Achieve the optimal capacities of renewable energy generating and storage equipment by loading factor indexes of commercial key-customers

Abstract According to the typical load characteristics of commercial key-customer, the loading factor index ( LFindex ) for 24 hours of the day in working day can be obtained. The solar power generation and the commercial key-customer load are estimated on the basis of the local sunshine which the optimal capacity of solar energy and power storage equipment is deduced under various load indicators in accordance with the supply-demand theory. The loading factor index is based on the average load to get the different loading factor indexes under different loads per hour. If the load index is greater than 1 that apply the distributed power generation is more applicable for solar power generation of renewable energy which can restrain the peak power consumption of commercial key-customers. Based on the selected key-customer when the loading factor index is equal to 1, the optimal solar energy setting capacity is 1.0268 PU, the optimal power storage device capacity is 0.3447 PU; the loading factor index is equal to 1.2 which get the optimal solar setting capacity is 0.618 PU and the optimal storage device capacity is 0.0261 PU; the loading factor index is equal to 1.5, both the optimal solar setting capacity is 0.0243 PU and storage device capacity is 0.0005 PU. The conclusion is that the loading factor index increases uniformly which the optimal solar installation capacity also decreases smoothly and the optimal energy storage equipment capacity decreases sharply.

Authors

Institutions

Publication Details

Journal
Journal of Physics Conference Series
Published
2024-10-01
DOI
https://doi.org/10.1088/1742-6596/2878/1/012002
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Achieve the optimal capacities of renewable energy generating and storage equipment by loading factor indexes of commercial key-customers

H S Huang, Y M Tseng, Jinhua Zheng, Guanghui Li et al.
Journal of Physics Conference Series
Integrated Energy Systems Optimization
article

Achieve the optimal capacities of renewable energy generating and storage equipment by loading factor indexes of commercial key-customers

H S Huang, Y M Tseng, Jinhua Zheng, Guanghui Li, Z J Mao
article en

Abstract

Abstract According to the typical load characteristics of commercial key-customer, the loading factor index ( LFindex ) for 24 hours of the day in working day can be obtained. The solar power generation and the commercial key-customer load are estimated on the basis of the local sunshine which the optimal capacity of solar energy and power storage equipment is deduced under various load indicators in accordance with the supply-demand theory. The loading factor index is based on the average load to get the different loading factor indexes under different loads per hour. If the load index is greater than 1 that apply the distributed power generation is more applicable for solar power generation of renewable energy which can restrain the peak power consumption of commercial key-customers. Based on the selected key-customer when the loading factor index is equal to 1, the optimal solar energy setting capacity is 1.0268 PU, the optimal power storage device capacity is 0.3447 PU; the loading factor index is equal to 1.2 which get the optimal solar setting capacity is 0.618 PU and the optimal storage device capacity is 0.0261 PU; the loading factor index is equal to 1.5, both the optimal solar setting capacity is 0.0243 PU and storage device capacity is 0.0005 PU. The conclusion is that the loading factor index increases uniformly which the optimal solar installation capacity also decreases smoothly and the optimal energy storage equipment capacity decreases sharply.

Journal of Physics Conference SeriesVol. 2878(1)
Putian University (CN)
Affordable and clean energy
Openalex Percentile: Top 82%
Integrated Energy Systems Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Achieve the optimal capacities of renewable energy generating and storage equipment by loading factor indexes of commercial key-customers — H S Huang, Y M Tseng, et al. · Journal of Physics Conference Series (2024) | TGRS Research Map | TGRS