지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.12 No.5
- 발행연도
- 2017.9
- 수록면
- 1,743 - 1,753 (11page)
이용수
초록· 키워드
오류제보하기
Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRSMCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.
목차
Abstract
1. Introduction
2. Probability Distribution Model for DG, EVCL, Random-state of Transmission Line
3. Composite Sampling Modeling for DG, EVCL, Random-state of Transmission Line
4. Non-parametric Kernel Density Estimation
5. Probabilistic Assessment of Voltage Quality Based on Composite Sampling Method
6. Case Study
7. Conclusion
References
참고문헌 (37)
참고문헌 신청
Doaa Khalil Ibrahim, Essam El Din Abo El Zahab, Saadoun Abd El Aziz Mostafa, “New Coordination Approach to Minimize the Number of Re-adjusted Relays When Adding DGs in Interconnected Power Systems,” Journal of Electrical Engineering & Technology, vol. 12, pp. 502-512, March.2017.
G. Marchesan, M.R. Muraro, G. Cardoso Jr, “Method for distributed generation anti-islanding protection based on singular value decomposition and linear discrimination analysis,” Electric Power Systems Research, vol. 130, pp. 124-131, Oct. 2016.
M. Fan, V. Vittal, G. Heydt, R. Ayyanar, “Probabilistic power flow analysis with generation dispatch including photovoltaic resource,” IEEE Transactions on Power Systems, vol. 28, pp. 1797-1805, Feb. 2013.
Wei CHEN, Hongqiang YAN, Xiping PEI, Butuo WU, “A Quasi Monte Carlo Probabilistic Load Flow Method of Distribution System Containing Distributed Generation and Electric Vehicle Charging Load Based on Sobol Sequence,” in Proceedings of the 7th China International Conference on Electricity Distribution, Xi'an, China, August 2016.
J. Romero-Ruiz, J. Perez-Ruiz, S. Martin, J. A. Aguado, S. De la Torre, “Probabilistic congestion management using EVs in a smart grid with intermittent renewable generation,” Electric Power Systems Research, vol. 137, pp. 155- 162, June. 2016.
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UCI(KEPA) : I410-ECN-0101-2018-560-001201727