Probabilistic Method for Estimation of Spinning Reserves in Multi-connected Power Systems with Bayesian Network-based Rescheduling Algorithm

Yerzhigit Bapin, Vasileios Zarikas

2019

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.

Paper Citation

in Harvard Style

Bapin Y. and Zarikas V. (2019). Probabilistic Method for Estimation of Spinning Reserves in Multi-connected Power Systems with Bayesian Network-based Rescheduling Algorithm.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 840-849. DOI: 10.5220/0007577308400849

in Bibtex Style

@conference{icaart19,
author={Yerzhigit Bapin and Vasileios Zarikas},
title={Probabilistic Method for Estimation of Spinning Reserves in Multi-connected Power Systems with Bayesian Network-based Rescheduling Algorithm},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={840-849},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007577308400849},
isbn={978-989-758-350-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Probabilistic Method for Estimation of Spinning Reserves in Multi-connected Power Systems with Bayesian Network-based Rescheduling Algorithm
SN - 978-989-758-350-6
AU - Bapin Y.
AU - Zarikas V.
PY - 2019
SP - 840
EP - 849
DO - 10.5220/0007577308400849