DOI QR코드

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Two Stage Hybrid Optimization을 사용한 ESS 최적 운전 전략에 대한 연구

A Study on ESS Optimal Operation Strategy Using Two Stage Hybrid Optimization

  • 투고 : 2018.02.20
  • 심사 : 2018.06.25
  • 발행 : 2018.07.01

초록

This paper presents an analysis and the methodology of optimal operation strategy of the ESS(Energy Storage System) for reduce electricity charges. Electricity charges consist of a basic charge based on the contract capacity and energy charge according to the power usage. In order to use electrical energy at minimal charge, these two factors are required to be reduced at the same time. QP(Quadratic Programming) is appropriate for minimization of the basic charge and LP(Linear Programmin) is adequate to minimize the energy charge. However, the integer variable have to be introduced for modelling of different charge and discharge efficiency of ESS PCS(Power Conversion System), where MILP(Mixed Integer Linear Programming) can be used. In this case, the extent to which the peak load savings is accomplished should be assumed before the energy charge is minimized. So, to minimize the electricity charge exactly, optimization is sequentially performed in this paper, so-called the Two Stage Hybird optimization, where the extent to which the peak load savings is firstly accomplished through optimization of basic charge and then the optimization of energy charge is performed with different charge and discharge efficiency of ESS PCS. Finally, the proposed method is analyzed quantitatively with other optimization methods.

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참고문헌

  1. G. Venkataramanan and C. Marnay, "A larger role for microgrids", IEEE Power Energy Mag., vol. 6, no. 3, pp. 78-82, 2008. https://doi.org/10.1109/MPE.2008.918720
  2. D.K. Maly and K.S. Kwan, "Optimal battery energy storage system(BESS) charge scheduling with dynamic programming", IEE Proc-Sci, Meas. Technol., vol. 142, no. 6, Nov. 1995.
  3. A. Purvins, T. I. Papaioannou and L. Debarberis, "Application of battery-based storage systems in household-demand smoothening in electricity-distribution grids", Energy Conversion and Management, vol. 65, pp. 272-284, Jan. 2013. https://doi.org/10.1016/j.enconman.2012.07.018
  4. J. Giraldez, R. Roche, S. Suryanarayanan and D. Zimmerle, "A Linear Programming Methodology to Quantify the Impact of PHEVs with V2G Capabilities on Distribution Systems", 2013 IEEE Green Technologies Conference (GreenTech), pp. 8-15, 2013.
  5. Rakkyung Ko, Seongbae Kong and Sung-Kwan Joo, "Mixed Integer Programming (MIP)-based Energy Storage System Scheduling Method for Reducing the Electricity Purchasing Cost in an Urban Railroad System", Trans. of KIEE, vol. 64, no. 7, pp. 1125-1129, 2015.
  6. O. Erdinc, N. G. Paterakis, T. D. P. Mendes, A. G. Bakirtzis and J. P. S. Catalao, "Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR", IEEE Trans. on Smart Grid, vol. 6, no. 3, pp. 1281-1291, 2015. https://doi.org/10.1109/TSG.2014.2352650
  7. C. Bustos, E. Sauma, S. Torre, J. A. Aguado, J. Contrreras, and D. Pozo, "Energy storage and transmission expansion planning: substitutes or complements?", IET Gener. Transm. Distrib., vol. 12, no. 8, pp. 1738-1746, 2018. https://doi.org/10.1049/iet-gtd.2017.0997
  8. Jae-Haeng Heo, Seungkwon Shin, Jong-young Park and Hyeongig Kim, "Study on the Optimal Operation of ESS Considering Urban Railway Load Characteristic," Trans. of KIEE, vol. 64, no. 10, pp. 1508-1516, 2015.
  9. C. Chen, S. Duan, T. Cai, B. Liu and G. Hu, "Smart energy management system for optimal microgrid economic operation", IET Renewable Power Generation, vol. 5, no. 3, pp. 258-267, 2011. https://doi.org/10.1049/iet-rpg.2010.0052
  10. Chakraborty S. Senjyu T. Toyama H. Saber A. Y. and Funabashi T., "Determination methodology for optimising the energy storage size for power system", IET Gener. Transm. Distrib., vol. 3, no. 11, pp. 987-999, 2009. https://doi.org/10.1049/iet-gtd.2008.0300
  11. Fangqing Gu, Yiu-Ming Cheung, "Self-Organizing Map- Based Weight Design for Decomposition-Based Many-Objective Evolutionary Algorithm," IEEE Trans. on Evolutionary Computation, vol. 22, no. 2, pp. 211-225, 2018. https://doi.org/10.1109/TEVC.2017.2695579