Multi-objective Allocation of Multi-type Distributed Generators along Distribution Networks Using Backtracking Search Algorithm and Fuzzy Expert Rules

被引:52
作者
El-Fergany, Attia [1 ]
机构
[1] Zagazig Univ, Fac Engn, Dept Elect Power & Machines, POB 44519, Zagazig, Egypt
关键词
multi-distributed generators; backtracking search algorithm; multi-objective optimization; fuzzy expert rules; loss minimization; static voltage stability indices; CAPACITOR ALLOCATION; DISTRIBUTION-SYSTEMS; GENETIC ALGORITHM; OPTIMAL PLACEMENT; OPTIMIZATION; LOCATION; DEFINITION; UNITS;
D O I
10.1080/15325008.2015.1102989
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
This article presents a methodology for a multi-objective optimal allocation of multi-type distributed generators in radial distribution networks based on a backtracking search algorithm. The study aims to prove the validity and the strength of the backtracking search algorithm multi-objective method on distributed generator allocation. The multi-objective function is expressed to minimize the network power losses, to consolidate the static voltage stability indices, and to ameliorate the bus's voltage profile. The indicators of loss sensitivity factors and bus voltage magnitudes are incorporated to establish set of fuzzy expert rules to assort the preliminary buses for distributed generator placement. The proposed methodology allows the fuzzy decision maker to decide the best compromise solution among the offered Pareto-optimal solutions. The salient features of the backtracking search algorithm are demonstrated and marked on 33- and 94-node radial distribution networks with various scenarios. The cropped results are compared with those reported by others in the literature, validating and signifying the proposed approach. The study finds that the type-3 distributed generator unit (delivers P and injects Q) is most preferred to reduce power losses along network lines and to boost both the bus voltage profile and voltage stability indices.
引用
收藏
页码:252 / 267
页数:16
相关论文
共 49 条
[31]   A hybrid islanding detection technique using voltage unbalance and frequency set point [J].
Menon, Vivek ;
Nehrir, M. Hashem .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (01) :442-448
[32]   A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems [J].
Moradi, M. H. ;
Abedini, M. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2012, 34 (01) :66-74
[33]   Capacitor allocation by approximate reasoning: Fuzzy capacitor placement [J].
Ng, HN ;
Salama, MMA ;
Chikhani, AY .
IEEE TRANSACTIONS ON POWER DELIVERY, 2000, 15 (01) :393-398
[34]   Location and Sizing of Distributed Generation Units for Loadabilty Enhancement in Primary Feeder [J].
Nguyen Cong Hien ;
Mithulananthan, Nadarajah ;
Bansal, R. C. .
IEEE SYSTEMS JOURNAL, 2013, 7 (04) :797-806
[35]   Reliability centered planning for distributed generation considering wind power volatility [J].
Novoa, Clara ;
Jin, Tongdan .
ELECTRIC POWER SYSTEMS RESEARCH, 2011, 81 (08) :1654-1661
[36]  
Parizad A., 2010, 23 CAN C EL COMP ENG, V1, P1, DOI DOI 10.1109/CCECE.2010.5575177
[37]   Distributed generation: definition, benefits and issues [J].
Pepermans, G ;
Driesen, J ;
Haeseldonckx, D ;
Belmans, R ;
D'haeseleer, W .
ENERGY POLICY, 2005, 33 (06) :787-798
[38]  
Pires D. F., 2009, 8 INESC, P1
[39]   GSA: A Gravitational Search Algorithm [J].
Rashedi, Esmat ;
Nezamabadi-Pour, Hossein ;
Saryazdi, Saeid .
INFORMATION SCIENCES, 2009, 179 (13) :2232-2248
[40]  
Rostamzadeh M., 2012, ART INTELL RES, V1, DOI [10.5430/air.vln2p56, 2012, DOI 10.5430/AIR.VLN2P56]