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Estimation of cross-border flow in electricity markets using a Markovian-Tobit approach
KTH, School of Electrical Engineering (EES).
2016 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In an electricity price forecast model the influence from connected external electricity markets affects the supply. In order to predict electricity prices in a supply and demand model one can increase the accuracy by predicting the import or export from the connected markets if the connected market models are not price optimized towards each other. There is a limit for the maximum transfer capacity of electricity between the markets and the capacity is changing in time. This thesis investigates methods of predicting the influence from connected markets by using cross validation. A multiple linear regression model is compared with varieties of the Tobit model, a model that accounts for limited or censored variables. An extension is made using Markov regime shifting models in order to evaluate if this can capture more dynamics and increase the predictive power. The result shows that a special case of the Tobit model that accounts for a time varying limit increases the accuracy of the prediction compared to the other models. The Markov regime shifting models add a greater level of complexity to the prediction, but can increase the predictive power in some cases.

Abstract [sv]

Elpriset kan estimeras i en modell som tar hänsyn till tillgång och efterfrågan på elmarknaden. I en sådan prognosmodell för elpriser på elmarknaden påverkar sammankopplade elmarknader tillgången på elektricitet i modellen. Om en angränsande marknad inte har prisoptimerats mot den gällande marknadsmodellen kan en prognos för import och export av el förbättra prisprognosen. ¨Överföringskapaciteten, den maximala mängden el som kan importeras eller exporteras mellan marknaderna är begränsad och kapaciteten skiftar i tiden. Detta arbete ¨ämnar att genom korsvalidering undersöka metoder för att estimera ett sådant begränsat flöde av elektricitet mellan två marknader. En multipel linjär regression är jämförd med varianter av Tobit modellen, en modell som hanterar avgränsat data. Denna modell är utökad med gömda Markovprocesser för att undersöka om detta kan minska felet i prediktionen. Resultatet visar att ett specialfall av Tobitmodellen som kan hantera en skiftande kapacitet i tiden minskar felet på prediktionen. Markov processerna ökar komplexiteten för prediktionen, men kan minska felet i prognosen i vissa fall.

Place, publisher, year, edition, pages
2016. , 89 p.
Series
EES Examensarbete / Master Thesis, TRITA 2016:040
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-187673OAI: oai:DiVA.org:kth-187673DiVA: diva2:931064
Examiners
Available from: 2016-05-26 Created: 2016-05-26 Last updated: 2016-05-26Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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