A mixed-integer linear programming approach for robust state estimation
Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
CHEN, Yanbo [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2014 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of modern power systems and clean energy - Nanjing : NARI, 2013, 2(2014), 4 vom: Dez., Seite 366-373 |
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| Übergeordnetes Werk: |
volume:2 ; year:2014 ; number:4 ; month:12 ; pages:366-373 |
| Links: |
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| DOI / URN: |
10.1007/s40565-014-0078-7 |
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SPR036669083 |
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10.1007/s40565-014-0078-7 doi (DE-627)SPR036669083 (SPR)s40565-014-0078-7-e DE-627 ger DE-627 rakwb eng CHEN, Yanbo verfasserin aut A mixed-integer linear programming approach for robust state estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2014 Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. State estimation (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Leverage point (dpeaa)DE-He213 Mathematical programming (dpeaa)DE-He213 Mixed integer linear programming (MILP) (dpeaa)DE-He213 MA, Jin aut Enthalten in Journal of modern power systems and clean energy Nanjing : NARI, 2013 2(2014), 4 vom: Dez., Seite 366-373 (DE-627)75682821X (DE-600)2727912-1 2196-5420 nnns volume:2 year:2014 number:4 month:12 pages:366-373 https://dx.doi.org/10.1007/s40565-014-0078-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2014 4 12 366-373 |
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10.1007/s40565-014-0078-7 doi (DE-627)SPR036669083 (SPR)s40565-014-0078-7-e DE-627 ger DE-627 rakwb eng CHEN, Yanbo verfasserin aut A mixed-integer linear programming approach for robust state estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2014 Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. State estimation (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Leverage point (dpeaa)DE-He213 Mathematical programming (dpeaa)DE-He213 Mixed integer linear programming (MILP) (dpeaa)DE-He213 MA, Jin aut Enthalten in Journal of modern power systems and clean energy Nanjing : NARI, 2013 2(2014), 4 vom: Dez., Seite 366-373 (DE-627)75682821X (DE-600)2727912-1 2196-5420 nnns volume:2 year:2014 number:4 month:12 pages:366-373 https://dx.doi.org/10.1007/s40565-014-0078-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2014 4 12 366-373 |
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10.1007/s40565-014-0078-7 doi (DE-627)SPR036669083 (SPR)s40565-014-0078-7-e DE-627 ger DE-627 rakwb eng CHEN, Yanbo verfasserin aut A mixed-integer linear programming approach for robust state estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2014 Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. State estimation (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Leverage point (dpeaa)DE-He213 Mathematical programming (dpeaa)DE-He213 Mixed integer linear programming (MILP) (dpeaa)DE-He213 MA, Jin aut Enthalten in Journal of modern power systems and clean energy Nanjing : NARI, 2013 2(2014), 4 vom: Dez., Seite 366-373 (DE-627)75682821X (DE-600)2727912-1 2196-5420 nnns volume:2 year:2014 number:4 month:12 pages:366-373 https://dx.doi.org/10.1007/s40565-014-0078-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2014 4 12 366-373 |
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10.1007/s40565-014-0078-7 doi (DE-627)SPR036669083 (SPR)s40565-014-0078-7-e DE-627 ger DE-627 rakwb eng CHEN, Yanbo verfasserin aut A mixed-integer linear programming approach for robust state estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2014 Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. State estimation (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Leverage point (dpeaa)DE-He213 Mathematical programming (dpeaa)DE-He213 Mixed integer linear programming (MILP) (dpeaa)DE-He213 MA, Jin aut Enthalten in Journal of modern power systems and clean energy Nanjing : NARI, 2013 2(2014), 4 vom: Dez., Seite 366-373 (DE-627)75682821X (DE-600)2727912-1 2196-5420 nnns volume:2 year:2014 number:4 month:12 pages:366-373 https://dx.doi.org/10.1007/s40565-014-0078-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2014 4 12 366-373 |
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10.1007/s40565-014-0078-7 doi (DE-627)SPR036669083 (SPR)s40565-014-0078-7-e DE-627 ger DE-627 rakwb eng CHEN, Yanbo verfasserin aut A mixed-integer linear programming approach for robust state estimation 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2014 Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. State estimation (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Leverage point (dpeaa)DE-He213 Mathematical programming (dpeaa)DE-He213 Mixed integer linear programming (MILP) (dpeaa)DE-He213 MA, Jin aut Enthalten in Journal of modern power systems and clean energy Nanjing : NARI, 2013 2(2014), 4 vom: Dez., Seite 366-373 (DE-627)75682821X (DE-600)2727912-1 2196-5420 nnns volume:2 year:2014 number:4 month:12 pages:366-373 https://dx.doi.org/10.1007/s40565-014-0078-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2014 4 12 366-373 |
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A mixed-integer linear programming approach for robust state estimation State estimation (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Leverage point (dpeaa)DE-He213 Mathematical programming (dpeaa)DE-He213 Mixed integer linear programming (MILP) (dpeaa)DE-He213 |
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mixed-integer linear programming approach for robust state estimation |
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A mixed-integer linear programming approach for robust state estimation |
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Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. © The Author(s) 2014 |
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Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. © The Author(s) 2014 |
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Abstract In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear programming formulation for RSE is converted to a MILP problem. The proposed approach not only guarantees to find the global optimum, but also does not have convergence problems. Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency. © The Author(s) 2014 |
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