Thesis

A multi-objective optimisation approach to the network arrangement of flexible heat demand

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Awarding institution
  • University of Strathclyde
Date of award
  • 2014
Thesis identifier
  • T13875
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Abstract
  • The electricity network in the UK is facing a challenging future where environmental and efficiency goals to be met require significant changes in the industry. The rethinking of how distribution networks are arranged and operated is essential due to increasing connections of generation at this level. This also gives significance to the issue of arranging and operating these assets in the most optimal manner. The saturated state of the transmission network has led to the popularity of connecting generation to distribution networks. It becomes evident that, when increasing generation from renewable sources, a means of storing energy is required. One area of storage being investigated for this aim is Electrical Thermal Storage (ETS), which is a form of flexible heating demand. This type of energy storage is cost effective, however it is limited in its application due to the natural dissipation of heat. It is preferable that this heat loss be of use and therefore ETS devices are used in the domestic setting. These devices can be in the form of space storage heaters or hot water storage tanks, which are able to store heat or hot water for up to several days, until the user wishes to make use of the resource. Although decentralised generation and energy storage (Distributed Energy Resources - DER) at first glance appear to be an attractive means for the energy and carbon targets to be met, it can introduce further problems to the electricity network. It is possible for the addition of DER to lead to voltage rise or voltage drop, negatively impact on the protection systems and affect power quality. In order for distribution networks to successfully operate it is important that any new network assets are connected in an optimal manner. This research has modified and used a multi-objective network planning framework to determine the optimal arrangement of ETS devices in distribution networks. The framework is built around the Strength Pareto Evolutionary Algorithm 2 (SPEA2), which takes its inspiration from evolution in nature, and is able to take into consideration the constraints of the network and multiple, conflicting objectives. The framework has been adapted to optimise the number of ETS devices, their location and operation, whilst ensuring that the network will operate within its constraints. The results generated by the planning framework illustrate the potential benefits offered by the inclusion of ETS in distribution networks, as well as demonstrate that the method and tools used are valuable and appropriate.
Resource Type
DOI
Date Created
  • 2014
Former identifier
  • 1041614

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