4.7 Article

Model predictive control of a combined solar tower and parabolic trough aided coal-fired power plant

Journal

APPLIED THERMAL ENGINEERING
Volume 193, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2021.116998

Keywords

Solar tower; Parabolic trough; Coal-fired power generation; Model predictive control; Power load; Sensitivity studies

Funding

  1. China National Natural Science Foundation [51776063]
  2. National Basic Research Program of China [2015CB251505]
  3. Science Fund for Creative Research Groups of the National Natural Science Foundation of China [51821004]
  4. Fundamental Research Funds for the Central Universities [2019QN010]
  5. China Scholarship Council
  6. Cranfield University as host institute

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Integrating solar tower and parabolic trough technology into coal-fired power generation can significantly reduce coal consumption, especially in high radiation conditions. The method is insensitive to forecast errors but sensitive to system configurations.
Investigating the potential to add solar tower and parabolic trough technology to aid coal-fired power generation could be a valuable intermediate step along the route to decarbonisation while making use of an existing assets, that would have a high efficiency and percentage contribution to utilise solar energy to reduce coal consumption. Based on the plant model of a typical 600 MWe coal-fired plant with the addition of tower and trough solar heat sources developed in Ebsilon Professional platform, the model predictive controller is developed in this study, incorporating the information of predictive weather data and real power load, to minimise accumulative coal consumption in a specific time horizon. Simulations on a typical day and a 10-day consecutive period are performed to observe the benefits and operation processes with a model predictive controller. Compared with a standard controller that doesnt make use of future solar and load predictions, the typical day simulation shows, that the coal consumption reduction using a predictive control approach is increased by 21.3-tonne (13.6%), and 320.0-tonne (20.3%) in the 10 consecutive day simulation. The absolute difference of reduction tends to be most significant in high radiation conditions (day 2), which gave a 61.7-tonne (34.3%) saving. The improvement appears to be achieved by dispatching the thermal energy storage ability to store more energy and discharging thermal energy optimally. The benefits from this approach is insensitive to forecast error and shows sensitivity to system configurations, which tends to be greater with sufficient solar energy input but inadequate thermal storage capacity. While the general area of solar aided coal-fired plants have been investigated in various configurations by others, this paper is novel in that it examines the benefit of using future weather forecast data within a model predictive controller to significantly improve the potential solar contribution such a plant can use. As such it quantifies the potential improvements such an approach may achieve. In summary, the application in the solar tower and parabolic trough aided coal-fired power generation system improved the understanding of the benefits and the limitations in using the model predictive control in the operation process.

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