Parallel Self-Adaptive Differential Evolution Algorithm for Solving Short-Term Hydro Scheduling Problem

被引：43

作者：

Glotic, Arnel ^{[1
]}

Glotic, Adnan ^{[2
]}

Kitak, Peter ^{[1
]}

Pihler, Joze ^{[1
]}

Ticar, Igor ^{[1
]}

机构：

[1] Univ Maribor, Fac Elect Engn & Comp Sci, Inst Power Engn, SLO-2000 Maribor, Slovenia

[2] HSE Grp Holding Slovenske Elektrarne Doo, Ljubljana 1000, Slovenia

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2014年 / 29卷 / 05期

关键词：

Algorithms; dispatching; hydroelectric power generation; optimization methods; parallel algorithms; UNIT COMMITMENT; POWER-SYSTEM; PLANTS;

D O I：

10.1109/TPWRS.2014.2302033

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In order to optimize hydro power plants generator scheduling according to 24-h system demand, a parallel self-adaptive differential evolution algorithm has been applied. The proposed algorithm presents a novel approach to considering the multi-population and utilization of the preselection step for the improvements of the algorithm's global search capabilities. A preselection step with the best, middle, and worst populations' individuals establishes the new trial vectors. This algorithm has been verified on two different models. The first one consists of eight power plants with real parameters, and the second one consists of four power plants, mostly used as a test model in scientific papers. The main goal of the optimization process is to satisfy system demand for 24 h with a decreased usage of water quantity per electrical energy unit. The initial and final states of the reservoirs must also be satisfied.

引用

页码：2347 / 2358

页数：12

共 35 条

[1] Augmented Lagrangian approach to hydro-thermal scheduling [J].

Al-Agtash, S ;

Su, RJ .

IEEE TRANSACTIONS ON POWER SYSTEMS, 1998, 13 (04) :1392-1400

[2] Parallelism and evolutionary algorithms [J].

Alba, E ;

Tomassini, M .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (05) :443-462

[3]

[Anonymous], 2002, ADV INTELL SYST FUZZ

[4]

[Anonymous], P NATO ADV RES WORKS

[5] Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems [J].

Brest, Janez ;

Greiner, Saso ;

Boskovic, Borko ;

Mernik, Marjan ;

Zumer, Vijern .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2006, 10 (06) :646-657

[6]

Bruce A. G., 2007, IEEE T POWER SYST, V22, P249

[7] Chaotic sequences to improve the performance of evolutionary algorithms [J].

Caponetto, R ;

Fortuna, L ;

Fazzino, S ;

Xibilia, MG .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2003, 7 (03) :289-304

[8] HYDROELECTRIC GENERATION SCHEDULING WITH AN EFFECTIVE DIFFERENTIAL DYNAMIC-PROGRAMMING ALGORITHM [J].

CHANG, SC ;

CHEN, CH ;

FONG, IK ;

LUH, PB .

IEEE TRANSACTIONS ON POWER SYSTEMS, 1990, 5 (03) :737-743

[9] Genetic aided scheduling of hydraulically coupled plants in hydro-thermal coordination [J].

Chen, PH ;

Hang, HG .

IEEE TRANSACTIONS ON POWER SYSTEMS, 1996, 11 (02) :975-981

[10] Application of Particle Swarm Optimization to Hydro Generation Scheduling [J].

Chen, Po-Hung ;

Chen, Li-Ming ;

Liu, An ;

Chen, Hung-Cheng .

ICEET: 2009 INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENT TECHNOLOGY, VOL 1, PROCEEDINGS, 2009, :541-+

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