| dc.description | The purpose of Economic Dispatch or Optimal Dispatch is to reduce fuel costs for power systems. The minimum cost is obtained if the hard constraints and soft constraints are satisfied. The hard constraints imposed on the system can not be violated; however, the soft constraints can be violated to some degree. This violation is related to power system parameters which deal with uncertainty due to fluctuations in model parameters such as load variations, noise in measurements, weather condition changes etc. For this reason there is a need more than ever for a fuzzy model to be developed to overcome this uncertainty. In this thesis the problem of fuzzy optimal economic dispatch and nonlinear optimal power flow optimization under a fuzzy load is introduced and formulated to minimize the total cost production of a network. This thesis implements three methods in formulating the economical dispatch of all thermal power systems. It starts with a simple economic dispatch problem with a fuzzy load demand neglecting transmission losses, but including generation limits. Two generation units are tested for the formulation with various alpha-cut representations of fuzzy numbers in illustrating the evaluation procedure and to evaluate effect of the spread on the outcome. Next a problem with a fuzzy cost function coefficient with fuzzy load demand is analyzed and formulated to minimize the total optimal production cost. To evaluate the performance and the capability of reducing cost while varying cost function coefficients, a synthetic system example of three generation units is used. Finally, a more realistic model with fuzzy load, fuzzy cost function coefficients and power losses is formulated, evaluated and tested on a three generation unit system to obtain the optimal minimum cost. The fuzzy nonlinear optimal load flow is presented when the active generation, active load, reactive generation and reactive load are considered to be fuzzy. Three formulation methods were adopted. First a system with all crisp cost function coefficient with fuzzy active, reactive power is tested on a 9-bus system for one hour. Next a fuzzy load that varies on an hourly basis for 24-hours is tested on the 9-bus system, while keeping the load and generation of the other buses unchanged. Finally, a system with a fuzzy coefficients cost function with fuzzy active and reactive power is formulated and tested to generate a minimum cost function. | en_US |
