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Techno-economic feasibility assessment for a standalone hybrid energy system integrating renewable energy sources [dataset] Open Access

In this study, techno-economic and environmental analyses (TEEA) of various combinations of hybrid renewable energy systems (HRES) intended to provide electricity to an off-grid location, utilising 100% renewable energy sources have been investigated. The study investigates various scenarios combining wind turbines (WT), photovoltaic (PV) panels, biogas generators (BG), batteries (BAT), and converters (CONV), and assesses their technical and economic performances. Economic analysis reveals that system integrating PV/WT/BAT/CONV/BG, demonstrates the lowest LCOE (0.278 $/kWh) and NPC (1.61 M$) of all the investigated systems. On the other hand, the system comprising BAT/CONV/BG, has the highest LCOE (0.455 $/kWh) and NPC (2.63 M$) among all the configurations investigated. Machine learning techniques are employed to analyze techno-economic and environmental performance data. The Rational Quadratic Gaussian Process Regression model and the Wide Neural Network model achieved the highest accuracy in predicting the levelized cost of electricity (LCOE) and CO2 emissions, respectively. These results provide valuable assessment for the design and optimisation of a standalone HRES in remote areas.

Descriptions

Resource type

Dataset

Contributors

Creator: Vijayalakshmi, Shivaprasad ¹
Contact person: Vijayalakshmi, Shivaprasad ¹
Data collector: Roy, Dibyendu ¹
Data curator: Roy, Dibyendu ¹
Editor: Wang, Yaodong ¹
Editor: Roskilly, Anthony ¹

¹ Durham University, UK

Funder

Engineering and Physical Science Research Council

Research methods

Other description

Keyword

HRES
Bioenergy
Energy storage
Machine learning
Environmental analysis
Technoeconomic analysis

Subject

Renewable energy sources
Solar energy--Hybrid systems
Wind energy conversion systems

Location

UK

Language

English

Cited in

doi:10.1016/j.clet.2025.101045

Identifier

doi:10.15128/r1c821gj86z

Rights

Creative Commons Attribution 4.0 International (CC BY)

Publisher

Durham University

Date Created

18/7/2025

File Details

Depositor

S.K. Vijayalakshmi

Date Uploaded

18 July 2025, 10:07:55

Date Modified

18 July 2025, 12:07:59

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Characterization

File format: vnd.ms-excel (Microsoft Excel 2007+, OpenDocument Text)

Mime type: application/vnd.ms-excel

File size: 14782

Last modified: 2025:07:18 11:46:15+01:00

Filename: CLET TECHNO ECONOMIC.xlsx

Original checksum: d52fde94859db1adccfaa9278c1f4f59