Minea Skok

Genetic algorithm and GIS enhanced long term planning of large link structured distribution systems

In order to enhance the serviceability in the distribution system genetic algorithm and GIS based method is proposed in this article for planning the link distribution networks. All practical issues such as cost parameters (investments, line losses, maintenance), and technical constraints (voltage drop, thermal limit, reliability) as well as physical routing constraints (obstacles, high cost passages, existing line sections) are taken into consideration. Fuzzy set concept and scenario representation (tree of futures) to model uncertainties, as well as decision making guided by a paradigm of multi-criteria risk analysis are discussed. The merits of the approach are discussed by analyzing its application to a study case based on a real case in a Croatian utility.

The genetic algorithm method for multiple depot capacitated vehicle routing problem solving

Many organizations face the problem of delivering goods from a certain number of warehouses to a number of retail sites using a fleet of vehicles. The multiple depot capacitated vehicle routing problem is mathematical model that closely approximates the problem faced by many of these organizations. Because the problem is NP-hard, requiring excessive time to be solved exactly, we develop a heuristic based on a genetic algorithm that finds high quality solutions in a reasonable amount of computer time. Basic GA procedures adapted to a given problem are presented and six versions of crossover operators are compared. The test results reveal that the method is able to produce results of a kind that are not easily obtained, namely in terms of the amount of information about the solutions and the solution space.

Artificial immune systems in solving routing problems

Successful planning of electrical distribution networks is a complex problem. Besides the well-known radial network layout, in Europe, particularly in Croatia, the distribution networks are also loop or link structured. In order to be solved, network optimization problem is translated into some known combinatorial problems. When networks are loop-structured, the traveling salesman problem (TSP) is commonly used. The combinatorial problems like TSP cannot be solved exactly and evolutionary algorithms have been successful in solving these problems. Although, they are shown as very efficient, progress is still expected concerning the stability and lesser dependency on input parameters. In addition, evolutionary techniques for solving combinatorial problems often do not pay attention to existing knowledge about the problem. An improvement of the classic genetic algorithm used for solving the TSP is shown here, inspired by artificial immune systems techniques. Special attention is also paid to object-oriented design of the application and achieved benefits.

Dynamic planning of medium voltage open-loop distribution networks under uncertainty

An efficient method to address the multistage planning of open loop structured mv distribution networks under uncertainty, taking into account distributed generation connected to distribution system, has been proposed. The fuzzy model can cope with important features implicit in planning studies such as time-phased representation, consideration of conflicting objectives and uncertainty in loads, distributed generation and economic data. Using two evolutionary algorithms simultaneous optimization of costs and the reliability is achieved. Thus, in addition to optimal radial layout along several stages in time, the algorithm can determine the optimal locations of reserve feeders that achieve the best network reliability with the lowest expansion and operational costs. The model and evolutionary algorithms have been applied intensively to real life power distribution systems showing its potential applicability to significantly larger systems than those frequently found in literature about dynamic distribution networks planning. Results have illustrated the significant influence of the uncertainties in the optimal distribution network planning mainly in terms of topology and supply capacity of the resulting optimal distribution system

The impact of reliability indices in the process of planning radial distribution networks

The work reported in this paper covers some problems regarding radial distribution network planning. Beside the common optimization criteria (new facility installation, maintenance and operation costs), the cost of the energy not supplied caused by expected outages is introduces. The expected outage time is determined in the reliability analysis in which reliability indices SAIFI (system average interruption frequency index) and SAIDI (system average interruption duration index) are calculated. The influence of network topology and switching devices configuration on system reliability is also described. A program module has been developed as a proposal to solving the problem of radial distribution network planning in rural areas. The program module is based on Prim minimum spanning tree algorithm. It is intended to become a part of software tools collectively referred CADDiN (computer aided design of distribution networks).