@inbook{0f55a85e148b46c0ae56388fa666058c,
title = "Renewables-Based Multigeneration System for District Energy Supply",
abstract = "District energy systems (DES) provide electric and thermal energy from a central plant to a developed area through underground distribution networks. Fossil fuels are widely used as a primary energy source in DES. In 2021, energy-related CO2 emissions from residential and commercial buildings reached 10% worldwide. In this paper, a renewables-based multigeneration system is proposed as a sustainable alternative for DES. The conventional system is based on a gas-fired combined cycle turbine and an absorption cooling system (ACS). The proposed renewables-based system utilises biomass and solar thermal energies and an ACS to provide district electricity, heating and cooling. A stochastic optimisation approach based on multi-objective generics algorithm (MOGA) is used to support the process modelling and identify the optimal pre-defined configurations based on their proximity to the Pareto curve. A techno-economic assessment is performed to compare the levelised cost of energy (LCOE) and evaluate the anticipated environmental footprint reduction. Results show that although the LCOE of the proposed system is higher than the conventional system, the reduction in CO2 emissions converts directly into annual savings in districts covered by a carbon tax regime.",
keywords = "Carbon tax, Multigeneration, Optimisation, Renewable energy, Techno-economic assessment",
author = "Houd Al-Obaidli and Rajesh Govindan and Tareq Al-Ansari",
note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.",
year = "2022",
month = jan,
doi = "10.1016/B978-0-323-95879-0.50206-X",
language = "English",
series = "Computer Aided Chemical Engineering",
publisher = "Elsevier B.V.",
pages = "1231--1236",
booktitle = "Computer Aided Chemical Engineering",
address = "Netherlands",
}