Browse > Article
http://dx.doi.org/10.5391/JKIIS.2014.24.2.141

Generation of Daily Load Curves for Performance Improvement of Power System Peak-Shaving  

Son, Subin (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Song, Hwachang (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.24, no.2, 2014 , pp. 141-146 More about this Journal
Abstract
This paper suggests a way of generating one-day load curves for performance improvement of peak shaving in a power system. This Peak Shaving algorithm is a long-term scheduling algorithm of PMS (Power Management System) for BESS (Battery Energy Storage System). The main purpose of a PMS is to manage the input and output power from battery modules placed in a power system. Generally, when a Peak Shaving algorithm is used, a difference occurs between predict load curves and real load curves. This paper suggests a way of minimizing the difference by making predict load curves that consider weekly normalization and seasonal load characteristics for smooth energy charging and discharging.
Keywords
BESS; Daily Load Curve; Load Curve Generation; Peak Shaving; Weekly Normalization;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 P. Mercier, R. Cherkaouri, and A. Oudalov, "Optimizing a battery energy storage system for frequency control application in an isolated power system," IEEE Trans. Power Systems, Vol. 24, No. 3, pp. 1469-1477, 2009.   DOI   ScienceOn
2 U.S. DOE, Basic Research Needs for Electrical Energy Storage, DOE Report, 2007.
3 Sung-Wook Park, Jin Soo Seo and Bo-Hyeun Wang, "Development of Home Electrical Power Monitoring System and Device Identification Algorithm" Journal of Korean Institute of Intelligent Systems, Vol. 21, No. 4, pp. 407-413, 2011.   과학기술학회마을   DOI   ScienceOn
4 P. Denholm, E. Ela, B. Kirby, and M. Milligan, The Role of Energy Storage with Renewable Electricity Generation, NREL Report: TP-6A2-47187, 2010.
5 X. Li, L. Liao,, B. Li, and Z. Wang, "Improvement of power quality and voltage stability of load by battery energy storage system," Proc. of Conferecne of Power Engineering, Energy and Electrical Drives, Lisbon, Portugal, 18-20 March 2009.
6 Y. H. Joo, K. H. Jung, D. W. Kim, and J. B. Park, "A Study of Short-Term Load Forecasting System Using Data Mining" Journal of Korean Institute of Fuzzy and Intelligent System, vol. 14, No. 2, pp. 130-135, 2004.   과학기술학회마을   DOI
7 J.-Y. Lee, W. Kim, and C.-H. Hyun, "Robust High-Gain Observer Based SOC Estimator for Uncertain RC Model of Li-Ion Batteries" Journal of Korean Institute of Intelligent Systems, Vol. 23, No.3, pp. 214-219, 2013.   과학기술학회마을   DOI
8 S. Ohn, J.-S. Kim, H. Song and B. Chang, "Fuzzy LP Based Power Network Peak Shaving Algorithm" Journal of Korean Institute of Intelligent Systems, Vol. 22, No. 6, pp. 754-760, 2012.   과학기술학회마을   DOI   ScienceOn
9 P. R. J. Campbell and K. Adamson, "Methodologies for Load Forecasting," Proc. of 3rd International Conference Intelligent Systems, London, UK, 2-6 September 2006.
10 S.-H. Yoo, "A Nonlinear Observer Design for Estimating State-of-Charge of Lithium Polymer Battery" Journal of Korean Institute of Intelligent Systems, Vol. 22, No. 3, pp. 300-304, 2012.   과학기술학회마을   DOI   ScienceOn
11 EPRI, Electricity Energy Storage Technology Options, EPRI Report, 2010.