Risk based optimization for strategical planning of electrical distribution systems with dispersed generation

Strategical planning for electrical distribution systems is a difficult multi-objective optimisation problem. The formulation adopted in this paper also includes an overloading risk index, which considers the possibility that the obtained solution may not meet the posed technical constraints. The inherent uncertainty of the considered problem, due to the existence of LV dispersed generation units such as micro-turbines or photovoltaic generators, is taken into account by means of a fuzzy formulation of the load density. In presence of dispersed generation, the load density in extended sense also includes the DG units contribution. The solution of this multiobjective optimisation, MO, problem has been carried out by means of a non-dominated sorting genetic algorithm-based approach. Distribution systems design using modular strategical planning indeed requires the minimisation/maximisation of many objects depending on mixed-integer variables. In this paper the concept of modularity has been used in the formulation of the strategical planning of electrical distribution systems. Different scenarios for the DG units penetration has been considered and the obtained results show many innovative and rational design solutions with different costs and risk indices.

[1]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[2]  Eleonora Riva Sanseverino,et al.  NSGA-based multiobjective optimisation for modular strategical planning of electric distribution systems , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).