Publication

Planning and Operation of Distribution Networks with High Penetration of Renewable Energy Resources and Integration of Smart Grid Technologies

Al-Ja'afreh, Mohammad A.A.
Publication Date
End of Embargo
Supervisor
Mokryani, Geev
Keywords
Distribution networks, Operation, Planning, Reliability, Network reconfiguration, Voltage unbalanced, Conservation voltage regulation (CVR), Photovoltaic systems (PVs), Multiple PV penetration, Enhanced CNN-LSTM, Load and PV-generation forecasting
Rights
Creative Commons License
The University of Bradford theses are licenced under a Creative Commons Licence.
Peer-Reviewed
Open Access status
Accepted for publication
Institution
University of Bradford
Department
School of Computer Science, AI and Electronics. Faculty of Engineering and Digital Technologies
Awarded
2023
Embargo end date
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Theses
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18020281 Mohammad Al-Ja'afreh- Thesis for Library.pdf
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Abstract
This thesis proposes novel techniques for planning and operating distribution networks (DNs) with high penetration of renewable energy resources (RERs), considering active network management (ANM). A long-term planning framework is developed, featuring deep learning forecasting models to predicted load and generation profiles, thereby facilitating efficient DNs planning with ANM. Additionally, an optimal planning and operation framework is introduced, integrating network reconfiguration and flexibility services to enhance system reliability. To address voltage imbalance in low voltage DNs with widespread photovoltaic systems (PVs), a time-series three-phase optimal power flow method is developed, considering active and reactive PV power control. Furthermore, a multi-stage short-term forecasting (STF) framework is developed to handle the intermittent behaviour of RERs and variations in load demand. The proposed STF framework is applied to various distribution system operators (DSOs) scenarios. Lastly, a novel conservation voltage regulation (CVR)-based optimization model is introduced, incorporating centralized and decentralized voltage control schemes, and addressing the impact of multi-penetration levels of widespread PVs. The proposed methods are validated through case studies, demonstrating their effectiveness. Results show an additional 8.6% PVs capacity and an additional 10.5% wind generation with ANM, reducing total operating costs by 12%. Optimized distribution reliability cost savings range from 36% to 71%. Voltage imbalance can be reduced by 69%, and STF achieves a 48% reduction in mean absolute percentage error. The CVR-based algorithm enhances LV network efficiency, showcasing an energy reduction of up to 12.5%. Overall, this thesis provides DSOs with a practical tool for effectively planning and operating their networks.
URI
https://bradscholars.brad.ac.uk/handle/10454/20326
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Type
Thesis
Qualification name
PhD
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