A Bi-Level Multi-Objective System for Renewable Energy Self-Consumption: A Resident-Aware Approach to Leveraging Energy Flexibility
The efficient exploitation of renewable energy sources is crucial for addressing the global energy crisis and increase in CO2 emissions. Energy management system aggregators, functioning as nonprofit cooperatives within energy communities, manage renewable energy resources and incentivize residents...
Saved in:
| Published in: | IEEE transactions on evolutionary computation p. 1 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
IEEE
2025
|
| Subjects: | |
| ISSN: | 1089-778X, 1941-0026 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | The efficient exploitation of renewable energy sources is crucial for addressing the global energy crisis and increase in CO2 emissions. Energy management system aggregators, functioning as nonprofit cooperatives within energy communities, manage renewable energy resources and incentivize residents towards self-consumption through dynamic, cost-attractive pricing schemes, receiving subsidies and long-term contracts as reward. This interaction between aggregator and residents is typically modeled using bi-level optimization frameworks, however, research studies often ignore the role of aggregators as self-consumption catalysts and the conflicting nature of the residents' objectives. Moreover, lack of cooperation between the decision levels results in inflexible decision making when prioritizing between the respective objectives. This paper defines and formulates a bi-level multi-objective optimization problem for optimizing self-consumption in energy communities, while considering the residents' welfare by maximizing satisfaction of their appliance-scheduling preferences and minimizing energy costs. We introduce the Bi-level Multi-Objective Energy Management System II (BiMO-EMS-II), composed of an Adaptive Population Transfer strategy, a Uniform Partially Mapped Crossover and a Decision Making heuristic with Cooperation. Our experimental evaluation has shown that BiMO-EMS-II simultaneously offers near-optimal self-consumption at the aggregator level and a high-quality trade-off between the conflicting objectives at the resident level, subject to different objective prioritization and decision-making assumptions. |
|---|---|
| AbstractList | The efficient exploitation of renewable energy sources is crucial for addressing the global energy crisis and increase in CO2 emissions. Energy management system aggregators, functioning as nonprofit cooperatives within energy communities, manage renewable energy resources and incentivize residents towards self-consumption through dynamic, cost-attractive pricing schemes, receiving subsidies and long-term contracts as reward. This interaction between aggregator and residents is typically modeled using bi-level optimization frameworks, however, research studies often ignore the role of aggregators as self-consumption catalysts and the conflicting nature of the residents' objectives. Moreover, lack of cooperation between the decision levels results in inflexible decision making when prioritizing between the respective objectives. This paper defines and formulates a bi-level multi-objective optimization problem for optimizing self-consumption in energy communities, while considering the residents' welfare by maximizing satisfaction of their appliance-scheduling preferences and minimizing energy costs. We introduce the Bi-level Multi-Objective Energy Management System II (BiMO-EMS-II), composed of an Adaptive Population Transfer strategy, a Uniform Partially Mapped Crossover and a Decision Making heuristic with Cooperation. Our experimental evaluation has shown that BiMO-EMS-II simultaneously offers near-optimal self-consumption at the aggregator level and a high-quality trade-off between the conflicting objectives at the resident level, subject to different objective prioritization and decision-making assumptions. |
| Author | Pamboris, Andreas Konstantinidis, Andreas Papakyriakou, Thalis |
| Author_xml | – sequence: 1 givenname: Thalis orcidid: 0009-0008-0176-1713 surname: Papakyriakou fullname: Papakyriakou, Thalis – sequence: 2 givenname: Andreas orcidid: 0000-0002-4877-6663 surname: Pamboris fullname: Pamboris, Andreas – sequence: 3 givenname: Andreas orcidid: 0000-0001-5370-8692 surname: Konstantinidis fullname: Konstantinidis, Andreas |
| BookMark | eNpFkMtKw0AYhQepYFt9AMHFvMDUmUkmF3cxtCpUCraKuzCXP3VKmoRJ2pq1L25DK67OWZwLfCM0KKsSELpldMIYje9X0490wikXE0_EEfeCCzRksc8IpTwYHD2NYhKG0ecVGjXNhlLmCxYP0U-CHy2Zwx4K_LorWksWagO6tXvAy65pYYvzyuE3KOEgVQF4WoJbd3gJRU7Sqmx227q1VfmAk2OosQbKliQH6QAnde0qqb9wW-H-wMm1Ldd_A7MCvq2yhW27a3SZy6KBm7OO0ftsukqfyXzx9JImc6KZJ1oCkVIB50YYnwutY5YHIjDScKNlBLmIdeBJyZgMcgGRUEKbMFc0MEyB9LXxxoiddrWrmsZBntXObqXrMkaznmLWU8x6itmZ4rFzd-pYAPjPM8Z9HnLvFxcAc3A |
| CODEN | ITEVF5 |
| ContentType | Journal Article |
| DBID | 97E RIA RIE AAYXX CITATION |
| DOI | 10.1109/TEVC.2025.3598236 |
| DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE/IET Electronic Library (IEL) (UW System Shared) CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE/IET Electronic Library (IEL) (UW System Shared) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Computer Science |
| EISSN | 1941-0026 |
| EndPage | 1 |
| ExternalDocumentID | 10_1109_TEVC_2025_3598236 11124272 |
| Genre | orig-research |
| GroupedDBID | -~X .DC 0R~ 29I 4.4 5GY 6IF 6IK 6IL 6IN 97E AAJGR AARMG AASAJ AAWTH ABAZT ABJNI ABQJQ ABVLG ACGFO ACGFS ACIWK ADZIZ AENEX AGQYO AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CHZPO CS3 EBS HZ~ IEGSK IFIPE IPLJI JAVBF LAI M43 O9- OCL P2P PQQKQ RIA RIE RIL RNS TN5 5VS AAYXX AETIX AGSQL AI. AIBXA ALLEH CITATION EJD H~9 IFJZH VH1 |
| ID | FETCH-LOGICAL-c135t-e8bb622d5d425cc91f656dad2dca8ef59c63aa11a6f5e85b5cd7fb06d1bea4cd3 |
| IEDL.DBID | RIE |
| ISSN | 1089-778X |
| IngestDate | Sat Nov 29 07:37:51 EST 2025 Wed Aug 20 06:20:37 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c135t-e8bb622d5d425cc91f656dad2dca8ef59c63aa11a6f5e85b5cd7fb06d1bea4cd3 |
| ORCID | 0009-0008-0176-1713 0000-0002-4877-6663 0000-0001-5370-8692 |
| PageCount | 1 |
| ParticipantIDs | crossref_primary_10_1109_TEVC_2025_3598236 ieee_primary_11124272 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-00-00 |
| PublicationDateYYYYMMDD | 2025-01-01 |
| PublicationDate_xml | – year: 2025 text: 2025-00-00 |
| PublicationDecade | 2020 |
| PublicationTitle | IEEE transactions on evolutionary computation |
| PublicationTitleAbbrev | TEVC |
| PublicationYear | 2025 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0014519 |
| Score | 2.4557023 |
| Snippet | The efficient exploitation of renewable energy sources is crucial for addressing the global energy crisis and increase in CO2 emissions. Energy management... |
| SourceID | crossref ieee |
| SourceType | Index Database Publisher |
| StartPage | 1 |
| SubjectTerms | bi-level optimization Computational modeling Costs Decision making Energy management systems Evolutionary computation evolutionary multi-objective optimization evolutionary transfer optimization Load modeling multi-criteria decision making Optimization Production Renewable energy sources self-consumption Stakeholders |
| Title | A Bi-Level Multi-Objective System for Renewable Energy Self-Consumption: A Resident-Aware Approach to Leveraging Energy Flexibility |
| URI | https://ieeexplore.ieee.org/document/11124272 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVIEE databaseName: IEEE/IET Electronic Library (IEL) (UW System Shared) customDbUrl: eissn: 1941-0026 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014519 issn: 1089-778X databaseCode: RIE dateStart: 19970101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELagYoCBQimivOSBCclt4iR2whaqVgxVQVCqbpGfEgilKKRUzPxxbCelXRjYosh5SJ99vvPd9x0AVzoJQxwyhTyiKDLxl0Bc6BjxmAYBw5gTx0qbjuh4HM9myUNNVndcGKWUKz5TXXvpcvlyLhb2qKxn1qXZUaixuNuUkoqs9ZsysDopVTV9YlzGeFanMH0v6U0G074JBXHUdXp1To55vQltdFVxm8qw-c_fOQD7tfcI0wruQ7Cl8hZorjozwHqhtsDehszgEfhO4e0LGtnyIOgIt-iev1aGDlaK5dC4rvDRmL2lZVLBgSMEwif1plHfcTSdYbmBqRlk-3vmJUqXrFAwrSXJYTmH9gOFa3q0esHQqm266tuvNngeDib9O1Q3X0DCD6ISqZhzgrGMpFnVQiS-Np6fZBJLwWKlo0SQgDHfZ0RHKo54JCTV3CPS54qFQgbHoJHPc3UCoJYcayp8QYx3xiVm1PbICgJPmNiGEdYB1ys0svdKYyNzsYmXZBa6zEKX1dB1QNsisR5Yg3D6x_0zsGsfr05NzkGjLBbqAuyIz_Llo7h0U-gHU-vGxg |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NS8MwFA8yBfXgdCrOzxw8Cdna9NtbHRsT6xSdY7eST5hIJ7VzePYfN0k7t4sHb6WEpPDre3kveb_fA-BSRq6LXSKQ5YsAqfyLIcpkiGgYOA7BmPqGlTZKgsEgHI-jx4qsbrgwQghTfCZa-tHc5fMpm-mjsrayS7WjBMrjrntqCauka_1eGmillLKePlJBYziuLjFtK2oPu6OOSgax1zKKdUaQebkNrfRVMdtKr_7PD9oFO1X8COMS8D2wJrIGqC96M8DKVBtge0VocB98x_BmghJdIAQN5RY90NfS1cFSsxyq4BU-Kcc311wq2DWUQPgs3iTqGJamcS3XMFaDdIfPrEDxnOQCxpUoOSymUC-Qm7ZHiwl6Wm_T1N9-HYCXXnfY6aOq_QJituMVSISU-hhzjyu7ZiyypYr9OOGYMxIK6UXMdwixbeJLT4Qe9RgPJLV8blNBXMadQ1DLppk4AlByimXAbOar-IxyTALdJctxLKayG-KTJrhaoJG-lyobqclOrCjV0KUaurSCrgkONBLLgRUIx3-8vwCb_eF9kia3g7sTsKWnKs9QTkGtyGfiDGywz2LykZ-b3-kH0oLKDQ |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Bi-Level+Multi-Objective+System+for+Renewable+Energy+Self-Consumption%3A+A+Resident-Aware+Approach+to+Leveraging+Energy+Flexibility&rft.jtitle=IEEE+transactions+on+evolutionary+computation&rft.au=Papakyriakou%2C+Thalis&rft.au=Pamboris%2C+Andreas&rft.au=Konstantinidis%2C+Andreas&rft.date=2025&rft.issn=1089-778X&rft.eissn=1941-0026&rft.spage=1&rft.epage=1&rft_id=info:doi/10.1109%2FTEVC.2025.3598236&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TEVC_2025_3598236 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1089-778X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1089-778X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1089-778X&client=summon |