Research On Aid Decision-making On Running Mode Of Electric Grid

With the developing of computer and network technology, the power dispatching automation system has evolved from the initial generation that is simple SCADA to the present fourth, the new system is the advanced system that the opening and distributing network environments are used, not only the newest software and hardware technology are applied, but the international criterions are adopted. Compared with the foregoing generations, its integrated capability and functions become flying in essence, the system has been providing the strong assistances.The network analysis system is an important part of power dispatching automation system. Overseas part or all of EMS functions have realized in many electric systems. Most interior systems are in stage of SCADA, only several large power networks and provincial networks have been in SCADA and AGC applications. The electric grid running modes are changed through linking lines and transformer launching or dropping out, adjusting the taps of the transformer, the capacitor groups launching or dropping out. It is the problem that many objects and operating parameters are regulated and harmonized.Lots of specialists have studied deeply on the optimization of the area electric network, and gained many applied fruits, especially on optimization of the inactive power. But most means are that the operating methods are adjusted in real time according to the loads change, thus it causes the electric equipments launching and dropping out continually, this will affect the operating life-span and bring the unsafe factors to power network. On the other hand, only the modernization high-tech means must be applied and expanded the EMS advanced functions of applying software, the increasing complex network structure is dispatched. In the dispatching automation of the area electric network, the present mean method is, according to a certain stage, that vary optimization arithmetic is used to adjust every control variable in order to realize the object that the loss of grid is least. No doubt the optimization economical running can be realized, but in practice it is not feasible because of the limits of equipment operating life and adjusting times.In this paper it is studied that the loads curve is divided into several parts according to the time, the control variables keep invariable, and then the optimization adjustmentis done in the period so that the most economical running scheme is gained.In first, the loads forecasting is done and there are many method such as the many factors linear regression method, the index flatness method and so on. In these methods the analytic expressions are required to be created among the loads and the influencing factors, it is very difficult in general and is one of the reasons for affecting forecasting precision. The analytic expressions needn't be created in ANN(artificial neural network ) method, and the network parameters will come out through the samples training on it. The loads for future may be forecasted by the trained network. In this paper the BP ANN is applied, with the transacted loads and influencing factors data the network is trained, the loads are forecasted with the trained network, the gross error of forecasted data reaches to 4.63 percent, and the results can meet the demands of the project.The forecasted loads curves are divided into several parts by the time. The principle that the total deviations are least is applied, and the results calculated by the step accelerating method, thus assures that the loads are relatively stable in some a period so that the electric grid economical running is guaranteed.The running mode of grid is commonly open, so the topology theory is used to compute all the running modes set, namely all the trees come out. According to the actual things the trees may be filtered and the practical subset of running mode is made certain.With regard to the practical subset, the optimizing arithmetic such as the network maximum flow method is used, and through the flows computing the gross loss of the...