engleski

Facing uncertainties in log-term distribution planning methods based on evolutionary algorithms

Electric utilities are nowadays operating in an increasingly challenging economic environment. Consequently, financial requirements and constraints imposed on utilities call for prudent investments. Long-term distribution system planning is a complex combinatorial optimization problem. In this sense the inclusion of risk in a decision making process is not straight forward. To clarify this matter, fuzzy sets based approach for handling uncertainties is presented which is used in long-term planning methods based on evolutionary algorithms devised by the Authors. The proposed methods can cope with important features such as uncertainty in loads, tentative distributed generation, changes in prices and costs, etc. Planning under uncertainty looks for the solution aimed at not only optimal but also robust decisions. In other words, the solution is expected not only to be economical and technically desirable, but also to perform well in any plausible future or, at least, to be sufficiently flexible when facing any unpredictable future. The model and evolutionary algorithms have been applied intensively to real life power distribution systems showing its potential applicability to large scale systems. 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.

planning; primary distribution system; uncertainty; fuzzy sets; evolutionary algorithms

nije evidentirano