Scheduling in Concentrating Solar Power Plants Based on Model Predictive Control and Binary-Regularization Methods

Cojocaru, Emilian Gelu; Vasallo, Manuel Jesús; Bravo, José Manuel; Marín, D.

doi:10.1109/ccta.2018.8511609

2018 IEEE Conference on Control Technology and Applications (CCTA) 2018

DOI: 10.1109/ccta.2018.8511609

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Scheduling in Concentrating Solar Power Plants Based on Model Predictive Control and Binary-Regularization Methods

Emilian Gelu Cojocaru

Manuel Jesús Vasallo

José Manuel Bravo

et al.

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2024

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Assessment of Storage Sizing for Solar Tower Plants Using Model-Predictive Control for Dispatch Planning

Mohammadzadeh,

Truong-Ba,

Picotti

et al. 2024

Journal of Solar Energy Engineering

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Solar Tower with Thermal Energy Storage (ST-TES) represents a promising technology for large-scale exploitation of solar irradiation for electricity generation. A ST-TES plant has the potential to extend electricity generation to more favorable conditions, such as high electricity prices. The size of TES, however, constrains the flexibility of dispatching choices, especially when there is significant uncertainty in forecasts of solar irradiation and electricity prices. This study explores the impact of TES size when a ST-TES plant uses Model-Predictive Control (MPC) for dispatch planning. The performance of MPC is benchmarked against perfect knowledge (PK) and two day-ahead strategies. The optimal achievable profit for each TES size is determined using the PK strategy. An analysis is conducted to evaluate the relative profit losses for all the other simulated strategies compared to the PK strategy. A case study is conducted for a hypothetical 115 MWe STTES plant in South Australia. For January and August, 100 tests are performed for each dispatch policy, with the TES size varying from 6 to 14 hours. The revenue evaluation is conducted with both fixed and wholesale spot prices. The analysis shows that MPC-aided dispatching enables the adoption of a smaller TES compared to day-ahead policies while maintaining the same expected profit. The resulting TES size reduction from 14 to 10 hours translates into approximately up to $45.4 million in capital cost savings. The findings of this study can inform the ST-TES plant's design procedures and facilitate negotiations for electricity sales contracts.

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Assessment of Storage Sizing for Solar Tower Plants Using Model-Predictive Control for Dispatch Planning

Mohammadzadeh,

Truong-Ba,

Picotti

et al. 2024

Journal of Solar Energy Engineering

View full text Add to dashboard Cite

show abstract

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Scheduling in Concentrating Solar Power Plants Based on Model Predictive Control and Binary-Regularization Methods

Cited by 1 publication

References 27 publications

Assessment of Storage Sizing for Solar Tower Plants Using Model-Predictive Control for Dispatch Planning

Assessment of Storage Sizing for Solar Tower Plants Using Model-Predictive Control for Dispatch Planning

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