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Probabilistic method for estimation of spinning reserves in multi-connected power systems with Bayesian network-based rescheduling algorithm

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Autore
Bapin Y., Zarikas V.
Data
2019
Language
en
DOI
10.5220/0007577308400849
Soggetto
Artificial intelligence
Electric power system interconnection
Random errors
Stochastic models
Stochastic systems
Estimation models
General structures
Power system reliability
Probabilistic methods
Probabilistic reserves
Renewable energies
Reserve requirements
Spinning reserves
Bayesian networks
SciTePress
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Abstract
This study proposes a new stochastic spinning reserve estimation model applicable to multi-connected energy systems with reserve rescheduling algorithm based on Bayesian Networks. The general structure of the model is developed based on the probabilistic reserve estimation model that considers random generator outages as well as load and renewable energy forecast errors. The novelty of the present work concerns the additional Bayesian layer which is linked to the general model. It conducts reserve rescheduling based on the actual net demand realization and other reserve requirements. The results show that the proposed model improves estimation of reserve requirements by reducing the total cost of the system associated with reserve schedule. Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved
URI
http://hdl.handle.net/11615/71120
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