A Study Of Optimal Location And Parameters Of TCSC Devices

As a consequence of the deregulation of electricity supply industry and interconnection of power network, Flexible AC Transmission System (FACTS) has been paid more and more attentions by researchers. It is characterized with fast respondence, effective control on system parameters and power flow. The wide application of FACTS devices can bring many benefits for the whole system. It has the advantages of effectively increasing the transfer capability, reducing the network loss and improving the system stability without changing the generation mode and network structure. So it has been a noticeable problem for researchers to take good use of FACTS devices. The improvement of transfer capability can be a great increase of economical profit under the power market environment. At the same time, it is helpful to improve the reliability of power supply and decrease the reserve capability for power supply areas. However, due to the expensive cost, it is very important to attain the optimal allocation of FACTS devices. TCSC is one of the most widely used devices. On the base of analyzing the characteristics of TCSC, a new methodology to attain the optimal location and parameters of TCSC is developed in this thesis and the following work is completed:1. For the calculation of TCSC locations, A sensitivity index is derived to evaluate the influences on total transfer capability caused by different locations of TCSC. The total transfer capability is calculated with the consideration of the static voltage stability constraints.2. A probality index is proposed with the consideration of load and generator output uncertainties by Monte Carlo simulation. Combined with the sensitivity index, the optimal location of TCSC is attained. The effects of load uncertainties, power increasing modes on the results are also discussed.3. For the calculation of optimal capability of TCSC, an economical model is estabilished, in which the total income of TCSC investment is maximized to find the optimal parameters and non-sequential Monte Carlo algorithm is also used to consider the uncertain factors.4. The IEEE14 and IEEE118 system is illustrated as an example to validate the advantage of the proposed methods.