Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Solar ESS Peak-cut Simulation Model for Customer

수용가 대응용 태양광 ESS 피크컷(Peak-cut) 시뮬레이션 모델

  • Received : 2019.05.02
  • Accepted : 2019.07.20
  • Published : 2019.07.28
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Abstract

The world's electricity production ratio is 40% for coal, 20% for natural gas, 16% for hydroelectric power, 15% for nuclear power and 6% for petroleum. Fossil fuels also cause serious problems in terms of price and supply because of the high concentration of resources on the earth. Solar energy is attracting attention as a next-generation eco-friendly energy that will replace fossil fuels with these problems. In this study, we test the charge-operation plan and the discharge operation plan for peak-cut operation by applying the maximum power demand reduction simulation. To do this, we selected the electricity usage from November to February, which has the largest amount of power usage, and applied charge / discharge logic. Simulation results show that the contract power decreases as the peak demand power after the ESS Peak-cut service is reduced to 50% of the peak-target power. As a result, the contract power reduction can reduce the basic power value of the customer and not only the economic superiority can be expected, but also contribute to the improvement of the electric quality and stabilization of the power supply system.

전 세계 전력 생산 에너지의 비율은 석탄이 40%, 천연가스 20%, 수력 16%, 원자력 15%, 석유 6%로 모두가 환경오염을 유발하는 에너지다. 또한 화석연료는 지구상에 자원의 편중이 심하기 때문에 가격과 공급면에서 심각한 문제를 야기한다. 이러한 문제로 화석 연료를 대체하게 될 차세대 친환경 에너지로써 태양광 에너지가 각광 받고 있다. 이에 본 연구에서는 국내 공단에 Test-Bed를 선정하여 수용가의 대응용 태양광 ESS 시스템 적용함에 있어 Peak-cut 운영을 위한 Charge Operation Plan과 Discharge Operation Plan 운영방안을 최대수요전력 감소 시뮬레이션을 통해 검증하고자 한다. 이를 위해 전력사용량이 가장 많은 11월부터 2월의 전력사용량을 선정하여 Charge/Discharge Logic을 적용했다. 본 논문에서 제시한 충전/방전 로직에 따른 시뮬레이션 결과, ESS Peak-cut 서비스 이후의 최대수요전력이 감소하였으며 Peak-target 전력의 50%로 감소함에 따라 계약전력 또한 감소함을 알 수 있다. 이를 통해 계약전력 감소는 해당 수용가의 기본 전력 값을 감소시켜, 경제적 우월성을 기대할 수 있을 뿐만 아니라 전기품질 향상 및 전력공급시스템의 안정화에도 기여할 수 있을 것으로 판단된다.

Keywords

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Fig. 1. Monthly power consumption

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Fig. 2. Daily Power Consumption

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Fig. 3. Consumed energy per hour

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Fig. 4. Charge operation plan

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Fig. 5. Discharge operation plan

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Fig. 6. February simulation results

Table 1. Current month Maximum demand

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Table 2. Charge logic

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Table 3. Discharge logic

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Table 4. February simulation results

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References

  1. S. Yoon, J. Kwon, J. Park & S. Choi. (2011). Indirect current control for seamless transfer of three-phase utility interactive inverters. IEEE Transactions on Power Electronics, 27(2), 773-781. DOI : 10.1109/APEC.2011.5744661
  2. S. Yu. (2018). 2030 Greenhouse Gas Reduction Roadmap and Power Sector Response. Journal of Electrical World Monthly Magazine. 20-26.
  3. J. S. Kim & U. J. Lee. (2009). Best Practices Research Use of Solar Energy For Low Carbon Green City. The Korean Solar Energy Society, 29(1), 37-42.
  4. K. S, Ahn, S. T. Lee & Y. S. Oh. (2018). Development of the Modular PCS for ESS with Hot-swap Function. Journal of the Korea Convergence Society, 9(3), 31-37. DOI : 10.15207/JKCS.2018.9.3.031
  5. K. I. Song. (2012). Current Status and Prospect of PV Power Industry in RPS. The Korean Society of Mechanical Engineers, 52(3), 42-46.
  6. G. J. You & K, Y, Park. (2003). Current status and prospects of future energy and photovoltaic technology. The Korean Society of Mechanical Engineers, 43(10), 41-47.
  7. H. Y. Kim. (2010). A Study on the Improvement of the Accuracy of Photovoltaic Facility Location Using the Geostatistical Analysis. Journal of the Korean Association of Geographic Information Studies, 13(2), 146-156 https://doi.org/10.11108/kagis.2010.13.2.146
  8. K, H. Lee, H. G. Son & S. Y. Kim, (2018). A study on solar energy forecasting based on time series models. Korean Journal of Applied Statistics, 31(1), 139-159. DOI : 10.5351/KJAS.2018.31.1.139.
  9. R. Hanna, J. Kleissl, A. Nottrott & M. Ferry (2014). Energy dispatch schedule optimization for demand charge reduction using a photovoltaic-battery storage system with solar forecasting. Solar Energy, 103, 269-287 DOI : 10.1016/j.solener.2014.02.020
  10. S. M. Park, C. S. Kim,L. D. Vuong, M. W. Park & I. K. Yu. (2016). Design of a Photovoltaic PCS with Compensation Control of Reactive Power and Unbalance Current in Three-phase systems. Jounal of the Korea Industrial Information Systems, 21(3), 29-33. DOI : 10.9723/jksiis.2016.21.3.029
  11. M. H. Kwon, S. H. Yang, H. J. Kim, S. W. Choi, D. W. Hwang, D. J. Lee & S. M. Paik (2015). A PCS Control Strategy for Hybrid ESS with Function of Emergency Power Supply. The Korean Institute of Power Electronics, 21(3), 403-404.
  12. C. Yao, M. Chen & Y. Hong, (2018). Novel Adaptive Multi-Clustering Algorithm-Based Optimal ESS Sizing in Ship Power System Considering Uncertainty. IEEE Transactions on Power Systems, 33(1), 307-316, DOI : 10.1109/TPWRS.2017.2695339
  13. H. T. Kim & S. S. Jhang. (2018). Key Technologies for Stabilization of Power System for Successful Achievement of 3020 Renewable Energy Policy. The Transactions of the Korean Institute of Electrical Engineers, 67(2), 149-157. DOI : 10.5370/KIEE.2018.67.2.149
  14. J. H. Lee, I. S. Lee, K. S. Jung, B. H. Chae, & J. Y. Lee (2017). Patents and Papers Trends of Solar-Photovoltaic(PV) Technology using LDA Algorithm. The Society of Digital Policy & Management, 15(9), 231-239. DOI : 10.14400/JDC.2017.15.9.231.
  15. J. W. Lim, D. H. Han, S. W. Kim, C. H. Ban, & J. M. Choi (2012). PV System with Battery Storage using Peak-cut Algorithm. The Korean Institute of Power Electronics Proceeding, 2012(11), 135-136.