Close menu

SURE

Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study

Kahwash, Fadi, Barakat, Basel, Taha, Ahmad, Abbasi, Qammer H. and Imran, Muhammad Ali (2021) Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study. Energies, 14 (21). p. 7084. ISSN 1996-1073

Item Type: Article

Abstract

This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simulations were carried out using the actual and forecasted parameters to improve decision making. The results show that incorporating forecasted parameters into the optimisation allows to identify the subset of optimal solutions that will become sub-optimal in the future and, therefore, should be avoided. Finally, a framework for choosing the most suitable subset of optimal solutions was presented.

[img]
Preview
PDF
14290.pdf - Published Version
Available under License Creative Commons Attribution.

Download (4MB) | Preview

More Information

Depositing User: Basel Barakat

Identifiers

Item ID: 14290
Identification Number: https://doi.org/10.3390/en14217084
ISSN: 1996-1073
URI: http://sure.sunderland.ac.uk/id/eprint/14290
Official URL: http://dx.doi.org/10.3390/en14217084

Users with ORCIDS

ORCID for Basel Barakat: ORCID iD orcid.org/0000-0001-9126-7613

Catalogue record

Date Deposited: 19 Jan 2022 13:33
Last Modified: 25 Jan 2022 08:45

Contributors

Author: Basel Barakat ORCID iD
Author: Fadi Kahwash
Author: Ahmad Taha
Author: Qammer H. Abbasi
Author: Muhammad Ali Imran

University Divisions

Faculty of Technology > School of Computer Science

Subjects

Computing
Engineering

Actions (login required)

View Item View Item