1998
DOI: 10.1109/59.736231
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An interior-point method for nonlinear optimal power flow using voltage rectangular coordinates

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Cited by 323 publications
(162 citation statements)
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“…Furthermore, PDIPM implements only MVA flow constraints. However, as the main computational burden in IPM is the factorization of a linear system of equations [12], we notice that as Matpower solvers rely on the "reduced KKT system" [10,21], the number of inequality constraints does not affect the size of this system, contrary to our implementation which uses the full KKT system (17). Table 8 presents the results of our experiments for four feasible OPF problems, where "L" denotes the linear objective 6 function (24), "Q" denotes the quadratic objective function MD (1), and the base case A-PST has been obtained from the base case A by setting to zero the angle of all 84 phase shifters and using as starting point the load flow solution of case A.…”
Section: Comparison With Available Solversmentioning
confidence: 99%
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“…Furthermore, PDIPM implements only MVA flow constraints. However, as the main computational burden in IPM is the factorization of a linear system of equations [12], we notice that as Matpower solvers rely on the "reduced KKT system" [10,21], the number of inequality constraints does not affect the size of this system, contrary to our implementation which uses the full KKT system (17). Table 8 presents the results of our experiments for four feasible OPF problems, where "L" denotes the linear objective 6 function (24), "Q" denotes the quadratic objective function MD (1), and the base case A-PST has been obtained from the base case A by setting to zero the angle of all 84 phase shifters and using as starting point the load flow solution of case A.…”
Section: Comparison With Available Solversmentioning
confidence: 99%
“…A (locally) optimal solution is found and the optimization process terminates when: primal feasibility, scaled dual feasibility, scaled complementarity gap and objective function variation from an iteration to the next fall below some tolerances [9,10,12]:…”
Section: The MCC Algorithmmentioning
confidence: 99%
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“…Because the corrected voltage should be equal to the lower bound ( V corr i = V lb i ) to maximize the CVR effect, α is given by: (27) Finally, the droop constants are corrected by using Equations (23) and (24). Even though the corrected droop constants are used, the voltage magnitude of node i can be smaller than its lower bound for another combination of the active power outputs.…”
Section: Final Correctionmentioning
confidence: 99%
“…An interior point method (IPM) has been reformulated and adapted to solve such a nonlinear problem. In fact, the IPM has been widely used to solve problems like the optimal power flow for large-scale systems [14], load ability maximization [15], voltage stability analysis [16], and security-constrained economic dispatch [17]. The IPM can be employed to solve TEP as a NLP problem that should be solved in each step of the ECHA.…”
Section: Introductionmentioning
confidence: 99%