Managing uncertainty in electricity generation and demand forecasting

The most readily accessed and abundant renewable energy sources—wind, hydro, and solar—are weather dependent and are therefore inherently intermittent. Energy demand is also dependent on the weather as well as many other difficult-to-model factors. In fact, there are many uncertainty factors that affect the modeling of both energy demand and renewable energy sources. In this paper, we begin with an overview of several of the underlying changes taking place in the energy industry and then specifically consider the uncertainty inherent in the forecasting of energy demand and wind power. We conclude with a discussion of techniques to integrate energy demand and the renewable energy supply, each with their associated uncertainty factors, in a stochastic environment to enable better informed business decisions.

[1]  C. Moehrlen.  Uncertainty in wind energy forecasting , 2004 .

[2]  Yannig Goude,et al.  Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting , 2012, NIPS.

[3]  Gregor Giebel,et al.  The State-Of-The-Art in Short-Term Prediction of Wind Power. A Literature Overview , 2003 .

[4]  H. Wang,et al.  Enabling coupled models to predict the business impact of weather on electric utilities , 2016, IBM J. Res. Dev..

[5]  Jianqing Fan,et al.  Efficient Estimation of Conditional Variance Functions in Stochastic Regression , 1998 .

[6]  Dzung T. Phan,et al.  Optimization Approaches to Security-Constrained Unit Commitment and Economic Dispatch with Uncertainty Analysis , 2013 .

[7]  Ehab F. El-Saadany,et al.  Overview of wind power intermittency impacts on power systems , 2010 .

[8]  Tri Kurniawan Wijaya,et al.  Forecasting Uncertainty in Electricity Demand , 2015, AAAI Workshop: Computational Sustainability.

[9]  Harriet Bulkeley,et al.  Peak electricity demand and the flexibility of everyday life , 2014 .

[10]  Soumyadip Ghosh,et al.  Two-stage stochastic optimization for optimal power flow under renewable generation uncertainty , 2014, ACM Trans. Model. Comput. Simul..

[11]  S. Kihm,et al.  Does Disruptive Competition Mean a Death Spiral for Electric Utilities , 2014 .

[12]  Lawrence E. Jones,et al.  Renewable Energy Integration: Practical Management of Variability, Uncertainty, and Flexibility in Power Grids , 2014 .

[13]  Aoife Foley,et al.  Current methods and advances in forecasting of wind power generation , 2012 .

[14]  Emilio Gómez-Lázaro,et al.  Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint , 2013 .