Dynamics of supplychain and market volatility of networks

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Dynamics of supply-chain and market volatility of
networks
WP5 UPDATE
Fernanda Strozzi Cattaneo University-LIUC Italy
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Contents

• Main results of D5.3 (Strozzi)
• Application of nonlinear time series (Nord Pool
  data)
• Correlation between Electricity prices and
• Disturbances (Nordel data)
• SVARs and DFMs for modeling electricity prices
  (Manera/Serati)
• General Model of Supply Chain (Rossi/Noè)

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D5.3 (M24) The study of electricity market
properties and its correlation with the faults in
the electricity newtork using Cross Recurrence
Quantification Analysis.

• 1. APPLICATION OF NON-LINEAR TIME SERIES ANALYSIS
  
• TECHNIQUES TO THE NORDIC SPOT ELECTRICITY MARKET
• DATA.
• a. LIUC paper 200, October 2007
• b. Time series analysis and long range
  correlations of Nordic spot electricity market
  data, Erzgraber, Strozzi, Zaldivar, Touchette,
  Gutierrez, Arrowsmith, Phy A
• c. Measuring volatility in the Nordic spot
  electricity market using Recurrence
  Quantification Analysis. Strozzi, Gutiérrez,
  Noè, Rossi, Serati and Zaldívar . European
  Journal of Physics-ST, 2008
• 2. CORRELATION ANALYSIS BETWEEN FAULTS IN THE
• ELECTTRICITY GRID AND SPOT PRICES IN THE NORDIC
• REGION.
• LIUC paper xxx, February 2009.
• Work in preparation for Energy Policy.

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D5.3 (M24) 1. APPLICATION OF NON-LINEAR TIME
SERIES ANALYSIS TECHNIQUES TO THE NORDIC SPOT
ELECTRICITY MARKET DATA

• Main Results
• R/S analysis confirms long range correlation and
  anti-persistence.
• Stable distribution fitting of electricity
  prices.
• Recurrence Quantification Analysis and in
  particular determinism is able to distinguish
  between real and surrogate (Gaussian with the
  same FFT) data.
• Determinism and laminarity as volatility
  measures. Dynamic-statistic properties.

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D5.3 (M24) 2. CORRELATION ANALYSIS BETWEEN
FAULTS IN THE ELECTTRICITY GRID AND ELECTRICITY
PRICES IN THE NORDIC REGION

• Main Results
• Disturbance volatility is linear correlated with
  price first differences using window of six or
  twelve months.
• w12, sh1, R0.7567, p0.0000
• w12, sh12, R0.8138, p0.0488
• w6, sh6, R -0.7778, p0.0017
• Applying PCA on the 12 time series obtained by S,
  D, T we found that to explain at least 90 of
  variance we need more than 3 principal
  components.

Linear correlation coefficient
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D5.3 (M24) 2. CORRELATION ANALYSIS BETWEEN
FAULTS IN THE ELECTTRICITY GRID AND SPOT PRICES
IN THE NORDIC REGION
Cross Correlation Function
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D5.3 (M24) 2. CORRELATION ANALYSIS BETWEEN
FAULTS IN THE ELECTTRICITY GRID AND SPOT PRICES
IN THE NORDIC REGION

• Cross Correlation function calculated using
  Disturbances and Spot prices (w2, sh1) has a
  regular oscillating behaviour even if it never
  reaches values higher than R0.4.

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D5.3 (M24) 2. CORRELATION ANALYSIS BETWEEN
FAULTS IN THE ELECTTRICITY GRID AND SPOT PRICES
IN THE NORDIC REGION
Cross Recurrence Plot

• Using Cross Recurrence Plot we
• identify time series that are linear
• correlated only on for some time.

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D5.3 (M24) 2. CORRELATION ANALYSIS BETWEEN
FAULTS IN THE ELECTTRICITY GRID AND SPOT PRICES
IN THE NORDIC REGION
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Example
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Key insight and results associated with the
deliverables D5.1-3

• D5.1 (M12). Supply-chain logical model by means
  of the Petri nets and its interconnection with
  the electric network . Modeling of the
  elementary components of a supply chain and
  their interconnection with the electric network.
• D5.2(M12) Literature analysis of electricity
  market dynamics models. Usually Statistical and
  not econometric models, univariate approach.
• D5.3 (M24) Study of the relationship between
  market volatility and the dynamics of power
  system using Cross Recurrence Quantification
  Analysis. A linear correlation exists between
  Prices and disturbacies.
• D5.4 (M30) coupled market, power systems and
  supply chain dynamics.
• D5.5 (M36) Early warning detection algorithm and
  suggestions on how implement it in real systems.

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LIUC collaboration to date and planned for the
future

• JRC and Queen Mary
• 1_Time series analysis and long range
  correlations of Nordic spot electricity market
  data, H.Erzgraber, F. Strozzi, J.M. Zaldivar,
  H.Touchette, E. Gutierrez, D.K.Arrowsmith,
   Physica A, 2008
• 2_ Measuring volatility in the Nordic spot
  electricity market using Recurrence
  Quantification Analysis. F. Strozzi,
  E.Gutiérrez, C. Noè, T. Rossi, M.Serati and J.M.
  Zaldívar . European Journal of Physics-ST, 2008.
• NESA Quantifying and ranking risks. C. Colicchia,
  H. Sivonen, C. Noè, F. Strozzi. IPMA world
  congress Rome 9-11 Nov 2008
• COLB (to be discussed)
• MASA (to be discussed about supply chain
  vulnerability and the aplication of Markov chain
  model)

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Outreach activities LIUC efforts

• International Conference on applied simulation
  and modeling,
• Corfù (June 2008)
• Analysis of complex systems by means of
  mathematical and simulation methods (Noè/Rossi) .
  
• EDF (Électricité de France)
• The 23rd European Conference on Operational
  Research
• EURO XXIII, Bonn, July 5- 8  2009
• Streem Methodology of Societal Complexity
• MANMADE project (accepted)
• Ranking vulnerability in a supply chain (in
  preparation)

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Update of deliverable D5.5 (M36)Early warning
detection algorithm and suggestions on how to
implement it in real systems ..

• Analysis of the divergence operator for the
  stability evaluation of a small electric network
  weakly connected to the main electric network or
  isolated and in which one node is constituted by
  a source of renewable energy.
• We will study the transient stability of the
  system due for example to an external
  perturbation or a fault or a generator
  malfunction or to the non constant supply of a
  renewable source.

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Update of deliverable D5.5 (M36)

• The perturbations have direct implications on the
  balance of the active power i.e. on the dynamic
  equilibrium of the electric network.
• After the perturbation a transient appears in
  which the net frequency increases or decreases.
• The feedback on the system can be a signal of
  correction for this balance.
• Note this work will be done in collaboration
  with the electric engineering department of
  Politecnico of Milan.
• They already started to develop the electric
  model.

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Brief plan /update ofRemaining deliverables

• D5.4 (M30) coupling between electricity market
  and supply chain model (Rossi, Serati, Noè,
  Manera, JRC)
• Vulnerability of a supply chain using influence
  model work in progress (Colicchia, Strozzi, Noè,
  MASA, QUML). (T5.6)
• D5.5 (M36) Early warning detection algorithm and
  suggestions on how to implement it in real
  systems (Strozzi, COLB?)

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WP5 Tasks overview
EWDS of Blackouts T5.4
Coupling models Task5.5
Electricity price Model T5.1
Interaction Risk T5.6
Electric power Model T5.1
Correlation Analysis(T5.2-T5.3)
Supply chain Model T5.1, T5.5
Energy spot prices Volatility
Blackouts Volatility
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Conferences DISSEMINATION 1_ Analysis of
complex systems by means of mathematical and
simulation methods (Noè/Rossi) . International
Conference on applied simulation and modeling,
Corfù (June 2008) 2_ Quantifying and ranking
risks. C. Colicchia, H. Sivonen, C. Noè, F.
Strozzi. IPMA world congress Rome 9-11 Nov
2008 3_Application of RQA to Financial Time
Series, F. Strozzi, J.M. Zaldivar, J.
Zbilut, Second International workshop on
Recurrence Plot, Siena, 10-12 September
2007. Reports -Application of non-linear time
series analysis techniques to the Nordic spot
electricity market F. Strozzi, E.Gutiérrez, C.
Noè, T. Rossi, M.Serati and J.M.Zaldívar. LIUC
Paper 200,October 2007 -Deliverables D5.1,
D5.2 Papers 1_Time series analysis and long range
correlations of Nordic spot electricity market
data, H.Erzgraber, F. Strozzi, J.M. Zaldivar,
H.Touchette, E. Gutierrez, D.K.Arrowsmith,
 Physica A 2_ Measuring volatility in the Nordic
spot electricity market using Recurrence
Quantification Analysis. F. Strozzi,
E.Gutiérrez, C. Noè, T. Rossi, M.Serati and J.M.
Zaldívar . European Journal of Physics-ST,
2008 3_ A supply chain as a serie of filter or
amplificators of the bullwhip effect . Caloiero,
G., Strozzi, F., Zaldívar, J.M., 2007.
International Journal of Production Economics
2008 4_Control and on-line optimization of one
level supply chain, F. Strozzi, C.Noè, J.M.
Zaldivar, submitted to IJPE, 2008