Renewable Electricity Pricing Mechanism Formation Mechanism Model Prediction
This paper mainly peak and valley electric charges price periods division and peak and valley electric charges determine optimized research established model peak and valley electric charges valley periods division and user response. First apply fuzzy math trapezoid membership function method to det...
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AIDIC Servizi S.r.l.
2016-08-01
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Series: | Chemical Engineering Transactions |
Online Access: | https://www.cetjournal.it/index.php/cet/article/view/4072 |
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doaj-28aad9be009e4f65a489f73ffb3c5f472021-02-19T21:00:45ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162016-08-015110.3303/CET1651208Renewable Electricity Pricing Mechanism Formation Mechanism Model PredictionQ. CaiL. LeThis paper mainly peak and valley electric charges price periods division and peak and valley electric charges determine optimized research established model peak and valley electric charges valley periods division and user response. First apply fuzzy math trapezoid membership function method to determine the load curve points at the possibility of peak, flat, valley period, providing a theoretical basis for the scientific division valley period. On this basis, load shifting, so that daily load curve of the system becomes more smooth for the purpose of considering the establishment of a user response peak and valley electric charges model and constraint condition set in a peak period pricing constraint that electricity peak period should not be higher than the cost of a small turbine to generate electricity, thereby reducing the small power generating units in the peak period of peak power generation, promote energy conservation.https://www.cetjournal.it/index.php/cet/article/view/4072 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Q. Cai L. Le |
spellingShingle |
Q. Cai L. Le Renewable Electricity Pricing Mechanism Formation Mechanism Model Prediction Chemical Engineering Transactions |
author_facet |
Q. Cai L. Le |
author_sort |
Q. Cai |
title |
Renewable Electricity Pricing Mechanism Formation Mechanism Model Prediction |
title_short |
Renewable Electricity Pricing Mechanism Formation Mechanism Model Prediction |
title_full |
Renewable Electricity Pricing Mechanism Formation Mechanism Model Prediction |
title_fullStr |
Renewable Electricity Pricing Mechanism Formation Mechanism Model Prediction |
title_full_unstemmed |
Renewable Electricity Pricing Mechanism Formation Mechanism Model Prediction |
title_sort |
renewable electricity pricing mechanism formation mechanism model prediction |
publisher |
AIDIC Servizi S.r.l. |
series |
Chemical Engineering Transactions |
issn |
2283-9216 |
publishDate |
2016-08-01 |
description |
This paper mainly peak and valley electric charges price periods division and peak and valley electric charges determine optimized research established model peak and valley electric charges valley periods division and user response. First apply fuzzy math trapezoid membership function method to determine the load curve points at the possibility of peak, flat, valley period, providing a theoretical basis for the scientific division valley period. On this basis, load shifting, so that daily load curve of the system becomes more smooth for the purpose of considering the establishment of a user response peak and valley electric charges model and constraint condition set in a peak period pricing constraint that electricity peak period should not be higher than the cost of a small turbine to generate electricity, thereby reducing the small power generating units in the peak period of peak power generation, promote energy conservation. |
url |
https://www.cetjournal.it/index.php/cet/article/view/4072 |
work_keys_str_mv |
AT qcai renewableelectricitypricingmechanismformationmechanismmodelprediction AT lle renewableelectricitypricingmechanismformationmechanismmodelprediction |
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1724260524506480640 |