Cumulant-based correlated probabilistic load flow considering photovoltaic generation and electric vehicle charging demand

Nitesh Ganesh BHAT, B. Rajanarayan PRUSTY, Debashisha JENA

PDF(428 KB)
PDF(428 KB)
Front. Energy ›› 2017, Vol. 11 ›› Issue (2) : 184-196. DOI: 10.1007/s11708-017-0465-7
RESEARCH ARTICLE
RESEARCH ARTICLE

Cumulant-based correlated probabilistic load flow considering photovoltaic generation and electric vehicle charging demand

Author information +
History +

Abstract

This paper applies a cumulant-based analytical method for probabilistic load flow (PLF) assessment in transmission and distribution systems. The uncertainties pertaining to photovoltaic generations and aggregate bus load powers are probabilistically modeled in the case of transmission systems. In the case of distribution systems, the uncertainties pertaining to plug-in hybrid electric vehicle and battery electric vehicle charging demands in residential community as well as charging stations are probabilistically modeled. The probability distributions of the result variables (bus voltages and branch power flows) pertaining to these inputs are accurately established. The multiple input correlation cases are incorporated. Simultaneously, the performance of the proposed method is demonstrated on a modified Ward-Hale 6-bus system and an IEEE 14-bus transmission system as well as on a modified IEEE 69-bus radial and an IEEE 33-bus mesh distribution system. The results of the proposed method are compared with that of Monte-Carlo simulation.

Keywords

battery electric vehicle / extended cumulant method / photovoltaic generation / plug-in hybrid electric vehicle / probabilistic load flow

Cite this article

Download citation ▾
Nitesh Ganesh BHAT, B. Rajanarayan PRUSTY, Debashisha JENA. Cumulant-based correlated probabilistic load flow considering photovoltaic generation and electric vehicle charging demand. Front. Energy, 2017, 11(2): 184‒196 https://doi.org/10.1007/s11708-017-0465-7

References

[1]
Borkowska B. Probabilistic load flow. IEEE Transactions on Power Apparatus and Systems, 1974, PAS-93(3): 752–759
CrossRef Google scholar
[2]
Prusty B R, Jena  D. A critical review on probabilistic load flow studies in uncertainty constrained power systems with photovoltaic generation and a new approach. Renewable & Sustainable Energy Reviews, 2017, 69: 1286–1302
CrossRef Google scholar
[3]
Zhang P, Lee  S T. Probabilistic load flow computation using the method of combined cumulants and Gram-Charlier expansion. IEEE Transactions on Power Systems, 2004, 19(1): 676–682
CrossRef Google scholar
[4]
Usaola J. Probabilistic load flow in systems with wind generation. IET Generation, Transmission & Distribution, 2009, 3(12): 1031–1041
CrossRef Google scholar
[5]
Fan M, Vittal  V, Heydt G T ,  Ayyanar R . Probabilistic power flow studies for transmission systems with photovoltaic generation using cumulants. IEEE Transactions on Power Systems, 2012, 27(4): 2251–2261
CrossRef Google scholar
[6]
Villanueva D, Feijóo  A E, Pazos  J L. An analytical method to solve the probabilistic load flow considering load demand correlation using the DC load flow. Electric Power Systems Research, 2014, 110: 1–8
CrossRef Google scholar
[7]
Prusty B R, Jena  D. Modeling of correlated photovoltaic generations and load demands in probabilistic load flow. In: 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control (INDICON 2015), New Delhi, 2015, 1–6
[8]
Prusty B R, Jena  D. Combined cumulant and Gaussian mixture approximation for correlated probabilistic load flow studies: a new approach. CSEE Journal of Power and Energy Systems, 2016, 2(2): 71–78
CrossRef Google scholar
[9]
Conti S, Raiti  S. Probabilistic load flow using Monte Carlo techniques for distribution networks with photovoltaic generators. Solar Energy, 2007, 81(12): 1473–1481
CrossRef Google scholar
[10]
Ruiz-Rodriguez F J ,  Hernández J C ,  Jurado F . Probabilistic load flow for photovoltaic distributed generation using the Cornish–Fisher expansion. Electric Power Systems Research, 2012, 89: 129–138
CrossRef Google scholar
[11]
Carpinelli G, Caramia  P, Varilone P . Multi-linear Monte Carlo simulation method for probabilistic load flow of distribution systems with wind and photovoltaic generation systems. Renewable Energy, 2015, 76: 283–295
CrossRef Google scholar
[12]
Vlachogiannis J G . Probabilistic constrained load flow considering integration of wind power generation and electric vehicles. IEEE Transactions on Power Systems, 2009, 24(4): 1808–1817
CrossRef Google scholar
[13]
Pashajavid E, Golkar  M A. Charging of plug-in electric vehicles: stochastic modelling of load demand within domestic grids. In: Proceedings of 20th Iranian Conference on Electrical Engineering (ICEE2012), Tehran, 2012, 535–539
[14]
Kong S, Cho  H C, Lee  J U, Joo  S K. Probabilistic modeling of electric vehicle charging load for probabilistic load flow. In: 2012 IEEE Vehicle Power and Propulsion Conference (VPPC 2012), Seoul, Republic of Korea, 2012, 1010–1013
[15]
Wu C, Wen  F, Lou Y ,  Xin F. Probabilistic load flow analysis of photovoltaic generation system with plug-in electric vehicles. International Journal of Electrical Power & Energy Systems, 2015, 64: 1221–1228
CrossRef Google scholar
[16]
Papadopoulos P, Skarvelis-Kazakos  S, Grau I ,  Awad B, Cipcigan  L M, Jenkins  N. Impact of residential charging of electric vehicles on distribution networks, a probabilistic approach. In: Proceedings of 2010 45th International Universities’ Power Engineering Conference (UPEC), Cardiff, Wales, 2010, 1–5
[17]
Tehrani N H, Wang  P. Probabilistic estimation of plug-in electric vehicles charging load profile. Electric Power Systems Research, 2015, 124: 133–143
CrossRef Google scholar
[18]
Li G, Zhang  X P. Modeling of plug-in hybrid electric vehicle charging demand in probabilistic power flow calculations. IEEE Transactions on Smart Grid, 2012, 3(1): 492–499
CrossRef Google scholar
[19]
Dimitrovski A, Ackovski  R. Probabilistic load flow in radial distribution networks. In: Proceedings of the 1996 14th IEEE Transmission and Distribution Conference, Los Angeles, CA, 1996, 102–107
[20]
Golkar M A. A new probabilistic load-flow method for radial distribution networks. European Transactions on Electrical Power Systems, 2003, 13(3): 167–172
CrossRef Google scholar
[21]
Hoese A, Garcés  F. Stochastic correlated simulation: an extension of the cumulant method to include time-dependent energy sources. International Journal of Electrical Power & Energy Systems, 1999, 21(1): 13–22
CrossRef Google scholar
[22]
Cai D, Shi  D, Chen J . Probabilistic load flow computation with polynomial normal transformation and Latin hypercube sampling. IET Generation, Transmission & Distribution, 2013, 7(5): 474–482 doi:10.1049/iet-gtd.2012.0405
[23]
Pai M A, Chatterjee  D. Computer Techniques in Power System Analysis. 3rd ed. Noida: McGraw Hill Education (India) Private Limited, 2014
[24]
Electrical Engineering, University of Washington. Power systems test case archive, 2016-09-26. http://www2.ee.washington.edu/research/pstca
[25]
Kumar D, Agrawal  S. Load flow solution for meshed distribution networks. Dissertation for the Bachelor’s Degree. Rourkela: National Institute of Technology Rourkela, 2013

RIGHTS & PERMISSIONS

2017 Higher Education Press and Springer-Verlag Berlin Heidelberg
AI Summary AI Mindmap
PDF(428 KB)

Accesses

Citations

Detail

Sections
Recommended

/