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Environmental Sciences Proceedings
Volume 26
Issue 1
10.3390/environsciproc2023026176
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Proceeding Paper

Stochastic Assessment of Day-Ahead, Wind Energy Curtailment-Driven Demand Response Requirements in Non-Interconnected Island Systems †

by
Dimitrios Zafirakis
1,*,
Konstantinos Christopoulos
1,
Konstantinos Moustris
2 and
John K. Kaldellis
1
1
Soft Energy Applications & Environmental Protection Laboratory, Mechanical Engineering Department, School of Engineering, University of West Attica, 250 Thivon & Petrou Ralli, 12244 Athens, Greece
2
Air Pollution Laboratory, Department of Mechanical Engineering, University of West Attica, 250 Thivon & P. Ralli Street, 12244 Athens, Greece
*
Author to whom correspondence should be addressed.
†
Presented at the 16th International Conference on Meteorology, Climatology and Atmospheric Physics—COMECAP 2023, Athens, Greece, 25–29 September 2023.
Environ. Sci. Proc. 2023, 26(1), 176; https://doi.org/10.3390/environsciproc2023026176
Published: 6 September 2023
(This article belongs to the Proceedings of 16th International Conference on Meteorology, Climatology and Atmospheric Physics—COMECAP 2023)
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Abstract

Occurrence of wind energy curtailments in non-interconnected island systems of considerable wind power capacity comes as a result of local grid limitations and significant load variation across seasons. Facilitating increased wind energy generation requires flexibility means such as energy storage and/or demand response (DR), with the latter presenting the advantage of suggesting a non-capital-intensive solution. To that end, in the present study we examine the problem of assessing day-ahead demand response requirements for the recovery of wind energy curtailments and put forward a stochastic approach, supported by the employment of artificial neural networks’ forecasting models and the integration of prediction uncertainties. For the application of our methodology, we use data from the non-interconnected island system of Kos and Kalymnos in the SE Aegean Sea and investigate the dynamics of the proposed DR scheme on the island of Tilos, belonging to the electricity complex of Kos and Kalymnos. At the same time, we perform a parametrical analysis so as to study the impact of appreciating different levels of available DR capacity, with our findings comparing favorably against the results of applying a deterministic approach.
Keywords: artificial neural networks; day-ahead forecasting; wind energy curtailments; demand response; stochastic analysis artificial neural networks; day-ahead forecasting; wind energy curtailments; demand response; stochastic analysis

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MDPI and ACS Style

Zafirakis, D.; Christopoulos, K.; Moustris, K.; Kaldellis, J.K. Stochastic Assessment of Day-Ahead, Wind Energy Curtailment-Driven Demand Response Requirements in Non-Interconnected Island Systems. Environ. Sci. Proc. 2023, 26, 176. https://doi.org/10.3390/environsciproc2023026176

AMA Style

Zafirakis D, Christopoulos K, Moustris K, Kaldellis JK. Stochastic Assessment of Day-Ahead, Wind Energy Curtailment-Driven Demand Response Requirements in Non-Interconnected Island Systems. Environmental Sciences Proceedings. 2023; 26(1):176. https://doi.org/10.3390/environsciproc2023026176

Chicago/Turabian Style

Zafirakis, Dimitrios, Konstantinos Christopoulos, Konstantinos Moustris, and John K. Kaldellis. 2023. "Stochastic Assessment of Day-Ahead, Wind Energy Curtailment-Driven Demand Response Requirements in Non-Interconnected Island Systems" Environmental Sciences Proceedings 26, no. 1: 176. https://doi.org/10.3390/environsciproc2023026176

APA Style

Zafirakis, D., Christopoulos, K., Moustris, K., & Kaldellis, J. K. (2023). Stochastic Assessment of Day-Ahead, Wind Energy Curtailment-Driven Demand Response Requirements in Non-Interconnected Island Systems. Environmental Sciences Proceedings, 26(1), 176. https://doi.org/10.3390/environsciproc2023026176

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