Loading…

Modelling interregional links in electricity price spikes

Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models...

Full description

Saved in:
Bibliographic Details
Published in:Energy economics 2015-09, Vol.51, p.383-393
Main Authors: Clements, A.E., Herrera, R., Hurn, A.S.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c484t-84b37b55a5a72a53a1116bd7ea5531b2c6bd8072916492bbbc332c3510ce5ec53
cites cdi_FETCH-LOGICAL-c484t-84b37b55a5a72a53a1116bd7ea5531b2c6bd8072916492bbbc332c3510ce5ec53
container_end_page 393
container_issue
container_start_page 383
container_title Energy economics
container_volume 51
creator Clements, A.E.
Herrera, R.
Hurn, A.S.
description Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models have been proposed to deal with spikes within an individual market region. This paper is the first to develop a multivariate self-exciting point process model for dealing with price spikes across connected regions in the Australian National Electricity Market. The importance of the physical infrastructure connecting the regions on the transmission of spikes is examined. It is found that spikes are transmitted between the regions, and the size of spikes is influenced by the available transmission capacity. It is also found that improved risk estimates are obtained when inter-regional linkages are taken into account. •First to consider price spikes across the Australian Electricity market regions•Multivariate Hawkes model developed for the intensity of spikes in multiple regions•Intensity and size of price spikes are dealt with.•Transmission of spikes is conditional on physical infrastructure linking regions.•Allowing for links between regions gives superior forecasts of spikes.
doi_str_mv 10.1016/j.eneco.2015.07.014
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1761667732</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0140988315002285</els_id><sourcerecordid>3867119261</sourcerecordid><originalsourceid>FETCH-LOGICAL-c484t-84b37b55a5a72a53a1116bd7ea5531b2c6bd8072916492bbbc332c3510ce5ec53</originalsourceid><addsrcrecordid>eNqNkD1PwzAQhi0EEqXwC1gisbAk-OL4IwMDqviSilhgthznWjlN42KnSP33uJSJATGd_Op5T-eHkEugBVAQN12BA1pflBR4QWVBoToiE1CS5QIUHJNJSmheK8VOyVmMHaWUC64mpH7xLfa9G5aZG0YMAZfOD6bPUrSKKcuwRzsGZ924yzZpYhY3boXxnJwsTB_x4mdOyfvD_dvsKZ-_Pj7P7ua5rVQ15qpqmGw4N9zI0nBmAEA0rUTDOYOmtOmhqCxrEFVdNk1jGSst40AtcrScTcn1Ye8m-I8txlGvXbTpZjOg30YNUoAQUrLyHyhXdUWlFAm9-oV2fhvSx_cUY6AErVii2IGywccYcKGTgbUJOw1U783rTn-b13vzmkqdPKfW7aGFScunw6CjdThYbF1ILnXr3Z_9LxUei3c</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1733186043</pqid></control><display><type>article</type><title>Modelling interregional links in electricity price spikes</title><source>International Bibliography of the Social Sciences (IBSS)</source><source>Elsevier</source><source>PAIS Index</source><creator>Clements, A.E. ; Herrera, R. ; Hurn, A.S.</creator><creatorcontrib>Clements, A.E. ; Herrera, R. ; Hurn, A.S.</creatorcontrib><description>Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models have been proposed to deal with spikes within an individual market region. This paper is the first to develop a multivariate self-exciting point process model for dealing with price spikes across connected regions in the Australian National Electricity Market. The importance of the physical infrastructure connecting the regions on the transmission of spikes is examined. It is found that spikes are transmitted between the regions, and the size of spikes is influenced by the available transmission capacity. It is also found that improved risk estimates are obtained when inter-regional linkages are taken into account. •First to consider price spikes across the Australian Electricity market regions•Multivariate Hawkes model developed for the intensity of spikes in multiple regions•Intensity and size of price spikes are dealt with.•Transmission of spikes is conditional on physical infrastructure linking regions.•Allowing for links between regions gives superior forecasts of spikes.</description><identifier>ISSN: 0140-9883</identifier><identifier>EISSN: 1873-6181</identifier><identifier>DOI: 10.1016/j.eneco.2015.07.014</identifier><identifier>CODEN: EECODR</identifier><language>eng</language><publisher>Kidlington: Elsevier B.V</publisher><subject>Australia ; Classification ; Economic forecasting ; Electric power ; Electric rates ; Electricity ; Electricity distribution ; Electricity prices ; Electricity pricing ; Energy economics ; Energy policy ; Forecasting ; Hawkes process ; Infrastructure ; Markets ; Mathematical models ; Peaks over threshold ; Point process ; Price increases ; Price spikes ; Prices ; Probability ; Public infrastructure ; Risk ; Spikes ; Studies ; Time series ; Transmission capacity</subject><ispartof>Energy economics, 2015-09, Vol.51, p.383-393</ispartof><rights>2015 Elsevier B.V.</rights><rights>Copyright Elsevier Science Ltd. Sep 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c484t-84b37b55a5a72a53a1116bd7ea5531b2c6bd8072916492bbbc332c3510ce5ec53</citedby><cites>FETCH-LOGICAL-c484t-84b37b55a5a72a53a1116bd7ea5531b2c6bd8072916492bbbc332c3510ce5ec53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27846,27847,27905,27906,33204,33205</link.rule.ids></links><search><creatorcontrib>Clements, A.E.</creatorcontrib><creatorcontrib>Herrera, R.</creatorcontrib><creatorcontrib>Hurn, A.S.</creatorcontrib><title>Modelling interregional links in electricity price spikes</title><title>Energy economics</title><description>Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models have been proposed to deal with spikes within an individual market region. This paper is the first to develop a multivariate self-exciting point process model for dealing with price spikes across connected regions in the Australian National Electricity Market. The importance of the physical infrastructure connecting the regions on the transmission of spikes is examined. It is found that spikes are transmitted between the regions, and the size of spikes is influenced by the available transmission capacity. It is also found that improved risk estimates are obtained when inter-regional linkages are taken into account. •First to consider price spikes across the Australian Electricity market regions•Multivariate Hawkes model developed for the intensity of spikes in multiple regions•Intensity and size of price spikes are dealt with.•Transmission of spikes is conditional on physical infrastructure linking regions.•Allowing for links between regions gives superior forecasts of spikes.</description><subject>Australia</subject><subject>Classification</subject><subject>Economic forecasting</subject><subject>Electric power</subject><subject>Electric rates</subject><subject>Electricity</subject><subject>Electricity distribution</subject><subject>Electricity prices</subject><subject>Electricity pricing</subject><subject>Energy economics</subject><subject>Energy policy</subject><subject>Forecasting</subject><subject>Hawkes process</subject><subject>Infrastructure</subject><subject>Markets</subject><subject>Mathematical models</subject><subject>Peaks over threshold</subject><subject>Point process</subject><subject>Price increases</subject><subject>Price spikes</subject><subject>Prices</subject><subject>Probability</subject><subject>Public infrastructure</subject><subject>Risk</subject><subject>Spikes</subject><subject>Studies</subject><subject>Time series</subject><subject>Transmission capacity</subject><issn>0140-9883</issn><issn>1873-6181</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><sourceid>8BJ</sourceid><recordid>eNqNkD1PwzAQhi0EEqXwC1gisbAk-OL4IwMDqviSilhgthznWjlN42KnSP33uJSJATGd_Op5T-eHkEugBVAQN12BA1pflBR4QWVBoToiE1CS5QIUHJNJSmheK8VOyVmMHaWUC64mpH7xLfa9G5aZG0YMAZfOD6bPUrSKKcuwRzsGZ924yzZpYhY3boXxnJwsTB_x4mdOyfvD_dvsKZ-_Pj7P7ua5rVQ15qpqmGw4N9zI0nBmAEA0rUTDOYOmtOmhqCxrEFVdNk1jGSst40AtcrScTcn1Ye8m-I8txlGvXbTpZjOg30YNUoAQUrLyHyhXdUWlFAm9-oV2fhvSx_cUY6AErVii2IGywccYcKGTgbUJOw1U783rTn-b13vzmkqdPKfW7aGFScunw6CjdThYbF1ILnXr3Z_9LxUei3c</recordid><startdate>201509</startdate><enddate>201509</enddate><creator>Clements, A.E.</creator><creator>Herrera, R.</creator><creator>Hurn, A.S.</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TA</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>JBE</scope><scope>JG9</scope><scope>SOI</scope></search><sort><creationdate>201509</creationdate><title>Modelling interregional links in electricity price spikes</title><author>Clements, A.E. ; Herrera, R. ; Hurn, A.S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c484t-84b37b55a5a72a53a1116bd7ea5531b2c6bd8072916492bbbc332c3510ce5ec53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Australia</topic><topic>Classification</topic><topic>Economic forecasting</topic><topic>Electric power</topic><topic>Electric rates</topic><topic>Electricity</topic><topic>Electricity distribution</topic><topic>Electricity prices</topic><topic>Electricity pricing</topic><topic>Energy economics</topic><topic>Energy policy</topic><topic>Forecasting</topic><topic>Hawkes process</topic><topic>Infrastructure</topic><topic>Markets</topic><topic>Mathematical models</topic><topic>Peaks over threshold</topic><topic>Point process</topic><topic>Price increases</topic><topic>Price spikes</topic><topic>Prices</topic><topic>Probability</topic><topic>Public infrastructure</topic><topic>Risk</topic><topic>Spikes</topic><topic>Studies</topic><topic>Time series</topic><topic>Transmission capacity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Clements, A.E.</creatorcontrib><creatorcontrib>Herrera, R.</creatorcontrib><creatorcontrib>Hurn, A.S.</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Materials Business File</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Materials Research Database</collection><collection>Environment Abstracts</collection><jtitle>Energy economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Clements, A.E.</au><au>Herrera, R.</au><au>Hurn, A.S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modelling interregional links in electricity price spikes</atitle><jtitle>Energy economics</jtitle><date>2015-09</date><risdate>2015</risdate><volume>51</volume><spage>383</spage><epage>393</epage><pages>383-393</pages><issn>0140-9883</issn><eissn>1873-6181</eissn><coden>EECODR</coden><abstract>Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models have been proposed to deal with spikes within an individual market region. This paper is the first to develop a multivariate self-exciting point process model for dealing with price spikes across connected regions in the Australian National Electricity Market. The importance of the physical infrastructure connecting the regions on the transmission of spikes is examined. It is found that spikes are transmitted between the regions, and the size of spikes is influenced by the available transmission capacity. It is also found that improved risk estimates are obtained when inter-regional linkages are taken into account. •First to consider price spikes across the Australian Electricity market regions•Multivariate Hawkes model developed for the intensity of spikes in multiple regions•Intensity and size of price spikes are dealt with.•Transmission of spikes is conditional on physical infrastructure linking regions.•Allowing for links between regions gives superior forecasts of spikes.</abstract><cop>Kidlington</cop><pub>Elsevier B.V</pub><doi>10.1016/j.eneco.2015.07.014</doi><tpages>11</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0140-9883
ispartof Energy economics, 2015-09, Vol.51, p.383-393
issn 0140-9883
1873-6181
language eng
recordid cdi_proquest_miscellaneous_1761667732
source International Bibliography of the Social Sciences (IBSS); Elsevier; PAIS Index
subjects Australia
Classification
Economic forecasting
Electric power
Electric rates
Electricity
Electricity distribution
Electricity prices
Electricity pricing
Energy economics
Energy policy
Forecasting
Hawkes process
Infrastructure
Markets
Mathematical models
Peaks over threshold
Point process
Price increases
Price spikes
Prices
Probability
Public infrastructure
Risk
Spikes
Studies
Time series
Transmission capacity
title Modelling interregional links in electricity price spikes
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T05%3A32%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Modelling%20interregional%20links%20in%20electricity%20price%20spikes&rft.jtitle=Energy%20economics&rft.au=Clements,%20A.E.&rft.date=2015-09&rft.volume=51&rft.spage=383&rft.epage=393&rft.pages=383-393&rft.issn=0140-9883&rft.eissn=1873-6181&rft.coden=EECODR&rft_id=info:doi/10.1016/j.eneco.2015.07.014&rft_dat=%3Cproquest_cross%3E3867119261%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c484t-84b37b55a5a72a53a1116bd7ea5531b2c6bd8072916492bbbc332c3510ce5ec53%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1733186043&rft_id=info:pmid/&rfr_iscdi=true