Capacity allocation of a hybrid energy storage system for power system peak shaving at high wind power penetration level

High wind power penetration in power system leads to a significant challenge in balancing power production and consumption due to the intermittence of wind. Introducing energy storage system in wind energy system can help offset the negative effects, and make the wind power controllable. However, the power spectrum density of wind power outputs shows that the fluctuations of wind energy include various components with different frequencies and amplitudes. This implies that the hybrid energy storage system is more suitable for smoothing out the wind power fluctuations effectively rather than the independent energy storage system. In this paper, we proposed a preliminary scheme for capacity allocation of hybrid energy storage system for power system peak shaving by using spectral analysis method. The unbalance power generated from load dispatch plan and wind power outputs is decomposed into four components, which are outer-day, intra-day, short-term and very short-term components, by using Discrete Fourier Transform (DFT) and spectral decomposition method. The capacity allocation can be quantified according to the information in these components. The simulation results show that the power rating and energy rating of hybrid energy storage system in partial smoothing mode decrease significantly in comparison with those in fully smoothing mode.

[1]  S. Bhattacharya,et al.  Control Strategies for Battery Energy Storage for Wind Farm Dispatching , 2009, IEEE Transactions on Energy Conversion.

[2]  Mir-Akbar Hessami,et al.  Economic feasibility and optimisation of an energy storage system for Portland Wind Farm (Victoria, Australia) , 2011 .

[3]  Adrian Ilinca,et al.  Energy storage systems—Characteristics and comparisons , 2008 .

[4]  X.Y. Wang,et al.  Determination of Battery Storage Capacity in Energy Buffer for Wind Farm , 2008, IEEE Transactions on Energy Conversion.

[5]  Hamidreza Zareipour,et al.  Energy storage for mitigating the variability of renewable electricity sources: An updated review , 2010 .

[6]  Andreas Sumper,et al.  A review of energy storage technologies for wind power applications , 2012 .

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

[8]  K. A. Kavadias,et al.  Energy balance analysis of wind-based pumped hydro storage systems in remote island electrical networks , 2010 .

[9]  Magnus Korpaas,et al.  Operation and sizing of energy storage for wind power plants in a market system , 2003 .

[10]  Septimus van der Linden,et al.  Bulk energy storage potential in the USA, current developments and future prospects , 2006 .

[11]  Sanjit K. Mitra,et al.  Digital Signal Processing: A Computer-Based Approach , 1997 .

[12]  Jay Apt,et al.  The spectrum of power from wind turbines , 2007 .

[13]  Julio Usaola,et al.  Optimal operation of a pumped-storage hydro plant that compensates the imbalances of a wind power pr , 2011 .

[14]  H. Bludszuweit,et al.  A Probabilistic Method for Energy Storage Sizing Based on Wind Power Forecast Uncertainty , 2011, IEEE Transactions on Power Systems.

[15]  Pavlos S. Georgilakis,et al.  Technical challenges associated with the integration of wind power into power systems , 2008 .

[16]  Andrey V. Savkin,et al.  A model predictive control approach to the problem of wind power smoothing with controlled battery storage , 2010 .

[17]  Songyan Wang,et al.  Optimal sizing of the CAES system in a power system with high wind power penetration , 2012 .

[18]  M. Matos,et al.  Optimization of Pumped Storage Capacity in an Isolated Power System With Large Renewable Penetration , 2008, IEEE Transactions on Power Systems.