Publication
Multi-step optimization of the purchasing options of power retailers to feed their portfolios of consumers
| dc.contributor.author | Algarvio, Hugo | |
| dc.date.accessioned | 2023-03-14T11:39:29Z | |
| dc.date.available | 2023-03-14T11:39:29Z | |
| dc.date.issued | 2022-11 | |
| dc.description.abstract | ABSTRACT: The liberalization of the retail market of electricity increased the tariff choice of end-use consumers. Retailers compete in the retail market for customers, obtaining private portfolios of end-use consumers to manage. Retailers buy electricity at wholesale markets to feed their customers' demands. They can use spot, derivatives, and bilateral markets to acquire the energy they need. The increasing levels of variable renewable energy sources trading at spot markets, increase the price volatility of these markets. To hedge against the volatility of spot prices, retailers may negotiate standard physical or financial bilateral contracts at derivatives markets. Alternatively, they can also negotiate private bilateral contracts. This article addresses the optimization of the retailers purchasing options, to increase their risk-return ratio from electricity markets, and offer more competitive tariffs to consumers. Considering the risk attitude of retailers, they use a multi-step purchasing model composed of a multi-level risk-return optimization and a decision support system. The article presents an agent-based study considering a retailer with a portfolio of 312 real-world consumers. Risk-seeking and risk-neutral retailers obtained a return up to 38%, less than 7% of the optimal return. However, risk-neutral retailers are subject to four times higher risk in their returns than risk-seeking retailers. The results support the conclusion that wholesale markets of electricity are more favourable to risk-seeking retailers, considering their real returns. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Algarvio, Hugo - Multi-step optimization of the purchasing options of power retailers to feed their portfolios of consumers. In: International Journal of Electrical Power and Energy Systems, 2022, vol. 142, article nº 108260 | pt_PT |
| dc.identifier.doi | 10.1016/j.ijepes.2022.108260 | pt_PT |
| dc.identifier.issn | 0142-0615 | |
| dc.identifier.uri | http://hdl.handle.net/10400.9/4030 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Elsevier | pt_PT |
| dc.relation | Tools for the Design and modelling of new markets and negotiation mechanisms for a ~100% Renewable European Power Systems | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.ijepes.2022.108260 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Electricity markets | pt_PT |
| dc.subject | Agent-based tools for energy markets | pt_PT |
| dc.subject | Risk management | pt_PT |
| dc.title | Multi-step optimization of the purchasing options of power retailers to feed their portfolios of consumers | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Tools for the Design and modelling of new markets and negotiation mechanisms for a ~100% Renewable European Power Systems | |
| oaire.awardURI | info:eu-repo/grantAgreement/EC/H2020/864276/EU | |
| oaire.citation.title | International Journal of Electrical Power and Energy Systems | pt_PT |
| oaire.citation.volume | 142 | pt_PT |
| oaire.fundingStream | H2020 | |
| person.identifier.ciencia-id | B01D-304F-6CD3 | |
| person.identifier.orcid | 0000-0002-4129-838X | |
| project.funder.identifier | http://doi.org/10.13039/501100008530 | |
| project.funder.name | European Commission | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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