Thanks Ray, I see so the result.x includes control variables and state variables.
But what exact control variables are for 'runopf'? Thanks Wenlei Bai Electrical Engineering, Department of Electrical & Computer Engineering Baylor University, One Bear Place #97356 Waco, TX 76798-7356 (254)405-3320 [email protected] ________________________________ From: [email protected] <[email protected]> on behalf of Ray Zimmerman <[email protected]> Sent: Thursday, October 6, 2016 7:28:03 AM To: MATPOWER discussion forum Subject: Re: OPF control variables The mathematical formulation of the OPF problem is specified as an optimization problem, with optimization variables that need not be partitioned (for the sake of the optimization) into control and state variables. This variables in results.x include the full set of optimization variables. To be sure, when using an OPF to "control" a system, it will be important to know which of the optimization variables can be controlled directly, and which are state variables whose values are implicitly determined by the control variable settings. But this distinction is not necessary for MATPOWER to specify and solve the OPF problem. Hope this helps, Ray On Oct 5, 2016, at 11:01 PM, Bai, Wenlei <[email protected]<mailto:[email protected]>> wrote: Dear Ray, I noticed that when I 'results = runopf('case')', I am able to find the control variables by 'results.x'; however, the control variables consist of all the bus angles, bus voltages, P output from generator buses(including slack bus), and reactive power Q from generator buses (including slack bus) To my understanding, isn't true that control variables should only include real power P from generator buses except slack bus, voltage of all generator buses and shunt capacitors and transformers if necessary? Blessings, Wenlei Bai Electrical Engineering, Department of Electrical & Computer Engineering Baylor University, One Bear Place #97356 Waco, TX 76798-7356 (254)405-3320 [email protected]<mailto:[email protected]>
