Establishment of a Model for a Combined Heat and Power Plant with ThermosysPro Library

Deneux, Olivier; Hafni, B. El; Péchiné, B.; Penta, E. Di; Antonucci, G.; Nuccio, Patrizio

doi:10.1016/j.procs.2013.06.098

Cited by 6 publications

(8 citation statements)

References 12 publications

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“…With Equations (11) to (17), the full behavior of the large turbine can be explained, and only the pressure at the output of the saturator (P SSaOut ) is needed to obtain the mass flow of steam at the input of the turbines (W STuIn ). If these equations are analyzed carefully, it can be seen how a new nonlinear algebraic loop appears affecting all of them.…”

Section: Expansion Zonementioning

confidence: 99%

“…On the other hand, many tools, designed for modeling and simulating different energy simulation systems are available in the market; in [16], an extensive review of the available tools can be found. Some of the developed models found in the literature are built based on model libraries offered by third parties, such is the case for Modelica [17], EcosimPro [18] or Aspenplus [19]. In addition, detailed models for the individual components constituting CHP plants such as boilers [20][21][22] or steam turbines [23] can be found.…”

Section: Introductionmentioning

confidence: 99%

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Modeling On-Site Combined Heat and Power Systems Coupled to Main Process Operation

2019

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Many production processes work with on-site Combined Heat and Power (CHP) systems to reduce their operational cost and improve their incomes by selling electricity to the external grid. Optimal management of these plants is key in order to take full advantage of the possibilities offered by the different electricity purchase or selling options. Traditionally, this problem is not considered for small cogeneration systems whose electricity generation cannot be decided independently from the main process production rate. In this work, a non-linear gray-box model is proposed in order to deal with this dynamic optimization problem in a simulated sugar factory. The validation shows that with only 52 equations, the whole system behavior is represented correctly and, due to its structure and small size, it can be adapted to any other production process working along a CHP with the same plant configuration.

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Section: Expansion Zonementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling On-Site Combined Heat and Power Systems Coupled to Main Process Operation

2019

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“…Cogeneration (COGEN) system mainly comprise of a boiler and a turbine where dual industrial process requirement of power and heating can be satisfied using a single fuel (Deneux et al, 2013;El-Halwagi, 2006Kamrava et al, 2015). Boiler produces steam that is used to operate a turbine to produce shaft work for power generation.…”

Section: Cogenmentioning

confidence: 99%

Multi-objective optimization methodology to size cogeneration systems for managing flares from uncertain sources during abnormal process operations

Kazi

Mohammed

AlNouss

et al. 2015

Computers & Chemical Engineering

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“…Fuel, water and air flowrates to the engine and boilers are internally regulated in order to produce 90 o C hot water. A model of the power plant was developped with Modelica and the library ThermoSysPro (Deneux et al, 2013). The nonlinear Modelica model of the plant which is used in the MPC has 31 states and 726 algebraic variables (after Dymola symbolic processing).…”

Section: Combined Heat and Power Plantmentioning

confidence: 99%

Tracking of optimal trajectories for power plants based on physical models

et al. 2015

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International audienceThe paper deals with tracking of optimal trajectories for large scale non linear systems like power plants. It is assumed that an accurate nonlinear model of the plant is available, but because of its size and complexity, it cannot be used directly for long term dynamic optimization. For this reason, reference input and output trajectories are obtained from a simplified optimization model. Then a tracking Model Predictive Control (MPC) algorithm based on tangent linear approximations of the nonlinear model along a nominal trajectory is used to correct the trajectories. It includes input and output constraints, state estimation and disturbances rejection. The concept is shown on the tracking of optimal trajectories by a Combined Heat and Power (CHP) plant with heat storage and time varying electricity price

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Establishment of a Model for a Combined Heat and Power Plant with ThermosysPro Library

Cited by 6 publications

References 12 publications

Modeling On-Site Combined Heat and Power Systems Coupled to Main Process Operation

Modeling On-Site Combined Heat and Power Systems Coupled to Main Process Operation

Multi-objective optimization methodology to size cogeneration systems for managing flares from uncertain sources during abnormal process operations

Tracking of optimal trajectories for power plants based on physical models

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