Smoothing effect for spatially distributed renewable resources and its impact on power grid robustness.

In this paper, we show that spatial correlation of renewable energy outputs greatly influences the robustness of the power grids against large fluctuations of the effective power. First, we evaluate the spatial correlation among renewable energy outputs. We find that the spatial correlation of renewable energy outputs depends on the locations, while the influence of the spatial correlation of renewable energy outputs on power grids is not well known. Thus, second, by employing the topology of the power grid in eastern Japan, we analyze the robustness of the power grid with spatial correlation of renewable energy outputs. The analysis is performed by using a realistic differential-algebraic equations model. The results show that the spatial correlation of the energy resources strongly degrades the robustness of the power grid. Our results suggest that we should consider the spatial correlation of the renewable energy outputs when estimating the stability of power grids.

[1]  M. Timme,et al.  Critical Links and Nonlocal Rerouting in Complex Supply Networks. , 2015, Physical review letters.

[2]  G. Filatrella,et al.  Analysis of a power grid using a Kuramoto-like model , 2007, 0705.1305.

[3]  Peter J. Menck,et al.  How basin stability complements the linear-stability paradigm , 2013, Nature Physics.

[4]  Hideyuki Suzuki,et al.  Wind direction modelling using multiple observation points , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[5]  Matthias Wachter,et al.  Fatigue Load Estimation through a Simple Stochastic Model , 2014, 1410.8005.

[6]  Shintaro Komami,et al.  A Study on a Method for Presuming Total Output Fluctuation of Highly Penetrated Photovoltaic Generation Considering Mutual Smoothing Effect in a Narrow Area like Distribution Line Level , 2013 .

[7]  Marc Timme,et al.  Decentral Smart Grid Control , 2015 .

[8]  A. Díaz-Guilera,et al.  Role of network topology in the synchronization of power systems , 2012, 1207.0406.

[9]  J. Peinke,et al.  Turbulent character of wind energy. , 2013, Physical review letters.

[10]  Andrej Gajduk,et al.  Improving power grid transient stability by plug-in electric vehicles , 2014, ArXiv.

[11]  Jobst Heitzig,et al.  How dead ends undermine power grid stability , 2014, Nature Communications.

[12]  Marc Timme,et al.  Self-organized synchronization in decentralized power grids. , 2012, Physical review letters.

[13]  M. Kato,et al.  Voltage assessment of distribution network with large penetration of PVs by probabilistic approach , 2013 .

[14]  Shintaro Komami,et al.  A Method for Presuming Total Output Fluctuation of Highly Penetrated Photovoltaic Generation Considering Mutual Smoothing Effect , 2014 .

[15]  Zhang Yan,et al.  A review on the forecasting of wind speed and generated power , 2009 .

[16]  Denki Gakkai.  IEEJ transactions on electrical and electronic engineering , 2006 .

[17]  Kazuyuki Aihara,et al.  Predicting multivariate time series in real time with confidence intervals: Applications to renewable energy , 2014 .

[18]  Lubos Buzna,et al.  Synchronization in symmetric bipolar population networks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Tatsuma Matsuo,et al.  Cascade Failure in a Phase Model of Power Grids , 2012, 1205.6561.

[20]  Florian Dörfler,et al.  Synchronization and transient stability in power networks and non-uniform Kuramoto oscillators , 2009, Proceedings of the 2010 American Control Conference.

[21]  Bae.  50 % , 2018, CME.

[22]  Gouhei Tanaka,et al.  Node-wise robustness against fluctuations of power consumption in power grids , 2014 .

[23]  M. Timme,et al.  Braess's paradox in oscillator networks, desynchronization and power outage , 2012 .

[24]  Kazuyuki Aihara,et al.  Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers , 2012, Scientific Reports.

[25]  Pravin Varaiya,et al.  Foundations of direct methods for power system transient stability analysis , 1987 .

[26]  Joachim Peinke,et al.  Self-organized synchronization and voltage stability in networks of synchronous machines , 2013, ArXiv.