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

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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), 7084. ISSN 1996-1073 [Article]

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Official URL: https://www.mdpi.com/1996-1073/14/21/7084

Abstract or Description

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.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.3390/en14217084

Data Access Statement:

Restrictions apply to the availability of the electricity consumption data. The data belongs to Medway NHS Foundation Trust but was collected using systems provided by EnergyLogix. Data, however, can be made available with the approval of the corresponding author (Ahmad Taha), Medway NHS Foundation Trust, and energylogix. As for the carbon intensity data, it was obtained from [27] and the solar irradiance data was obtained from the online tool PVGIS [31].

Keywords:

grid-connected; hybrid renewable energy systems; multi-objective optimisation; machine learning; forecasting; NHS; CO2 emissions; net-zero systems; hospital

Departments, Centres and Research Units:

Computing

Dates: