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Optimized Demand-Side Day-Ahead Generation Scheduling Model for a Wind–Photovoltaic–Energy Storage Hydrogen Production System
[Image: see text] This paper proposed an optimized day-ahead generation model involving hydrogen-load demand-side response, with an aim to make the operation of an integrated wind–photovoltaic–energy storage hydrogen production system more cost-efficient. Considering the time-of-use electricity pric...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744089/ https://www.ncbi.nlm.nih.gov/pubmed/36519112 http://dx.doi.org/10.1021/acsomega.2c05319 |
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author | Chen, Kang Peng, Huaiwu Zhang, Junfeng Chen, Pengfei Ruan, Jingxin Li, Biao Wang, Yueshe |
author_facet | Chen, Kang Peng, Huaiwu Zhang, Junfeng Chen, Pengfei Ruan, Jingxin Li, Biao Wang, Yueshe |
author_sort | Chen, Kang |
collection | PubMed |
description | [Image: see text] This paper proposed an optimized day-ahead generation model involving hydrogen-load demand-side response, with an aim to make the operation of an integrated wind–photovoltaic–energy storage hydrogen production system more cost-efficient. Considering the time-of-use electricity pricing plan, demand for hydrogen load, and the intermittency of renewable energy, the model has the ambition to achieve minimum daily cost of operating a hydrogen production system. The model is power-balanced, fit for energy storage devices, and developed through adaptive simulated annealing particle swarm optimization. Analysis results showed that the proposed optimized scheduling model helped avoid the significant purchase of electric power at peak times and reduced the cost of running the hydrogen production system, ensuring that the daily hydrogen energy produced could meet the daily demand for the gas load. This justified how the model and its algorithm were correctly and efficiently applied. |
format | Online Article Text |
id | pubmed-9744089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-97440892022-12-13 Optimized Demand-Side Day-Ahead Generation Scheduling Model for a Wind–Photovoltaic–Energy Storage Hydrogen Production System Chen, Kang Peng, Huaiwu Zhang, Junfeng Chen, Pengfei Ruan, Jingxin Li, Biao Wang, Yueshe ACS Omega [Image: see text] This paper proposed an optimized day-ahead generation model involving hydrogen-load demand-side response, with an aim to make the operation of an integrated wind–photovoltaic–energy storage hydrogen production system more cost-efficient. Considering the time-of-use electricity pricing plan, demand for hydrogen load, and the intermittency of renewable energy, the model has the ambition to achieve minimum daily cost of operating a hydrogen production system. The model is power-balanced, fit for energy storage devices, and developed through adaptive simulated annealing particle swarm optimization. Analysis results showed that the proposed optimized scheduling model helped avoid the significant purchase of electric power at peak times and reduced the cost of running the hydrogen production system, ensuring that the daily hydrogen energy produced could meet the daily demand for the gas load. This justified how the model and its algorithm were correctly and efficiently applied. American Chemical Society 2022-11-16 /pmc/articles/PMC9744089/ /pubmed/36519112 http://dx.doi.org/10.1021/acsomega.2c05319 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Chen, Kang Peng, Huaiwu Zhang, Junfeng Chen, Pengfei Ruan, Jingxin Li, Biao Wang, Yueshe Optimized Demand-Side Day-Ahead Generation Scheduling Model for a Wind–Photovoltaic–Energy Storage Hydrogen Production System |
title | Optimized Demand-Side Day-Ahead Generation Scheduling
Model for a Wind–Photovoltaic–Energy Storage Hydrogen
Production System |
title_full | Optimized Demand-Side Day-Ahead Generation Scheduling
Model for a Wind–Photovoltaic–Energy Storage Hydrogen
Production System |
title_fullStr | Optimized Demand-Side Day-Ahead Generation Scheduling
Model for a Wind–Photovoltaic–Energy Storage Hydrogen
Production System |
title_full_unstemmed | Optimized Demand-Side Day-Ahead Generation Scheduling
Model for a Wind–Photovoltaic–Energy Storage Hydrogen
Production System |
title_short | Optimized Demand-Side Day-Ahead Generation Scheduling
Model for a Wind–Photovoltaic–Energy Storage Hydrogen
Production System |
title_sort | optimized demand-side day-ahead generation scheduling
model for a wind–photovoltaic–energy storage hydrogen
production system |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744089/ https://www.ncbi.nlm.nih.gov/pubmed/36519112 http://dx.doi.org/10.1021/acsomega.2c05319 |
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