Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective
This paper discusses the importance of adopting a spatiotemporal model-based scenario generation technique by approximating a multivariate continuous stochastic process in a discrete form. The computational steps for such a model development are comprehensibly discussed via a case study using PV gen...
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Institute of Electrical and Electronics Engineers Inc.
2023
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oai:scholars.utp.edu.my:376122023-10-13T13:05:01Z http://scholars.utp.edu.my/id/eprint/37612/ Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective Rajanarayan Prusty, B. Bingi, K. Jena, D. Badi, M. Mohan Krishna, S. This paper discusses the importance of adopting a spatiotemporal model-based scenario generation technique by approximating a multivariate continuous stochastic process in a discrete form. The computational steps for such a model development are comprehensibly discussed via a case study using PV generation data collected from the USA. The model accuracy comparison through a detailed discussion of obtained results is likely to help novice researchers to choose the best model amongst the available options and tactically decide to improvise the modeling framework further. This systematically prepared paper is expected to help power engineers with enough confidence to execute operational planning decisions realistically. © 2023 IEEE. Institute of Electrical and Electronics Engineers Inc. 2023 Conference or Workshop Item NonPeerReviewed Rajanarayan Prusty, B. and Bingi, K. and Jena, D. and Badi, M. and Mohan Krishna, S. (2023) Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective. In: UNSPECIFIED. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168652120&doi=10.1109%2fICEPE57949.2023.10201560&partnerID=40&md5=eadb1013933d528ef8451cc83fc088fd 10.1109/ICEPE57949.2023.10201560 10.1109/ICEPE57949.2023.10201560 10.1109/ICEPE57949.2023.10201560 |
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This paper discusses the importance of adopting a spatiotemporal model-based scenario generation technique by approximating a multivariate continuous stochastic process in a discrete form. The computational steps for such a model development are comprehensibly discussed via a case study using PV generation data collected from the USA. The model accuracy comparison through a detailed discussion of obtained results is likely to help novice researchers to choose the best model amongst the available options and tactically decide to improvise the modeling framework further. This systematically prepared paper is expected to help power engineers with enough confidence to execute operational planning decisions realistically. © 2023 IEEE. |
format |
Conference or Workshop Item |
author |
Rajanarayan Prusty, B. Bingi, K. Jena, D. Badi, M. Mohan Krishna, S. |
spellingShingle |
Rajanarayan Prusty, B. Bingi, K. Jena, D. Badi, M. Mohan Krishna, S. Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective |
author_facet |
Rajanarayan Prusty, B. Bingi, K. Jena, D. Badi, M. Mohan Krishna, S. |
author_sort |
Rajanarayan Prusty, B. |
title |
Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective |
title_short |
Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective |
title_full |
Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective |
title_fullStr |
Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective |
title_full_unstemmed |
Uncertainty Management in Utility Grid Considering PV Generation: An Operational Planner's Perspective |
title_sort |
uncertainty management in utility grid considering pv generation: an operational planner's perspective |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2023 |
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http://scholars.utp.edu.my/id/eprint/37612/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168652120&doi=10.1109%2fICEPE57949.2023.10201560&partnerID=40&md5=eadb1013933d528ef8451cc83fc088fd |
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13.222552 |