{"id":{"repo_id":"bradford","oai_identifier":"oai:bradscholars.brad.ac.uk:10454/20755"},"canonical_url":"https://search.dev.ndltd.org/etd/bradford/oai:bradscholars.brad.ac.uk:10454/20755","repository":{"repo_id":"bradford","name":"University of Bradford","base_url":"https://bradscholars.brad.ac.uk/oai/request"},"display":{"title":"Planning and Operation of Multi-Vector Energy System with High Penetration of Renewable Energy Sources","abstract":"The increasing penetration of renewable energy sources (RESs) into current electricity network introduces challenges to the planning and operation of electricity network due to the intermittent nature of the resources which will result in variability and uncertainty in electricity supply. The power-to-gas (P2G) technologies, gas-fired units (GFUs) and demand response programs (DRPs) potentials are practical solutions to overcome these challenges and if exploited it will provide some level of flexibility needed in the system. Hence, to achieve this, the effective integration of electricity and gas networks (IEGN) via P2G and GFUs is required, and the process of this integration is known as multi energy systems (MES). This work presents basic principles of integrating RESs into MES and particularly focuses on IEGN via P2G and GFUs. In this thesis, a novel technique that applied the stochastic approach for the expansion planning model of a IEGN coupled with GFUs. P2G, and RESs is proposed. The projected model minimised the total planning costs of IEGN when compared to the traditional planning models that considered both gas and electricity networks separately. The model is recast using mixed integer linear programming that is solved by the General Algebraic Modelling software. In addition, a bi-level bidding strategy for GFUs, P2G and RESs in a coordinated energy market considering DRPs is proposed. The upper-level model is projected to maximizes profits, while the lower-level maximizes social welfare. Finally, a realistic case study (16-bus UK electricity and 20-node Belgium gas networks) is used to demonstrate effectiveness of proposed method.","abstract_html":"The increasing penetration of renewable energy sources (RESs) into current electricity network introduces challenges to the planning and operation of electricity network due to the intermittent nature of the resources which will result in variability and uncertainty in electricity supply. The power-to-gas (P2G) technologies, gas-fired units (GFUs) and demand response programs (DRPs) potentials are practical solutions to overcome these challenges and if exploited it will provide some level of flexibility needed in the system. Hence, to achieve this, the effective integration of electricity and gas networks (IEGN) via P2G and GFUs is required, and the process of this integration is known as multi energy systems (MES). This work presents basic principles of integrating RESs into MES and particularly focuses on IEGN via P2G and GFUs. In this thesis, a novel technique that applied the stochastic approach for the expansion planning model of a IEGN coupled with GFUs. P2G, and RESs is proposed. The projected model minimised the total planning costs of IEGN when compared to the traditional planning models that considered both gas and electricity networks separately. The model is recast using mixed integer linear programming that is solved by the General Algebraic Modelling software. In addition, a bi-level bidding strategy for GFUs, P2G and RESs in a coordinated energy market considering DRPs is proposed. The upper-level model is projected to maximizes profits, while the lower-level maximizes social welfare. Finally, a realistic case study (16-bus UK electricity and 20-node Belgium gas networks) is used to demonstrate effectiveness of proposed method.","abstract_has_math":false,"creators":["Onen, Patrick S."],"institution":"University of Bradford","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Abd-Alhameed, Raed","Li, Jian-Ping","Mokryani, Geev"],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T01:15:08Z","subjects":["Multi-Vector energy systems","Electricity distribution networks","Natural gas distribution networks","Energy market","Uncertainty modelling","Energy hub","Renewable energy sources","Planning and operation","Optimization","Demand response"],"languages":["en"],"rights":["\"Creative
The University of Bradford theses are licenced under a Creative Commons Licence."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://bradscholars.brad.ac.uk/handle/10454/20755","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Abd-Alhameed, Raed","Li, Jian-Ping","Mokryani, Geev"]},{"key":"dc:creator","label":"Author","values":["Onen, Patrick S."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-01-27T15:26:56Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-01-27T15:26:56Z"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Computer Science, AI, and Electronics. Faculty of Engineering and Digital Technologies"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Bradford"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Multi-Vector energy systems","Electricity distribution networks","Natural gas distribution networks","Energy market","Uncertainty modelling","Energy hub","Renewable energy sources","Planning and operation","Optimization","Demand response"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["\"Creative
The University of Bradford theses are licenced under a Creative Commons Licence."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://bradscholars.brad.ac.uk/handle/10454/20755"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The increasing penetration of renewable energy sources (RESs) into current electricity network introduces challenges to the planning and operation of electricity network due to the intermittent nature of the resources which will result in variability and uncertainty in electricity supply. The power-to-gas (P2G) technologies, gas-fired units (GFUs) and demand response programs (DRPs) potentials are practical solutions to overcome these challenges and if exploited it will provide some level of flexibility needed in the system. Hence, to achieve this, the effective integration of electricity and gas networks (IEGN) via P2G and GFUs is required, and the process of this integration is known as multi energy systems (MES). This work presents basic principles of integrating RESs into MES and particularly focuses on IEGN via P2G and GFUs. In this thesis, a novel technique that applied the stochastic approach for the expansion planning model of a IEGN coupled with GFUs. P2G, and RESs is proposed. The projected model minimised the total planning costs of IEGN when compared to the traditional planning models that considered both gas and electricity networks separately. The model is recast using mixed integer linear programming that is solved by the General Algebraic Modelling software. In addition, a bi-level bidding strategy for GFUs, P2G and RESs in a coordinated energy market considering DRPs is proposed. The upper-level model is projected to maximizes profits, while the lower-level maximizes social welfare. Finally, a realistic case study (16-bus UK electricity and 20-node Belgium gas networks) is used to demonstrate effectiveness of proposed method."]},{"key":"dc:title","label":"Title","values":["Planning and Operation of Multi-Vector Energy System with High Penetration of Renewable Energy Sources"]}]}],"canonical_facts":{"dc:contributor.advisor":["Abd-Alhameed, Raed","Li, Jian-Ping","Mokryani, Geev"],"dc:creator":["Onen, Patrick S."],"dc:date.accessioned":["2026-01-27T15:26:56Z"],"dc:date.available":["2026-01-27T15:26:56Z"],"dc:description.abstract":["The increasing penetration of renewable energy sources (RESs) into current electricity network introduces challenges to the planning and operation of electricity network due to the intermittent nature of the resources which will result in variability and uncertainty in electricity supply. The power-to-gas (P2G) technologies, gas-fired units (GFUs) and demand response programs (DRPs) potentials are practical solutions to overcome these challenges and if exploited it will provide some level of flexibility needed in the system. Hence, to achieve this, the effective integration of electricity and gas networks (IEGN) via P2G and GFUs is required, and the process of this integration is known as multi energy systems (MES). This work presents basic principles of integrating RESs into MES and particularly focuses on IEGN via P2G and GFUs. In this thesis, a novel technique that applied the stochastic approach for the expansion planning model of a IEGN coupled with GFUs. P2G, and RESs is proposed. The projected model minimised the total planning costs of IEGN when compared to the traditional planning models that considered both gas and electricity networks separately. The model is recast using mixed integer linear programming that is solved by the General Algebraic Modelling software. In addition, a bi-level bidding strategy for GFUs, P2G and RESs in a coordinated energy market considering DRPs is proposed. The upper-level model is projected to maximizes profits, while the lower-level maximizes social welfare. Finally, a realistic case study (16-bus UK electricity and 20-node Belgium gas networks) is used to demonstrate effectiveness of proposed method."],"dc:identifier.uri":["https://bradscholars.brad.ac.uk/handle/10454/20755"],"dc:language.iso":["en"],"dc:publisher.department":["School of Computer Science, AI, and Electronics. Faculty of Engineering and Digital Technologies"],"dc:publisher.institution":["University of Bradford"],"dc:rights":["\"Creative
The University of Bradford theses are licenced under a Creative Commons Licence."],"dc:subject":["Multi-Vector energy systems","Electricity distribution networks","Natural gas distribution networks","Energy market","Uncertainty modelling","Energy hub","Renewable energy sources","Planning and operation","Optimization","Demand response"],"dc:title":["Planning and Operation of Multi-Vector Energy System with High Penetration of Renewable Energy Sources"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["PhD"]},"updated_at":"2026-07-24T01:15:08Z"}