Dinh Duong LE, Nhi Thi Ai NGUYEN, Van Duong NGO, Alberto BERIZZI

Advanced probabilistic power ow methodology for power systems with renewable resources

Renewable resources have added additional uncertainty to power grids. Deterministic power ow does not provide sufficient information for power system calculation and analysis, since all sources of uncertainty are not taken into account. To handle uncertainties PPF has been introduced and used as an efficient tool. In this paper, we present a cumulant-based PPF approach that can account for various sources of uncertainty in power systems with renewable resources such as wind and photovoltaic energy. We also propose the use of a new methodology to estimate probability distribution for wind power output based on measured data. The proposed approach is carried out on a modi ed IEEE-14 bus test system. Simulation results of the proposed method are then compared with the result obtained by Monte Carlo simulation.

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[1] Borkowska B. Probabilistic load ow. IEEE T Power Ap Syst 1974; PAS-93: 752-759.
[2] Carpinelli G, Caramia P, Varilone P. Multi-linear Monte Carlo simulation method for probabilistic load ow of distribution systems with wind and photovoltaic generation systems. Renew Energ 2015; 76: 283-295.
[3] Hajian M, Rosehart WD, Zareipour H. Probabilistic power ow by Monte Carlo simulation with Latin supercube sampling. IEEE T Power Syst 2013; 28: 1550-1559.
[4] Su CL. Probabilistic load- ow computation using point estimate method. IEEE T Power Syst 2005; 20: 1843-1851.
[5] Aien M, Khajeh MG, Rashidinejad M, Fotuhi-Firuzabad M. Probabilistic power ow of correlated hybrid wind- photovoltaic power systems. IET Renew Power Gen 2014; 8: 649-658.
[6] Mohammadi M, Shayegani A, Adaminejad H. A new approach of point estimate method for probabilistic load ow. Int J Elec Power 2013; 51: 54-60.
[7] Allan RN, Al-Shakarchi MRG. Probabilistic techniques in A.C. load- ow analysis. P I Electr Eng 1977; 124: 154-160.
[8] Sanabria LA, Dillon TS. Stochastic power ow using cumulants and Von Mises functions. Int J Elec Power 2004; 8: 676-682.
[9] Zhang P, Lee TS. Probabilistic load ow computation using the method of combined cumulants and Gram-Charlier expansion. IEEE T Power Syst 2004; 19: 676-682.
[10] Yuan Y, Zhou J, Ju P, Feuchtwang J. Probabilistic load ow computation of a power system containing wind farms using the method of combined cumulants and Gram-Charlier expansion. IET Renew Power Gen 2011; 5: 448-454.
[11] Ruiz-Rodriguez FJ, Hernandez JC, Jurado F. Probabilistic load ow for radial distribution networks with photo- voltaic generators. IET Renew Power Gen 2012; 6: 110-121.
[12] Le DD, Berizzi A, Bovo C, Ciapessoni E, Cirio D, Pitto A, Gross G. A probabilistic approach to power system security assessment under uncertainty. In: Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid, 2013 IREP Symposium; 25{30 August 2013; Rethymnon, Greece. New York, NY, USA: IEEE. pp. 1-7.
[13] Usaola L. Probabilistic load ow with wind production uncertainty using cumulants and Cornish Fisher expansion. Int J Elec Power 2009; 31: 474-481.
[14] Fan M, Vittal V, Heydt GT, Ayyanar R. Probabilistic power ow studies for transmission systems with photovoltaic generation using cumulants. IEEE T Power Syst 2012; 27: 2251-2261.
[15] Zheng J, Wen F, Ledwich G, Huang J. Risk control in transmission system expansion planning with wind generators. Int T Electr Energy 2014, 24: 227-245.
[16] Hu Z, Wang X. A probabilistic load ow method considering branch outages. IEEE T Power Syst 2006; 21: 507-514.
[17] Gan G, Ma C, Wu J. Data Clustering: Theory, Algorithms, and Applications. Philadelphia, PA, USA: SIAM, 2007.
[18] Tian WD, Sutanto D, Lee YB, Outhred HR. Cumulant based probabilistic power system simulation using Laguerre polynomials. IEEE T Energy Conver 1989; 4: 567-574.
[19] Fabbri A, Roman TGS, Abbad JR, Quezada VHM. Assessment of the cost associated with wind generation prediction errors in a liberalized electricity market. IEEE T Power Syst 2005; 20: 1440-1446.