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ID: 162931

Changes to Gate Closure and its impact on wholesale electricity prices: the case of the UK / Facchini, Angelo

Facchini, Angelo	Journal Article
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Summary/Abstract

The electricity supply industry in the United Kingdom underwent a number of regulatory reforms since late 80's that have transformed the trading and pricing of the energy market. Herein we provide empirical evidence that the Modification Proposal P12 (Mod P12) - that took place in 7/2/2002 - moving the Gate Closure (GC) interval from 3.5 h to 1 h before real time has caused a permanent alteration in the UK spot price volatility. Using a combination of Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) we find that, after the the change in the GC time, short term price volatility significantly decreased between 2001 and 2008 while long term price volatility is not affected by CG change. Similar results are obtained by means of spectral analysis on the price series, showing a significant reduction in its variability. The results of our analysis suggest that a dynamical regime shift of the price occurred, and such shift is linked to the GC change whereby shorter GC intervals facilitate short-term forecasting on electricity demand and better reliability on the supply side. Therefore, GC closer to real time is associated to reduced price fluctuations in the wholesale market.

Key Words

Recurrence Plots ; Electricicty Markets ; Gate Closure ; UK Spot Prices ; New Electricity Trading Arrangements

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ID: 168689

Pattern identification for wind power forecasting via complex network and recurrence plot time series analysis / Charakopoulos, Avraam

Charakopoulos, Avraam	Journal Article
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Summary/Abstract

Renewable energy sources, where wind energy is an important part, are increasingly participating in developing economies and environmental benefits. Wind power is strongly dependent on wind velocity and thus identifying patterns in wind speed data is an important issue for forecasting the generated power from a wind turbine and it has significant importance for the renewable energy market operations. In this work we approach the problem of identification of the underlying dynamic characteristics and patterns of wind behavior using two approaches of non-linear time series analysis tools: Recurrence Plots (RPs) and Complex Network analysis. The proposed methodology is applied on wind time series collected by cup anemometers located on a wind turbine installed in Greece. We show that the proposed approach provides useful information which can characterize distinct two time intervals of the data, one ranging from 2 to 4.5 days and another from 5 to 8.5 days. Also analysis can identify and detect dynamical transitions in the system's behavior and also reveals information about the changes in state inside the whole time series. The results will be useful in wind markets, for the prediction of the produced wind energy and also will be helpful for wind farm site selection.

Key Words

Wind Energy Market ; Complex Networks ; Recurrence Plots ; Wind Forecasting

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