Multi-temporal assessment of power system flexibility requirement

In power systems, flexibility can be defined as the ability to adapt to variability and uncertainty in demand and generation. Various ongoing changes in the power system are impacting the need for flexibility. We propose a novel methodology to (i) evaluate annual, weekly and daily flexibility requirements through a set of frequency spectrum analysis based metrics, (ii) examine the sensitivity of these flexibility requirements to five variables: the degree of network interconnection and the penetration of wind power, solar power, electric heating and cooling. The proposed methodology is validated on a case study focusing on the French power system, while accounting for its electrically connected neighbours. We provide an estimation of how flexibility requirements are likely to evolve in years to come; the use of global sensitivity analysis allows the identification of the variables responsible for these evolutions. The presented methodology and results can be used to identify future challenges, to evaluate the market potential of flexibility solutions and to assess the implications of policy decisions.

[1]  Soteris A. Kalogirou,et al.  An adaptive wavelet-network model for forecasting daily total solar-radiation , 2006 .

[2]  Peter Lund,et al.  Review of energy system flexibility measures to enable high levels of variable renewable electricity , 2015 .

[3]  Damian Flynn,et al.  Transmission, Variable Generation, and Power System Flexibility , 2015, IEEE Transactions on Power Systems.

[4]  Michael E. Webber,et al.  The impacts of wind and solar on grid flexibility requirements in the Electric Reliability Council of Texas , 2017 .

[5]  William D'haeseleer,et al.  Considerations on the need for electricity storage requirements: Power versus energy , 2017 .

[6]  Florian Steinke,et al.  Grid vs. storage in a 100% renewable Europe , 2013 .

[7]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[8]  Thomas Hamacher,et al.  Integration of wind and solar power in Europe: Assessment of flexibility requirements , 2014 .

[9]  M. O'Malley,et al.  Power system flexibility assessment — State of the art , 2012, 2012 IEEE Power and Energy Society General Meeting.

[10]  Eunsung Oh,et al.  Energy-storage system sizing and operation strategies based on discrete Fourier transform for reliable wind-power generation , 2018 .

[11]  J.P. Barton,et al.  Energy storage and its use with intermittent renewable energy , 2004, IEEE Transactions on Energy Conversion.

[12]  Ahmet Yucekaya,et al.  Forecasting electricity demand for Turkey: Modeling periodic variations and demand segregation , 2017 .

[13]  Richard A. Buswell,et al.  The implications of heat electrification on national electrical supply-demand balance under published 2050 energy scenarios , 2016 .

[14]  I. Sobola,et al.  Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates , 2001 .

[15]  Hendrik Kondziella,et al.  Flexibility requirements of renewable energy based electricity systems – a review of research results and methodologies , 2016 .

[16]  Eduardo Zarza,et al.  Uncertainty and global sensitivity analysis in the design of parabolic-trough direct steam generation plants for process heat applications , 2014 .

[17]  Por Lip Yee,et al.  Estimating the diffuse solar radiation using a coupled support vector machine–wavelet transform model , 2016 .

[18]  Jan Carmeliet,et al.  Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems , 2018 .

[19]  Robin Girard,et al.  A generic GIS-based method for small Pumped Hydro Energy Storage (PHES) potential evaluation at large scale , 2017 .

[20]  Ana Estanqueiro,et al.  Variability of Load and Net Load in Case of Large Scale Distributed Wind Power , 2010 .

[21]  Ming-Chao Huang,et al.  Oscillation characteristic study of wind speed, global solar radiation and air temperature using wavelet analysis , 2017 .

[22]  Pengwei Du,et al.  Sizing Energy Storage to Accommodate High Penetration of Variable Energy Resources , 2012, IEEE Transactions on Sustainable Energy.

[23]  René M.J. Benders,et al.  Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands , 2009 .

[24]  Alexander Zerrahn,et al.  Long-run power storage requirements for high shares of renewables: review and a new model , 2017 .

[25]  Robin Girard,et al.  LCA of emerging technologies: addressing high uncertainty on inputs' variability when performing global sensitivity analysis. , 2017, The Science of the total environment.

[26]  Gunnar S. Eskeland,et al.  Electricity demand in a changing climate , 2010 .

[27]  Robin Girard,et al.  Sensitivity analysis in the technical potential assessment of onshore wind and ground solar photovoltaic power resources at regional scale , 2016 .

[28]  Dietmar Lindenberger,et al.  The role of grid extensions in a cost-efficient transformation of the European electricity system until 2050 , 2013 .

[29]  W. Ackooij,et al.  Dynamic Constraints for Aggregated Units: Formulation and Application , 2011, IEEE Transactions on Power Systems.

[30]  Harald G. Svendsen,et al.  A generic framework for power system flexibility analysis using cooperative game theory , 2018 .

[31]  Luis F. Ochoa,et al.  Evaluating and planning flexibility in sustainable power systems , 2013, 2013 IEEE Power & Energy Society General Meeting.

[32]  Pranab J. Baruah,et al.  Uncertainties in future energy demand in UK residential heating , 2015 .

[33]  Paola Annoni,et al.  Sixth International Conference on Sensitivity Analysis of Model Output How to avoid a perfunctory sensitivity analysis , 2010 .

[34]  Hannele Holttinen,et al.  The Flexibility Workout: Managing Variable Resources and Assessing the Need for Power System Modification , 2013, IEEE Power and Energy Magazine.

[35]  R. Belhomme,et al.  Evaluating and planning flexibility in sustainable power systems , 2013, 2013 IEEE Power & Energy Society General Meeting.

[36]  Luai M. Al-Hadhrami,et al.  Extraction of the inherent nature of wind speed using wavelets and FFT , 2014 .

[37]  Saltelli Andrea,et al.  Global Sensitivity Analysis: The Primer , 2008 .

[38]  I. Staffell,et al.  The Shape of Future Electricity Demand: Exploring Load Curves in 2050s Germany and Britain , 2015 .

[39]  Maximilian Auffhammer,et al.  North–south polarization of European electricity consumption under future warming , 2017, Proceedings of the National Academy of Sciences.

[40]  Kameshwar Poolla,et al.  Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform , 2016 .