JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Study on BESS Charging and Discharging Scheduling Using Particle Swarm Optimization
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Study on BESS Charging and Discharging Scheduling Using Particle Swarm Optimization
Park, Hyang-A; Kim, Seul-Ki; Kim, Eung-Sang; Yu, Jung-Won; Kim, Sung-Shin;
  PDF(new window)
 Abstract
Analyze the customer daily load patterns, be used to determine the optimal charging and discharging schedule which can minimize the electrical charges through the battery energy storage system(BESS) installed in consumers is an object of this paper. BESS, which analyzes the load characteristics of customer and reduce the peak load, is essential for optimal charging and discharging scheduling to save electricity charges. This thesis proposes optimal charging and discharging scheduling method, using particle swarm optimization (PSO) and penalty function method, of BESS for reducing energy charge. Since PSO is a global optimization algorithm, best charging and discharging scheduling can be found effectively. In addition, penalty function method was combined with PSO in order to handle many constraint conditions. After analysing the load patterns of target BESS, PSO based on penalty function method was applied to get optimal charging and discharging schedule.
 Keywords
Battery energy storage system;Particle swarm optimization;Penalty function;Electric cost saving;Optimization of charging and discharging;
 Language
Korean
 Cited by
 References
1.
Soo-Hong Kim, Tae-Hyeong Kim, Yun-Hyun Kim, Dong-Seok In, Byung-Ki Kwon, and Chang-Ho Choi, "A Development of 2MVA Battery Energy Storage System", The Transactions of the Korean Institute of Power Electronics, Vol. 17, No. 2, pp. 174-181, 2012. crossref(new window)

2.
Tae-Ho Lee, "Optimal sizing and economic analysis of battery energy storage system(BESS) for demand side management", Master's Thesis, Inha University, 2014.

3.
A. Oudalov, R. Cherkoui, A. Beguin, "Sizing and optimal operation of battery energy storage system for peak shaving application", Power Tech, 2007 IEEE Lausanne. IEEE, pp. 621-625. 2007

4.
G. Carpinelli, S. Khormali, F. Mottola and D. Proto, "Optimal operation of electrical energy storage systems for industrial applications", Power and Energy Society General Meeting (PES), 2013 IEEE. IEEE, pp. 1-5, 2013.

5.
L. T. Youn and S. Cho, "Optimal operation of energy storage using linear programming technique", Proceedings of the World Congress on Engineering and Computer Science. Vol. 1. pp.480-485, 2009.

6.
Andries P., Engelbrecht, "Computational Intelligence : An Introduction", John Wiley & Sons, 2007.

7.
J. Kennedy and R. C. Eberhart, "Particle swarm optimization", Proceedings of IEEE International Conference on Neural Networks. Vol. 4. 1995.

8.
Sung-Min Cho, "Optimal BESS sizing for customer using new model considering efficiency and life cycle", Doctor's Thesis, Soongsil University, 2012.

9.
Seul-Ki Kim, Kyeong-Hee Cho, Jong-Yul Kim and Eung-Sang Kim, "Estimation of Reasonable Price of Battery Energy Storage System for Electricity Customers Demand Management", the Transactions of KIEE, Vol. 62, No. 10, pp. 1390-1396, October 2013.

10.
Korea Electric Power Corporation, http://cyber.kepco.co.kr