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  5. Conceptual Hybrid Energy Model for Different Power Potential Scales: Technical and Economic Approaches

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Article
English
2024

Conceptual Hybrid Energy Model for Different Power Potential Scales: Technical and Economic Approaches

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English
2024
Renewable Energy
DOI: 10.1016/j.renene.2024.121486

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Oscar Coronado-hernández
Oscar Coronado-hernández

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Helena M. Ramos
J. Pína
Oscar Coronado-hernández
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Abstract

This research attempts to address the gap between the theoretical fundamentals of hybrid renewable energy systems and their practical implementation at different scales through a new Conceptual Hybrid Energy Model (COHYBEM). The main objective was to develop a multi-variable model to allow a new complete and comprehensive techno-economic analysis of the performance of possible hybrid renewable power systems at different scales. The purpose is to evaluate the influence of critical parameters by changing key parameters in the developed model and identifying their impacts. It covers big data analyses, simulation and optimization of hybrid energy solutions, combining wind, solar and hydropower energy sources with the energy storage technology of pump hydropower storage. The research also denoted the Pareto front with the increasing power installed, for the maximum efficiency and total satisfied demand by Wind + PVSolar and by Hydro converges to a higher percentage, while a minimum waste by Wind + PVSolar is also progressing towards the increasing scales. In terms of investment costs for the 243 analyzed case studies, it varies between 45 k€ to 2.1 M€, resulting in a net present value (NPV) between 18 and 600 k€ and a payback period around 6–17 years depending on the power scale analyzed.

How to cite this publication

Helena M. Ramos, J. Pína, Oscar Coronado-hernández, Modesto Pérez‐Sánchez, Aonghus McNabola (2024). Conceptual Hybrid Energy Model for Different Power Potential Scales: Technical and Economic Approaches. Renewable Energy, pp. 121486-121486, DOI: 10.1016/j.renene.2024.121486.

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Publication Details

Type

Article

Year

2024

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

Renewable Energy

DOI

10.1016/j.renene.2024.121486

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