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...
Saved in:
Published in: | Energy economics 2015-09, Vol.51, p.383-393 |
---|---|
Main Authors: | , , |
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 |