A coordinated dispatching strategy for wind power rapid ramp events in power systems with high wind power penetration

Abstract High wind power penetration poses a challenge for the dispatch of the power system when rapid ramp events occur. This paper proposes an optimal dispatching strategy against wind power rapid ramp events during peak load periods by coordinating generation units with different time intervals. Special attention is given to the definition of the wind power rapid ramp events considering operation conditions of the system. Then, the online prediction of wind power rapid ramp events and its influence on the spinning reserve procurement of the system is analyzed. Based on the principle of coordination among generation units with different time intervals, the optimal dispatch during peak load periods when wind power rapid ramp events occur is formulated as an optimization problem considering thermal generation units, the energy storage system, interruptible load and load shedding. To improve computational efficiency, the power output calculation of the generation units with different time intervals is decomposed. The results show that the proposed dispatching strategy is feasible for accommodating wind power rapid ramp events during peak load periods.

[1]  Bijay Ketan Panigrahi,et al.  Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique , 2013 .

[2]  Kenneth Bruninx,et al.  A Statistical Description of the Error on Wind Power Forecasts for Probabilistic Reserve Sizing , 2014, IEEE Transactions on Sustainable Energy.

[3]  Chandrika Kamath,et al.  Associating weather conditions with ramp events in wind power generation , 2011, 2011 IEEE/PES Power Systems Conference and Exposition.

[4]  G. L. Torres,et al.  Robust Optimal Power Flow Solution Using Trust Region and Interior-Point Methods , 2011, IEEE Transactions on Power Systems.

[5]  Hamidreza Zareipour,et al.  Wind power ramp events classification and forecasting: A data mining approach , 2011, 2011 IEEE Power and Energy Society General Meeting.

[6]  Carlos Abreu Ferreira,et al.  A survey on wind power ramp forecasting. , 2011 .

[7]  Daniel S. Kirschen,et al.  Estimating the Spinning Reserve Requirements in Systems With Significant Wind Power Generation Penetration , 2009, IEEE Transactions on Power Systems.

[8]  João Gama,et al.  Predicting Ramp Events with a Stream-Based HMM Framework , 2012, Discovery Science.

[9]  Tomonobu Senjyu,et al.  A review of output power smoothing methods for wind energy conversion systems , 2013 .

[10]  Chun-Lung Chen,et al.  Optimal Wind–Thermal Generating Unit Commitment , 2008, IEEE Transactions on Energy Conversion.

[11]  Boon Teck Ooi,et al.  Impacts of Wind Power Minute-to-Minute Variations on Power System Operation , 2008, IEEE Transactions on Power Systems.

[12]  Chandrika Kamath,et al.  Understanding wind ramp events through analysis of historical data , 2009, IEEE PES T&D 2010.

[13]  C. Singh,et al.  Role of Clustering in the Probabilistic Evaluation of TTC in Power Systems Including Wind Power Generation , 2009, IEEE Transactions on Power Systems.

[14]  Kazem Zare,et al.  A solution to the generation scheduling problem in power systems with large-scale wind farms using MICA , 2014 .

[15]  Hoay Beng Gooi,et al.  Effective economic dispatch model and algorithm , 2007 .

[16]  M. O'Malley,et al.  A new approach to quantify reserve demand in systems with significant installed wind capacity , 2005, IEEE Transactions on Power Systems.

[17]  M. O'Malley,et al.  Unit Commitment for Systems With Significant Wind Penetration , 2009, IEEE Transactions on Power Systems.

[18]  P. Sauer,et al.  Wind power day-ahead uncertainty management through stochastic unit commitment policies , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[19]  M. Tripathy,et al.  Optimal power flow solution of wind integrated power system using modified bacteria foraging algorithm , 2014 .

[20]  Zongxiang Lu,et al.  A Consideration of the Wind Power Benefits in Day-Ahead Scheduling of Wind-Coal Intensive Power Systems , 2013, IEEE Transactions on Power Systems.

[21]  Zhang Kun,et al.  Study on unit commitment problem considering wind power and pumped hydro energy storage , 2014 .

[22]  S. Zachary,et al.  Challenges in quantifying wind generation's contribution to securing peak demand , 2011, IEEE Power & Energy Society General Meeting.

[23]  Cameron W. Potter,et al.  Potential benefits of a dedicated probabilistic rapid ramp event forecast tool , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.