Optimal Short-Term Reactive Power Scheduling Based On The Genetic Algorithm

The aim of this work is to develop an optimal short-term scheduling of reactive power in electric distribution systems. To do this, some decision analysis needs to undertake regarding to economic and security aspects. These decision analysis need to consider the physical constraints existing within power systems, such as the generation and transmission limits. An objective function is used that takes into account the security aspects, as well as the physical constraints, and the probabilistic nature of reactive power controllers. The target of this research is to determine the proper settings of the control devices (capacitor banks and transformer taps) for the 24 hours in the next day, which minimize the active power losses (reducing the cost) without exceeding the allowable number of movements of the control devices per day, and maintaining satisfactory voltage profile under various loading conditions. The objective function is then optimized (economically) by use of the Genetic Algorithm -a new-age tool that is relatively less computationally intensive than other optimization techniques, and is capable of optimizing complicated functions. The GA algorithm is implemented in two levels. At the first level, a GA is implemented to determine the optimal reactive power dispatch (optimal settings of control devices) for each operating hour in the day, and then at the second level, another GA is implemented again to find the final optimal reactive power dispatch for the whole day. The proposed method was applied to a modified IEEE 30-bus power system to show the feasibility and the capability of the proposed method. The experiment was carried out and the results are presented in this thesis.