Abstract
Conservation Voltage Reduction (CVR) has been found to be an effective methodology for dealing with thermal and voltage challenges caused by increasing penetration of low carbon technologies in power system distribution networks. Using validated openDSS simulation models of a number of distribution networks in the greater Manchester area in the UK, this paper evaluates the effectiveness of dynamically optimized CVR for energy reduction on distribution networks equipped with tap-changing transformers and switchable capacitor banks. Optimization of these controllable devices is carried out every 30 minutes using an oriented discrete coordinate descent (ODCD) algorithm, with a warm start strategy adopted to address local minima issues. Results show that the performance of warm start ODCD is comparable to Particle Swarm Optimisation, a benchmark global optimization technique, at a substantially reduced computation cost. The resulting dynamically optimized CVR yields an average reduction in energy consumption of 8% relative to nominal operating conditions for the low voltage distribution networks considered in the study.
Original language | English |
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Title of host publication | 2017 28th Irish Signals and Systems Conference, ISSC 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 6 |
ISBN (Electronic) | 9781538610466 |
ISBN (Print) | 978-1-5386-2221-6 |
DOIs | |
Publication status | Published - 20 Jul 2017 |
Event | 28th Irish Signals and Systems Conference, ISSC 2017 - Killarney, Ireland Duration: 20 Jun 2017 → 21 Jun 2017 |
Conference
Conference | 28th Irish Signals and Systems Conference, ISSC 2017 |
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Country/Territory | Ireland |
City | Killarney |
Period | 20/06/2017 → 21/06/2017 |
Keywords
- CVR implementation
- energy consumption optimisation
- warm start ODCD
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing
Fingerprint
Dive into the research topics of 'Warm start oriented discrete coordinate descent for dynamic CVR: A UK case study'. Together they form a unique fingerprint.Student theses
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Dynamic voltage optimisation of MV/LV networks
Gharavi Ahangar, H. (Author), Liu, X. (Supervisor) & McLoone, S. (Supervisor), Jul 2020Student thesis: Doctoral Thesis › Doctor of Philosophy
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