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Electrical Analysis that identifies price spikes PYTHON

Background

Over the last couple of years wholesale power has averaged £40 - £50/MWh but has demonstrated increasing volatility, particularly in peak demand periods. It is fairly widely understood that the price of power can at certain times jump to very high levels (both in the wholesale market and particularly in the balancing system). We want to understand what the impact of price spikes is on the average wholesale cost of fuel for domestic customers.

Preparation

Attached are several data sets (in a single spreadsheet):

Cash-out SBP: Elexon data System Price (this is the price we pay for power at times when we have bought insufficient power on the wholesale market when we are ‘out of balance’. This should happen in a minority of time periods).

APX Day Ahead Auction: Hourly delivered price through the day-ahead auction

Domestic Consumption: typical half hourly domestic usage patterns

Feel free to use any, all or none of this data or you can pull other data that you think is useful to provide insight around this question.

The Task

Please prepare some analysis that identifies price spikes (your definition) and determines what the impact on the average cost of power is during the period. What impact might this have on domestic customer bills? How might you use this information?

Analysis can be performed through any appropriate method and results can be presented in any format that you like. We will expect you to provide an answer and talk us through the approach you took, including any decisions that you made in getting to an answer. Also, any conclusions that you might draw having been through this exercise.

Provide graphs and analysis and results in Python (Jupyter Notebook)

Evner: Elektrisk Ingeniørarbejde, Elektronik, Matematik, Python, Statistikker

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Om arbejdsgiveren:
( 0 bedømmelser ) London, United Kingdom

Projekt ID: #17148234

9 freelancere byder i gennemsnit £23 på dette job

codedancer3

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pushkarajbadbade

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