Planning and Operation of Multi-Vector Energy System with High Penetration of Renewable Energy Sources

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.

Grantor dc:publisher.institution

University of Bradford

Author dc:creator

• Onen, Patrick S.

Advisors dc:contributor.advisor

• Abd-Alhameed, Raed
• Li, Jian-Ping
• Mokryani, Geev

• 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

Statement dc:rights

• <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.

Language dc:language.iso

en

Repository record dc:identifier.uri

https://bradscholars.brad.ac.uk/handle/10454/20755

OAI identifier oai:identifier

oai:bradscholars.brad.ac.uk:10454/20755