Optimal DG Allocation in Radial Distribution Systems with High Penetration of Non-linear Loads

被引:20
作者
Abdelsalam, Abdelazeem A. [1 ]
Zidan, Aboelsood A. [2 ]
El-Saadany, Ehab F. [3 ]
机构
[1] Suez Canal Univ, Dept Elect Engn, Ismailia 41522, Egypt
[2] Assiut Univ, Elect & Comp Engn, Assiut, Egypt
[3] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
关键词
distributed generation; optimization; voltage profile; power losses; THD; genetic algorithm; ELECTRIC-POWER NETWORKS; GENETIC ALGORITHM; GENERATION; OPTIMIZATION; PROPAGATION; SIMULATION; HARMONICS;
D O I
10.1080/15325008.2015.1043601
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 paper addresses the optimal distributed generation sizing and siting for voltage profile improvement, power losses, and total harmonic distortion (THD) reduction in a distribution network with high penetration of non-linear loads. The proposed planning methodology takes into consideration the load profile, the frequency spectrum of non-linear loads, and the technical constraints such as voltage limits at different buses (slack and load buses) of the system, feeder capacity, THD limits, and maximum penetration limit of DG units. The optimization process is based on the Genetic Algorithm (GA) method with three scenarios of objective function: system power losses, THD, and multi-objective function-based power losses and THD. This method is executed on the IEEE 31-bus system under sinusoidal and non-sinusoidal (harmonics) operating conditions including load variations within the 24-hr period. The simulation results using Matlab environment show the robustness of this method in optimal sizing and siting of DG, efficiency for improvement of voltage profile, reduction of power losses, and THD. A comparison with particle swarm optimization (PSO) method shows that the proposed method is better than PSO in reducing the power losses and THD in all suggested scenarios.
引用
收藏
页码:1487 / 1497
页数:11
相关论文
共 32 条
[11]   A genetic-based tabu search algorithm for optimal DG allocation in distribution networks [J].
Gandomkar, M ;
Vakilian, M ;
Ehsan, M .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2005, 33 (12) :1351-1362
[12]   An analytical method for the sizing and siting of distributed generators in radial systems [J].
Goezel, Tuba ;
Hocaoglu, M. Hakan .
ELECTRIC POWER SYSTEMS RESEARCH, 2009, 79 (06) :912-918
[13]   A method for placement of DG units in distribution networks [J].
Hedayati, Hasan ;
Nabaviniaki, S. A. ;
Akbarimajd, Adel .
IEEE TRANSACTIONS ON POWER DELIVERY, 2008, 23 (03) :1620-1628
[14]   Volt/VAr control in distribution systems using a time-interval based approach [J].
Hu, Z ;
Wang, X ;
Chen, H ;
Taylor, GA .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 2003, 150 (05) :548-554
[15]  
Jenkins N., 2000, EMBEDDED GENERATION
[16]  
Kim KH, 2002, 2002 IEEE POWER ENGINEERING SOCIETY SUMMER MEETING, VOLS 1-3, CONFERENCE PROCEEDINGS, P1148, DOI 10.1109/PESS.2002.1043458
[17]   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
[18]   Integration of Distributed Generation in Power Networks Considering Constraints on Discrete Size of Distributed Generation Units [J].
Musa, Idris ;
Gadoue, Shady ;
Zahawi, Bashar .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2014, 42 (09) :984-994
[19]  
Nara K, 2001, 2001 IEEE POWER ENGINEERING SOCIETY WINTER MEETING, CONFERENCE PROCEEDINGS, VOLS 1-3, P918, DOI 10.1109/PESW.2001.916995
[20]   Evaluating distributed generation impacts with a multiobjective index [J].
Ochoa, Luis F. ;
Padilha-Feltrin, Antonio ;
Harrison, Gareth P. .
IEEE TRANSACTIONS ON POWER DELIVERY, 2006, 21 (03) :1452-1458