Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Modelling of a population of heat pumps as a source of load in the Great Britain power system

Muhssin, Mazin T., Cipcigan, Liana Mirela, Jenkins, Nicholas, Meng, Cheng and Obaid, Zeyad A. 2016. Modelling of a population of heat pumps as a source of load in the Great Britain power system. Presented at: International Conference on Smart Systems and Technologies (SST), 12-14 October 2016. 2016 International Conference on Smart Systems and Technologies (SST). IEEE, pp. 109-113. 10.1109/SST.2016.7765642

Full text not available from this repository.

Abstract

The developments of large-scale renewable energy cause significant challenges for the operation of power system. Demand Side Response (DSR) based Thermostatically Controlled Loads (TCLs) may offer a broad range of potential benefits on system operation and reliability. This paper investigates the modelling of aggregated small loads, such as Heat Pump (HP). The simplified thermodynamic model of a residential single Air Source Heat Pump (ASHP) was developed and simulated using Matlab. A decentralized temperature control algorithm was used to control the ON/OFF cycle of the heat pump offering comfort to the customer. The behaviour of a population of controlled heat pumps was examined. Seven case studies were conducted to identify a suitable number of individual heat pump models that can be used to represent the total number of heat pumps in the UK according to the National Grid 2030 medium uptake scenario. Simulation results showed that an aggregation model of 5,000 individual heat pumps is suitable to represent the total number of heat pumps in the GB power system.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher: IEEE
ISBN: 978-1-5090-3720-9
Last Modified: 07 Aug 2019 14:55
URI: http://orca.cf.ac.uk/id/eprint/96978

Citation Data

Cited 7 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item