single-jc.php

JACIII Vol.20 No.6 pp. 1004-1012
doi: 10.20965/jaciii.2016.p1004
(2016)

Paper:

A Novel Approach for Determining Distributed Generations Penetration Level Using Least Square Minimization (LSM) Curve Fitting

Rodel D. Dosano*, Nemia H. Mabaquiao**, Godelyn Gallega-Hisole**, Regin A. Cabacas*, and In-Ho Ra***,†

*College of Information and Communications Technology, West Visayas State University
Luna Street, La Paz, Iloilo City, Philippines

**Department of Electrical Engineering, Iloilo Science and Technology University
Burgos Street, La Paz, Iloilo City, Philippines

***School of Computer, Information and Communication Engineering, Kunsan National University
558 Daehak-ro, Miryong-dong, Kunsan, South Korea

Corresponding author

Received:
April 29, 2016
Accepted:
September 1, 2016
Published:
November 20, 2016
Keywords:
RE resources integration, distributed generation (DG), DG penetration levels, penetration level margin
Abstract
With the publicized benefits offered by renewable energy resources, more and more households embrace the utilization of stand-alone installations ranging from small to medium scale systems. In literature, several studies provide insights on the effects of integration of renewable energy (RE) resources to the distribution systems but have inadequacy of considering the penetration levels. Moreover, RE cost reductions, increasing costs of traditional energy sources, and Renewable Portfolio Standards have created the possibility of significant increase of penetration levels of distributed RE generation being installed on distribution systems. To aid in the evaluation and assist with these expansions, new analysis tools are needed. In particular, new RE high-penetration analysis tools and procedures need to be developed and integrated with existing conventional methods. This paper presents a simulation based study on distribution system with and without integration of RE sources. It takes into account of the impending effects of these RE integrations in the distribution system. This paper emphasizes a novel method of determining the penetration level of Distributed Generation using least square minimization (LSM) method. The studies were tested using IEEE 123 bus distribution test feeder and actual data from an existing distribution system to verify the effectiveness and robustness of the proposed approach.
Cite this article as:
R. Dosano, N. Mabaquiao, G. Gallega-Hisole, R. Cabacas, and I. Ra, “A Novel Approach for Determining Distributed Generations Penetration Level Using Least Square Minimization (LSM) Curve Fitting,” J. Adv. Comput. Intell. Intell. Inform., Vol.20 No.6, pp. 1004-1012, 2016.
Data files:
References
  1. [1] F. Shahnia and A. Ghosh, “High Penetration of Rooftop Photovoltaic Cells in Low Voltage Distribution Networks,” Voltage Imbalance and Improvement, Renewable Energy Integration: Challenges and Solutions, Springer-Verlag Singapur, pp. 69-65, 2014.
  2. [2] S. Wanxing, Z. Shanshan, S. Xiaohu, and M. Xiaoli, “Maximum penetration level of distributed generation in consideration of voltage fluctuations based on multi-resolution model” IET Generation, Transmission & Distribution, Vol.9, Issue 3, pp. 241-248, 2015.
  3. [3] V. V. Thong, J. Driesen, and R. Belmans, “Transmission system operation concerns with high penetration level of distributed generation,” 42nd Int. Universities Power Engineering Conf., pp. 867-871, 2007.
  4. [4] C. H. Nguyen, N. Mithulananthan, and R. C. Bansal, “Location and Sizing of Distributed Generation Units for Loadabilty Enhancement in Primary Feeder,” IEEE Systems J., Vol.7, Issue 4, pp. 797-806, 2013.
  5. [5] H. A. Abdelsalam, A. Y. Abdelaziz, R. A. Osama, and B. K. Panigrahi, “Effect of Photovoltaic and Wind Power Variations in Distribution System Reconfiguration for Loss Reduction Using Ant Colony Algorithm,” Swarm, Evolutionary and Memetic Computing, Springer-Int. Publishing, pp. 504-514, 2013.
  6. [6] T. Senjyu, Y. Miyazato, A. Yona, and N. Urasaki, “Optimal Distribution Voltage Control and Coordination With Distributed Generation,” IEEE Trans. on Power Delivery, Vol.23, Issue 2, pp. 1236-1242, 2008.
  7. [7] IEEE Test Feeders, http://ewh.ieee.org/soc/pes/dsacom/testfeeders/ [Accessed March 26, 2016]
  8. [8] Panay Electric Company Website, http://www.panayelectric.com/ [Accessed March 26, 2016]
  9. [9] PECO Feeder Information, http://www.panayelectric.Com /pageid =557 [Accessed March 26, 2016]
  10. [10] N. H. Mabaquiao, G. G. Hisole, R. D. Dosano, R. A. Cabacas and I. H. Ra, “Distributed Generations Penetration Levels and its Effects on a Distribution System: A Simulation-based Study,” Joint SCIS and ISIS Conf., Mokpo, South Korea, 2015.
  11. [11] G. G. Hisole, R. D. Dosano, R. A. Cabacas, and I. H. Ra, “Determining the Optimal Reactive Power Dispatch of a Distribution System with Renewable Energy Sources using Differential Evolution Algorithm,” Joint SCIS and ISIS Conf., Mokpo, South Korea, 2015.
  12. [12] J. Bank, B. Mather, J. Keller, and M. Coddington, “High Penetration Photovoltaic Case Study Report,” National Renewable Energy Laboratory, Technical Report NREL/TP-5500-54742, January 2013.
  13. [13] S. A. Soliman and A. M. Alkandari, “Electrical Load Forecasting,” Elsevier Publishing, 2010.
  14. [14] A. EL-Dib, H. Youssef, H. EL-Metwally, and Z. Ozman, “Maximum loadability of power systems using hybrid particle swarm optimization,” Electric Power Systems Research, Vol.76, Issue 6, pp. 485-492, 2006.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Dec. 02, 2024