Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740413
Title: Distribution network automation for multi-objective optimisation
Author: Zhang, Boyi
ISNI:       0000 0004 7226 3280
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2018
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Abstract:
Asset management and automation are acknowledged by distribution utilities as a useful strategy to improve service quality and reliability. However, the major challenge faced by decision makers in distribution utilities is how to achieve long-term return on the projects while minimising investment and operation costs. Distribution automation (DA) in terms of transformer economic operation (TEO), distribution network reconfiguration (DNR), and sectionalising switch placement (SSP) is recognised as the most effective way for distribution network operators (DNOs) to increase operation efficiency and reliability. Automated tie-switches and sectionalising switches play a fundamental role in distribution networks. A method based on the Monte Carlo simulation is discussed for transformer loss reduction, which comprises of profile generators of residential demand and a distribution network model. The ant colony optimisation (ACO) algorithm is then developed for optimal DNR and TEO to minimise network loss. An ACO algorithm based on a fuzzy multi-objective approach is proposed to solve SSP problem, which considers reliability indices and switch costs. Finally, a multi-objective ant colony optimisation (MOACO) and an artificial immune systems-ant colony optimisation (AIS-ACO) algorithm are developed to solve the reconfiguration problem, which is formulated within a multi-objective framework using the concept of Pareto optimality. The performance of the optimisation techniques has been assessed and illustrated by various case studies on three distribution networks. The obtained optimum network configurations indicate the effectiveness of the proposed methods for optimal DA.
Supervisor: Li, Haiyu Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.740413  DOI: Not available
Keywords: network loss ; reliability ; transformer economic operation ; distributed generation ; distribution network reconfiguration ; ant colony optimisation ; distribution network ; sectionalising switch placement
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