The Journal of Information Systems (한국정보시스템학회지:정보시스템연구)

Korea Association of Information Systems (한국정보시스템학회)
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A Development of VPP Platform for the Efficient Utilization of Distributed Renewable Energy Resources

분산 재생에너지의 효율적 활용을 위한 가상발전소(VPP) 플랫폼 개발에 관한 연구

  • Received : 2018.05.30
  • Accepted : 2018.06.28
  • Published : 2018.06.30
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Abstract

Purpose The recent concern over environmental problems such as greenhouse gas emission and fine dust contributes increasing interest in renewable energies. However the intrinsic characteristics of renewable energies, intermittent and stochastic generation, might cause serious problems to the stability and controllability of power grid. Therefore countermeasures such as virtual power plant (VPP) must be prepared in advance of the spread of uncontrollable distributed renewable energy resources to be one of major energy sources. Design/methodology/approach This study deals with the design concept of the VPP platform. we proposed as a technology solution for achieving the stability of power grid by guaranteeing a single power profile combining multiple distributed power sources with ICT. The core characteristics of VPP should be able to participate in the grid operation by responding to operation instructions from the system operator, KPX, as well as the wholesale electricity market. Findings Therefore this study includes energy storage device(ESS) as a controllable component as well as renewable energy resources such as photovoltaic and wind power generation. Based on this configuration, we discussed core element technologies of VPP and protype design of VPP solution platform according to system requirements. In the proposed solution platform, UX design for the integrated control center and brokerage system were included as well as ancillary service function to respond to KPX's operation instruction with utilizing the capability of ESS. In addition, a simulator was suggested to verify the VPP operations.

Keywords

References

  1. 김종욱, 김병곤, "Why Systems Analysts Ignore Socio-Organizational Concerns During Systems Analysis?," 정보시스템연구, 제9권, 제1호, 2000, pp. 189-216.
  2. 김태운, 고창성, 김원경, "분산 및 글로벌 구매를 위한 멀티에이전트 설계," 정보시스템연구, 제8권, 제2호, 1999, pp. 111-127.
  3. 김태형, 함경선, "가상발전소 분산전원의 통합관리 및 정보교환을 위한 IEC 61850 적용 연구," 한국통신학회 학술대회논문집, 2017, pp. 1430-1430.
  4. 김형민, "아낀 전기 공급하는 '가상발전소'," 매일경제신문 기사, 2016.08.25.
  5. 박성원, "신재생원 도입 환경에서 배전계통 제약을 고려한 가상발전소 최적 운영 방법," 가천대학교 박사학위논문, 2018.
  6. 박용국, 이민구, 정경권, 이용구, "가변 및 민감성 부하를 고려한 대단위 가상 발전소 운영 방법," 전자공학회논문지, Vol. 52, No. 5, 2015, pp. 225-234. https://doi.org/10.5573/ieie.2015.52.5.225
  7. 박중성, "가상발전 최적운영 기술 개발을 위한 VPP 와 City EMS," 대한전기학회 학술대회 논문집, 2017, pp. 147-154.
  8. 배인수, "신뢰도 가치와 경제성 평가를 고려한 가상발전소의 최적 구성," 한양대학교 박사학위논문, 2007.
  9. 손달호, "컴퓨터 시스템의 시뮬레이션 모델링에 대한 정보 구조의 구축에 관한 연구," 정보시스템연구, 제1권, 제1호, 1992, pp. 111-122.
  10. 여정훈, 하영복, 윤장한, 김균관, "분산형전원(비상발전기, ESS, 태양광발전)을 활용한 VPP(가상발전소) 기반 통합에너지관리기술," 한국조명.전기설비학회학술대회논문집, 2014, pp. 421-422.
  11. 오창진, 이종혁, 심현보, "국내외 계통운영보조서비스 현황 비교 연구," 대한전기학회학술대회논문집, 2013, pp. 474-475.
  12. 유승형, 노재구, 김홍석, "심층신경망 기반 전력수요예측 모델에 대한 연구," 한국통신학회 학술대회논문집, 2016, pp. 488-489.
  13. 이윤환, "분산발전자원을 활용한 가상발전소 기반 기술의 전력시장 참여 방안에 대한 연구," 전기학회논문지, Vol. 65, No. 2, 2016, pp. 94-100. https://doi.org/10.5370/KIEEP.2016.65.2.094
  14. 임정택, 이지은, 김태형, 함경선, "국내 전력수요자원시장을 고려한 VPP 시스템의 I-Smart Open API 적용," 한국정보과학회 학술발표논문집, 2015, pp. 16-17.
  15. 장형철, 김제현, 김태형, 함경선, "VPP 플랫폼 운용 접근성을 고려한 사용자 인터페이스 연구," 한국정보과학회 학술발표논문집, 2015, pp. 18-20.
  16. 정구형, 박만근, 허돈, "스마트그리드 하에서 가상발전소의 전력시장 참여를 위한 제도적 선결요건에 관한 제언," 전기학회논문지, Vol. 64, No. 3, 2015, pp. 375-383. https://doi.org/10.5370/KIEE.2015.64.3.375
  17. 조강희, "계량기 뒤의 전력시장 '가상발전소'," 한국에너지신문 기사, 2017.6.19.
  18. Antonanzas, J., Osorio, N., Escobar, R., Urraca, R., Martinez-De-Pison, F., and Antonanzas-Torres, F., "Review of Photovoltaic Power Forecasting," Solar Energy, Vol. 136, 2016, pp. 78-111. https://doi.org/10.1016/j.solener.2016.06.069
  19. Crisostomi, E., Gallicchio, C., Micheli, A., Raugi, M., and Tucci, M., "Prediction of the Italian Electricity Price for Smart Grid Applications," Neurocomputing, Vol. 170, 2015, pp. 286-295. https://doi.org/10.1016/j.neucom.2015.02.089
  20. IEA, Digitalization and Energy, October 2017.
  21. Ju, L., Tan, Z., Yuan, J., Tan, Q., Li, H., and Dong, F., "A Bi-Level Stochastic Scheduling Optimization Model for a Virtual Power Plant Connected to a Wind-Photovoltaic-Energy Storage System Considering the Uncertainty and Demand Response," Applied Energy, Vol. 171, 2016, pp. 184-199. https://doi.org/10.1016/j.apenergy.2016.03.020
  22. Jung, J., Broadwater, R. P., and Supplement, C., "Current Status and Future Advances for Wind Speed and Power Forecasting," Renewable and Sustainable Energy Reviews, Vol. 31, 2014, pp. 762-777. https://doi.org/10.1016/j.rser.2013.12.054
  23. Lombardi, P., Powalko, M., and Rudion, K., "Optimal Operation of a Virtual Power Plant," IEEE Power & Energy Society General Meeting(PES'09), 2009, pp. 1-6.
  24. Paluszek, M. and Thomas, S., Matlab Machine Learning, Apress, 2016.
  25. Saboori, H., Mohammadi, M., and Taghe, R., "Virtual Power Plant (VPP), Definition, Concept, Components and Types," Asia-Pacific Power and Energy Engineering Conference(APPEEC), 2011, pp. 1-4.
  26. Sumathi, S., Kumar, L. A., and Surekha, P., Solar Power and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with Matlab/Simulink, and the Role of Soft Computing Techniques, Springer, 2015.
  27. Voyant, C., Notton, G., Kalogirou, S., Nivet, M. L., Paoli, C., Motte, F., and Fouilloy, A., "Machine Learning Methods for Solar Radiation Forecasting: A Review," Renewable Energy, Vol. 105, 2017, pp. 569-582. https://doi.org/10.1016/j.renene.2016.12.095
  28. Zamani, A. G., Zakariazadeh, A., and Jadid, S., "Day-Ahead Resource Scheduling of a Renewable Energy Based Virtual Power Plant," Applied Energy, Vol. 169, 2016, pp. 324-340. https://doi.org/10.1016/j.apenergy.2016.02.011