“…1 is the simulation level of our approach. In lower level, the methods we employed for solving (2) in Level-I, solving (3) in Level-II, solving (6) and (7) in Level-IV are the DPPQN-based algorithm [21]. Remark 1.…”
Section: Flow Chart Of the Four Levels Oo-based Methodsmentioning
confidence: 99%
“…; x c N Þ; the to-be-placed capacitors and the switchable capacitors used in all load cases in (1) (7) is a Quadratic Programming Problem of large network systems. The simulation method for solving (7) is of the DPPQN-based algorithm [21]. We let Dx ⁄ (l r ) denote the optimal solution of (7), thenxðl r Þ ¼ x c þ Dx à ðl r Þ is an approximate solution of (1) for the given …”
Section: Level-iimentioning
confidence: 99%
“…The OPF problem of multiple load cases (2) will be solved in the lower phase as indicated in Fig. 1 and this can be achieved by DPPQN-based algorithm [21]. Let k i denote the optimal Lagrange multiplier vector associated with the flow balance equations of load case i.…”
Section: Level-imentioning
confidence: 99%
“…Solving (3) is the simulation part of this level, we employ the DPPQN-based algorithm [21] to solve it. Once (3) have been solved, the resulting optimal continuous values of C b J will be used in the upper phase to update b J and M r in the following manner.…”
“…1 is the simulation level of our approach. In lower level, the methods we employed for solving (2) in Level-I, solving (3) in Level-II, solving (6) and (7) in Level-IV are the DPPQN-based algorithm [21]. Remark 1.…”
Section: Flow Chart Of the Four Levels Oo-based Methodsmentioning
confidence: 99%
“…; x c N Þ; the to-be-placed capacitors and the switchable capacitors used in all load cases in (1) (7) is a Quadratic Programming Problem of large network systems. The simulation method for solving (7) is of the DPPQN-based algorithm [21]. We let Dx ⁄ (l r ) denote the optimal solution of (7), thenxðl r Þ ¼ x c þ Dx à ðl r Þ is an approximate solution of (1) for the given …”
Section: Level-iimentioning
confidence: 99%
“…The OPF problem of multiple load cases (2) will be solved in the lower phase as indicated in Fig. 1 and this can be achieved by DPPQN-based algorithm [21]. Let k i denote the optimal Lagrange multiplier vector associated with the flow balance equations of load case i.…”
Section: Level-imentioning
confidence: 99%
“…Solving (3) is the simulation part of this level, we employ the DPPQN-based algorithm [21] to solve it. Once (3) have been solved, the resulting optimal continuous values of C b J will be used in the upper phase to update b J and M r in the following manner.…”
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