Optimal power system operation and control incorporating FACTS devices

Flexible AC Transmission Systems (FACTS) technology provides huge potential opportunities for improved transmission productivity. However, FACTS technology also produces technical problems which need to be addressed before the benefits of FACTS devices may be fully exploited in operation. The steady-state optimization related operation and control functions of FACTS devices in energy management systems (EMS) are the main thrust of research work to be studied and analyzed in this project. The static representations of the four main typical FACTS devices are first developed. An extended Newton-Raphson (N-R) power flow method is proposed to include the four typical FACTS devices as a basic tool in power system operation and control. An extended DC power flow method is developed as the basic tool for the analysis. A two-stage linear programming based contingency-constrained optimal active power flow algorithm is developed to incorporate the effects of three typical FACTS devices and the specified needs for power flow controls using the extended DC power flow method. This algorithm decomposes the problem into two subproblems' iteration to achieve convergency with efficiency. The first subproblem is solved by a sensitivity matrix based method, while the second subproblem is solved as optimal power flow (OPF) problem using LP based OPF method. This method has the advantage that it can be easily incorporated into present OPF function in EMS and would reduce software development and maintenance costs. A new, innovative decoupled OPF method is also developed to include the effects of four typical FACTS devices and the specified needs for power flow controls using the extended N-R power flow equation. In this method, the FACTS related control variables are classified into three types. They are active power related variables, reactive power related variables and active and reactive power related variables. The first and second types are implemented in active power and reactive power OPF respectively. The third type of variables would be optimized in both APOPF and RPOPF subproblems. A special technique is developed to improve the overall convergency and reliability of this OPF approach. Linear programming based OPF method is extended to solve APOPF while successive quadratic programming based method is developed to solve RPOPF. Research results and analysis are presented to show the applicability and efficiency of the method in large scale power systems operation.*; *Originally published in DAI  Vol. 59, No. 10. Reprinted here with corrected author name.