| 000 | 03907nlm1a2200457 4500 | ||
|---|---|---|---|
| 001 | 667686 | ||
| 005 | 20231030042121.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\38897 | ||
| 035 | _aRU\TPU\network\36371 | ||
| 090 | _a667686 | ||
| 100 | _a20220413a2021 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 102 | _aCH | ||
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aEWOA-OPF: Effective Whale Optimization Algorithm to Solve Optimal Power Flow Problem _fM. H. Nadimi-Shahraki, S. Taghian, S. Mirjalili [et al.] |
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| 203 |
_aText _celectronic |
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| 300 | _aTitle screen | ||
| 320 | _a[References: 101 tit.] | ||
| 330 | _aThe optimal power flow (OPF) is a vital tool for optimizing the control parameters of a power system by considering the desired objective functions subject to system constraints. Metaheuristic algorithms have been proven to be well-suited for solving complex optimization problems. The whale optimization algorithm (WOA) is one of the well-regarded metaheuristics that is widely used to solve different optimization problems. Despite the use of WOA in different fields of application as OPF, its effectiveness is decreased as the dimension size of the test system is increased. Therefore, in this paper, an effective whale optimization algorithm for solving optimal power flow problems (EWOA-OPF) is proposed. The main goal of this enhancement is to improve the exploration ability and maintain a proper balance between the exploration and exploitation of the canonical WOA. In the proposed algorithm, the movement strategy of whales is enhanced by introducing two new movement strategies: (1) encircling the prey using Levy motion and (2) searching for prey using Brownian motion that cooperate with canonical bubble-net attacking. To validate the proposed EWOA-OPF algorithm, a comparison among six well-known optimization algorithms is established to solve the OPF problem. All algorithms are used to optimize single- and multi-objective functions of the OPF under the system constraints. Standard IEEE 6-bus, IEEE 14-bus, IEEE 30-bus, and IEEE 118-bus test systems are used to evaluate the proposed EWOA-OPF and comparative algorithms for solving the OPF problem in diverse power system scale sizes. The comparison of results proves that the EWOA-OPF is able to solve single- and multi-objective OPF problems with better solutions than other comparative algorithms. | ||
| 461 | _tElectronics | ||
| 463 |
_tVol. 10, iss. 23 _v[2975, 23 p.] _d2021 |
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| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aoptimization | |
| 610 | 1 | _ametaheuristic algorithms | |
| 610 | 1 | _aoptimal power flow | |
| 610 | 1 | _awhale optimization algorithm | |
| 610 | 1 | _aоптимизация | |
| 610 | 1 | _aметаэвристические алгоритмы | |
| 701 | 1 |
_aNadimi-Shahraki _bM. H. _gMohammad |
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| 701 | 1 |
_aTaghian _bS. _gShokooh |
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| 701 | 1 |
_aMirjalili _bS. _gSeyedali |
|
| 701 | 1 |
_aAbualigah _bL. _gLaith |
|
| 701 | 1 |
_aMokhamed Elsaed (Mohamed Abd Elaziz) _bA. M. _cSpecialist in the field of informatics and computer technology _cProfessor of Tomsk Polytechnic University _f1987- _gAkhmed Mokhamed _2stltpush _3(RuTPU)RU\TPU\pers\46943 |
|
| 701 | 1 |
_aOliva Navarro _bD. A. _cspecialist in the field of informatics and computer technology _cProfessor of Tomsk Polytechnic University _f1983- _gDiego Alberto _2stltpush _3(RuTPU)RU\TPU\pers\37366 |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа информационных технологий и робототехники _bОтделение информационных технологий _h7951 _2stltpush _3(RuTPU)RU\TPU\col\23515 |
| 801 | 2 |
_aRU _b63413507 _c20220413 _gRCR |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.3390/electronics10232975 |
| 942 | _cCF | ||