Modelling Prices in Competitive Electricity MarketsDerek W. Bunn Electricity markets are structurally different to othercommodities, and the real-time dynamic balancing of the electricitynetwork involves many external factors. Because of this, it is nota simple matter to transfer conventional models of financial timeseries analysis to wholesale electricity prices. The rationale for this compilation of chapters from internationalauthors is, therefore, to provide econometric analysis of wholesalepower markets around the world, to give greater understanding oftheir particular characteristics, and to assess the applicabilityof various methods of price modelling. Researchers and professionals in this sector will find the book aninvaluable guide to the most important state-of-the-art modellingtechniques which are converging to define the special approachesnecessary for unravelling and forecasting the behaviour ofelectricity prices. It is a high-quality synthesis of the work offinancial engineering, industrial economics and power systemsanalysis, as they relate to the behaviour of competitiveelectricity markets. |
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Page 183
... conditional covariance matrix models . Conditional volatility in high - frequency data is due mainly to the clustering phenomenon , so that periods of high ( low ) variability tend to be followed by periods of high ( low ) variability ...
... conditional covariance matrix models . Conditional volatility in high - frequency data is due mainly to the clustering phenomenon , so that periods of high ( low ) variability tend to be followed by periods of high ( low ) variability ...
Page 221
... conditional expected price equation accommodates each market's own prices and the prices of other markets lagged one period : P = a + AP1 - 1 + εj ~ ( 10.1 ) where P is an n x 1 vector of daily prices at time t for each market and ɛ ...
... conditional expected price equation accommodates each market's own prices and the prices of other markets lagged one period : P = a + AP1 - 1 + εj ~ ( 10.1 ) where P is an n x 1 vector of daily prices at time t for each market and ɛ ...
Page 258
... Conditional forecast for the forward curve Our conditional prediction model uses the estimated parameters of the previous section to calculate the corresponding forward curve from a spot price scenario . In order to analyze our ...
... Conditional forecast for the forward curve Our conditional prediction model uses the estimated parameters of the previous section to calculate the corresponding forward curve from a spot price scenario . In order to analyze our ...
Contents
Structural and Behavioural Foundations of Competitive Electricity Prices | 1 |
ComplementarityBased Equilibrium Modeling for Electric Power Markets | 69 |
Price Impact of Horizontal Mergers in the British Generation Market | 99 |
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Common terms and phrases
analysis applied AR-GARCH autoregressive average behaviour bidding capacity CCGT clustering coal coefficients competitive conditional constraints correlation Cournot covariance daily day-ahead distribution dynamics Economics effect electricity markets electricity prices electricity trading arrangements Energy England and Wales equation equilibrium estimated fall-winter Figure firms forecast forward contracts forward curve forward price futures prices GARCH model hourly indicator Innogy innovations input lags linear load Lyapunov exponent marginal cost market power market price matrix mean method NETA node Nord Pool null hypothesis off-peak Ofgem optimal option p-value parameters peak period plant price modelling price spikes principal component problem quantile function residual demand function risk management scenarios seasonal Section sector significant simulation spark spread spot markets spot price spring-summer statistic stochastic structure suppliers supply function Table temperature trading transmission unit root variance volatility wholesale zero