ABSTRACT
Power engineers are constantly trying to develop multi-dimensional objectives for power networks. But as the numbers of constraints are increasing day by day, it has become a mammoth task to reach an optimum solution with classical techniques. In an endeavour optimize system performance the work presented in this chapter has been dedicated to the search for multiobjective solution algorithms to present-day power network problems like loss of sustainability, line congestion and cost volatility with the effective utilization of expert systems like genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE) and by the development of indices like security sensitivity index (SSI) and overloading index (OI). Deregulated power networks are concerned with producing cost-effective power; thus, any kind of network perturbation has to be treated as an economic perturbation. Hence, different perturbation measurement indices such as value of lost load (VOLL), value of congestion cost (VOCC) and value of excess loss (VOEL) have been developed in this chapter to expand a multiobjective cost-constrained deregulated power network.
