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Erik Murray: On modelling ancillary services markets

Time: Wed 2022-06-29 10.00 - 11.00

Location: Zoom

Video link: Meeting ID: 654 7952 8169

Doctoral student: Erik Murray


So-called ancillary services (AS) have always been critically important for the functioning of an electrical grid, and are becoming even more so with the advent of renewable energy sources.   Ancillary services are traded on open markets, and trading on these markets is arguably even more difficult to model than on traditional markets. This is, among other things, due to the limited availability of information such as current price, trading volume, etc., information that is typically available to traders on traditional markets. The goal of this thesis is to investigate whether the mean price of contracts on the FCR-D market (one of the AS markets) can be predicted with any useful accuracy using time series models, despite this scarcity of information.   Utilizing hourly mean price data ranging from the present moment to several years in the past, different specifications of ARIMA models are fitted to the data and their performance compared. The performance of these models' predictions are found to only barely outperform a naïve approach. The reasons for why this may be the case are investigated and discussed, and potential improvements utilizing approaches such as GARCH and trigonometric representations of seasonal components are presented. This thesis does not, however, present any conclusive evidence for or against the suitability of ARIMA models for forecasting the FCR-D market, nor does it investigate alternatives in detail.