Negnevitsky, M and Wong, K, Demand response visualization tool for electric power systems, Visualization in Engineering, 3, (7) pp. 1-14. ISSN 2213-7459 (2015) [Refereed Article]
© 2015 Negnevitsky and Wong; licensee Springer. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)http://creativecommons.org/licenses/by/4.0/
Demand response (DR) is referred to programs designed to manage and control electric loads. DR represents one of the vital tools utilized in power distribution networks to improve network efficiency. Effective implementation of DR programs delivers operational benefits such as reduced peak demands and relieved overloads, which are essential in a power system with growing penetration of fundamentally intermittent renewable energy sources.
This paper presents a visualization tool for optimising DR programs for domestic hot water systems in distribution power networks. The tool accurately models and predicts potential peak demand reductions through direct load control of domestic hot water systems. It employs a multi-layer thermally stratified hot water cylinder model and Monte Carlo simulations to generate hot water load profiles of domestic customers. To meet peak reduction targets set by the tool user, switching programs found via iterative optimizations are applied to hot water systems.
The structure and individual components of the tool are described, and case studies are presented. Impacts of different switching programs on customerís comfort are evaluated and discussed.
The visualization tool is designed to recommend optimum DR switching programs for domestic water heating systems. The tool can assess the performance of a DR switching program by estimating potential peak load reductions and customer comfort characterized by the probability of cold showers. A power system operator can use this tool to determine the available domestic water heating load in a controlled area, and predict the potential reduction in peak load.
|Item Type:||Refereed Article|
|Keywords:||visualization tool, demand response, smart grid, electric power system|
|Research Group:||Electrical and Electronic Engineering|
|Research Field:||Power and Energy Systems Engineering (excl. Renewable Power)|
|Objective Group:||Energy Storage, Distribution and Supply|
|Objective Field:||Energy Services and Utilities|
|UTAS Author:||Negnevitsky, M (Professor Michael Negnevitsky)|
|UTAS Author:||Wong, K (Mr Koon Wong)|
|Downloads:||181 View Download Statistics|
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