to the set of enclosed global minimization tasks and decomposition method. Both methods suggest dividing a given task into three subtasks of smaller dimension: 1. Subtask of definition the number and locations of new substations. 2. Subtask of definition the connection way of new consumers to network. 3. Subtask of definition the optimum connection way of new substations to the existing network. The optimization algorithms of subtasks solution are realized by the author. For solving subtask 1 three algorithms are designed and realized: algorithm based on the k-averages method; algorithm realizing the method of dividing clustering; heuristic algorithm. For solving subtask 3 three algorithms are also offered: heuristic algorithm of the reduced enumeration; genetic algorithm; algorithm based on constructing Voronoi diagrams. To solve subtask 3 the genetic algorithm is applied. Technical solutions represented in the article allow reducing time of design and increasing the quality of design decisions.