Control Co-Design Under Uncertainty for Offshore Wind Farms: Optimizing Grid Integration, Energy Storage, and Market Participation
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913788817571840 |
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| author | Sharma, Himanshu Wang, Wei Huang, Bowen She, Buxin Ramachandaran, Thiagarajan |
| author_facet | Sharma, Himanshu Wang, Wei Huang, Bowen She, Buxin Ramachandaran, Thiagarajan |
| contents | Offshore wind farms (OWFs) are set to significantly contribute to global decarbonization efforts. Developers often use a sequential approach to optimize design variables and market participation for grid-integrated offshore wind farms. However, this method can lead to sub-optimal system performance, and uncertainties associated with renewable resources are often overlooked in decision-making. This paper proposes a control co-design approach, optimizing design and control decisions for integrating OWFs into the power grid while considering energy market and primary frequency market participation. Additionally, we introduce optimal sizing solutions for energy storage systems deployed onshore to enhance revenue for OWF developers over time. This framework addresses uncertainties related to wind resources and energy prices. We analyze five U.S. west-coast offshore wind farm locations and potential interconnection points, as identified by the Bureau of Ocean Energy Management (BOEM). Results show that optimized control co-design solutions can increase market revenue by 3.2\% and provide flexibility in managing wind resource uncertainties. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_08555 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Control Co-Design Under Uncertainty for Offshore Wind Farms: Optimizing Grid Integration, Energy Storage, and Market Participation Sharma, Himanshu Wang, Wei Huang, Bowen She, Buxin Ramachandaran, Thiagarajan Systems and Control Computational Engineering, Finance, and Science Data Analysis, Statistics and Probability Offshore wind farms (OWFs) are set to significantly contribute to global decarbonization efforts. Developers often use a sequential approach to optimize design variables and market participation for grid-integrated offshore wind farms. However, this method can lead to sub-optimal system performance, and uncertainties associated with renewable resources are often overlooked in decision-making. This paper proposes a control co-design approach, optimizing design and control decisions for integrating OWFs into the power grid while considering energy market and primary frequency market participation. Additionally, we introduce optimal sizing solutions for energy storage systems deployed onshore to enhance revenue for OWF developers over time. This framework addresses uncertainties related to wind resources and energy prices. We analyze five U.S. west-coast offshore wind farm locations and potential interconnection points, as identified by the Bureau of Ocean Energy Management (BOEM). Results show that optimized control co-design solutions can increase market revenue by 3.2\% and provide flexibility in managing wind resource uncertainties. |
| title | Control Co-Design Under Uncertainty for Offshore Wind Farms: Optimizing Grid Integration, Energy Storage, and Market Participation |
| topic | Systems and Control Computational Engineering, Finance, and Science Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2504.08555 |