Quantitative risk associated with intermittent wind generation

Wind energy is a propitious alternative to fossil-fuel generation due to its benign environmental footprint and sustainability. However, the intermittent nature of wind turbine output may scale up the risk of not meeting current or future load demand. A quantitative risk measure associated with introducing wind turbines into the generation fleet is investigated in this paper. Due to the randomness of the wind speed profile, a common wind speed model employing a multistate wind generation pattern, representing various production levels, was adopted, as opposed to conventional generator models, which are suitably represented with a two-state model. Using a hybrid method that combines the analytical technique with Monte Carlo simulation, risk measures such as loss of load probability were evaluated and applied to the RBTS and IEEE-RTS test systems. The expected demand not supplied, due to contemplated uncertainties, was further quantified. Test results show that the capacity credit of wind turbine generators could vary widely depending on system size and configuration. Furthermore, the use of an 11-state wind representation model along with the normal distribution of wind speed produces very close results compared with the Weibull distribution of wind speed.

PDF

___

[1] Panwar NL, Kaushik SC, Kothari S. Role of renewable energy sources in environmental protection: a review. Renew Sust Energ Rev 2011; 15: 1513-1524.
[2] Billinton R, Allan RN. Reliability Evaluation of Power Systems. 2nd ed. New York, NY, USA: Plenum Press, 1996.
[3] Peng W, Zhiyong G, Bertling L. Operational adequacy studies of power systems with wind farms and energy storages. IEEE T Power Syst 2012; 27: 2377-2384.
[4] Dragoon K, Dvortsov V. Z-method for power system resource adequacy applications. IEEE T Power Syst 2006; 21: 982-988.
[5] DAnnunzio C, Santoso S. Noniterative method to approximate the effective load carrying capability of a wind plant. IEEE T Energy Conver 2008; 23: 544-550.
[6] Ghaedi A, Abbaspour A, Fotuhi-Firuzabad M, Moeini-Aghtaie M. Toward a comprehensive model of large-scale DFIG-based wind farms in adequacy assessment of power systems. IEEE T Sust Energ 2014; 5: 55-63.
[7] Keane A, Milligan M, Dent CJ, Hasche B, DAnnunzio C, Dragoon K, Holttinen H, Samaan N, Soder L, OMalley M. Capacity value of wind power. IEEE T Power Syst 2011; 26: 564-572.
[8] Billinton R, Guang B. Generating capacity adequacy associated with wind energy. IEEE T Energy Conver 2004; 19: 641-646.
[9] Karki R, Po H, Billinton R. A simplified wind power generation model for reliability evaluation. IEEE T Energy Conver 2006; 21: 533-540.
[10] Conroy J, Watson R. Aggregate modelling of wind farms containing full-converter wind turbine generators with permanent magnet synchronous machines: transient stability studies. IET Renew Power Gen 2009; 3: 39-52.
[11] Billinton R, Li W. Reliability Assessment of Electric Power Systems Using Monte Carlo Methods. New York, NY, USA: Plenum Press, 1994.
[12] Dimitrovski A, Tomsovic K. Impact of wind generation uncertainty on generating capacity adequacy. In: 2006 Probabilistic Methods Applied to Power Systems (PMAPS) Conference; 1115 June 2006; Stockholm, Sweden. New York, NY, USA: IEEE. pp. 1-6.
[13] Nor KM, Shaaban M, Abdul Rahman H. Feasibility assessment of wind energy resources in Malaysia based on NWP models. Renew Energ 2014; 62: 147-154.
[14] Jaeseok C, Jeongje P, Kyeonghee C, Taegon O, Shahidehpour M. Probabilistic reliability evaluation of composite power systems including wind turbine generators. In: 2010 Probabilistic Methods Applied to Power Systems (PMAPS) Conference; 1417 June 2010; Singapore. New York, NY, USA: IEEE. pp. 802-807.
[15] Gao Y, Billinton R. Adequacy assessment of generating systems containing wind power considering wind speed correlation. IET Renew Power Gen 2009; 3: 217-226.
[16] Sharaf TAM, Berg GJ. Loadability in composite generation/transmission power-system reliability evaluation. IEEE T Reliab 1993; 42: 393-400.
[17] Billinton R, Kumar S, Chowdhury N, Chu K, Goel L, Khan E, Kos P, Nourbakhsh G, Oteng-Adjei J. A reliability test system for educational purposes-basic results. IEEE T Power Syst 1990; 5: 319-325.
[18] Shaaban M, Bell K. Assessment of tradable short-term transmission access rights to integrate renewable generation. In: 2009 Universities Power Engineering Conference (UPEC); 14 September 2009. pp. 1-5.
[19] Rios SM, Vidal VP, Kiguel DL. Bus-based reliability indices and associated costs in the bulk power system. IEEE T Power Syst 1998; 13: 719-724.