Turbine investment optimisation for energy recovery plants by utilising historic steam flow profiles

Venter, Ponti; Terblanché, S.E.; Eldik, Martin van

doi:10.1016/j.energy.2018.04.186

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The Applicable Component and Process Limitations1

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Cited by 2 publications

(2 citation statements)

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“…Hence, the first two steps design a deterministic mixed-integer linear programming model. Many operations research problems involving the timing of production processes and related investment decisions are solved in that format, and thus employ already these two steps (Flisberg et al, 2014;Venter et al, 2018;Yan and Ji, 2017). This problem can be extended to a real option problem as discussed next.…”

Section: General Methodologymentioning

confidence: 99%

Stochastic-dynamic modelling of farm-level investments under uncertainty

Spiegel

Britz

Djanibekov

et al. 2020

Environmental Modelling & Software

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Section: General Methodologymentioning

confidence: 99%

Stochastic-dynamic modelling of farm-level investments under uncertainty

Spiegel

Britz

Djanibekov

et al. 2020

Environmental Modelling & Software

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“…A trip occurrence is harmful to PGEN components such as the turbine [27]. To avoid frequent trips, a time delay is typically introduced.…”

Section: The Applicable Component and Process Limitationsmentioning

confidence: 99%

Energy Recovery Maximisation Modelling Subject to Constrained Cooling

Bester,

Van Eldik,

Venter

2023

Energies

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The primary heat rejection cycle, which is critical for the stability and integrity of the metal production process and equipment, involves the transfer of heat from flue gas to a fluid circulated through a gas-cooler. The rate of heat transfer from the flue gas is influenced by several parameters, including the temperature of the cooling fluid. Heat transfer rates that are too high or too low can negatively impact equipment’s life, emphasising the need for a temperature operational envelope in the cooling fluid prior to entering the gas-cooler. Rejected heat is used for power generation, transferred to the environment, or both. This study examines the impact of control philosophies on both temperature and power generation, while maintaining the exit temperature within the desired range as the highest priority. A more advanced philosophy that combines bypass control with feedforward parameters can maintain temperatures within safe operating limits at all times, while improving the power generation, compared to a typical works approach which is used as a baseline. This study presents a formulation that increased power generation from an average of 6.11 MW for a typical works philosophy to 10.68 MW, while maintaining the temperature within the operating temperature envelope.

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Turbine investment optimisation for energy recovery plants by utilising historic steam flow profiles

Cited by 2 publications

References 18 publications

Stochastic-dynamic modelling of farm-level investments under uncertainty

Stochastic-dynamic modelling of farm-level investments under uncertainty

Energy Recovery Maximisation Modelling Subject to Constrained Cooling

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