Research On The Practical Model And Heuristics Hybrid Intelligent Algorithm Of Dynamic Reactive Power Optimization

This thesis was supported in part by the National Natural Science Foundation of China ("model and intelligent algorithm of fuzzy dynamic reactive power optimization in alternating and direct current system",No. 50577073) and the key project in Chongqing electric power corporation ("study on the development of controlling system of dynamic reactive power optimization in reginal power grid"). The model and corresponding optimization algorithm of dynamic reactive power optimization are studied in detail in this paper.In power system, dynamic reactive power optimization is an essential measure to reduce the total energy loss for a whole day. We can get the goal through controlling the var/voltages of generators, reactive power generation of shunted capacitors and the tap ratios of on-load tap changer (OLTC) of transformer under the conditions that system's equipments and operation's constraints are satisfied. In the existing research of dynamic reactive power optimization, maximum allowable daily operating times for discrete variables is considered in most cases, while the constraints of maximum allowable switching operations for OLTC between two adjacent time intervals is often ignored. Besides, there are also some problems to process the operating times for capacitors, such as the increment of control variables'scale, and unreasonable of throwing on and off. Aim to those problems, a new model of dynamic reactive power optimization is established in this paper, and the heuristics based hybrid intelligent algorithm is also proposed associated with the hybrid algorithm based on interior point method and immune genetic algorithm (IGA). The concrete contents are as follows:â‘ Based on the existing model of dynamic reactive power optimization, a new model is established, whose objective function is to minimize daily energy loss. The constraint conditions not only contain power flow equations and voltage safety constraints, the maximum allowable daily operating times for capacitor and OLTC, but also contain the constraints of maximum allowable switching operations for OLTC between two adjacent time intervals. Meanwhile, according to the principle of"switching on first then switching off first", all capacitors connected to one bus are made to be an equivalent capacitor variable, and its operating times is determined by the number of the capacitors.â‘¡Aiming to the established new model, the heuristics based hybrid intelligent algorithm is further proposed in this paper. Considering the characteristic of electrical network's parameter invariability in each time interval, sparse technology is used to ehance the calculation efficiency of hybrid algorithm. When processing the dynamic constraints, heuristics based adjustment strategy of"local correction"and"cutting peak and filling valley"is designed in this paper. The adjustment strategy can not only effectively process the constraints of maximum allowable switching operations for tap between two adjacent time intervals and the maximum allowable daily operating times for discrete control variables, but also has more advantageous than the conventional penalty strategy in obtaining the feasible solution.â‘¢At last, IEEE standard systems and a real power system are used to simulate and analysis the model and algorithm proposed in this paper. The results of the simulation indicate that the new model in this paper has more practical significance, and the heuristics based hybrid intelligent algorithm proposed is also more effective to solve the established new model.