Modelling and simulation of parabolic trough plants based on real operating data

Rohani, Shahab; Fluri, Thomas; Dinter, Frank; Nitz, Peter

doi:10.1016/j.solener.2017.10.023

Cited by 38 publications

(13 citation statements)

References 4 publications

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“…Rohani et al proposed a storage system operation strategy based on weather forecast; this strategy keeps the CSP plant continuously in operation with lower generation at night. [ 83 ] The minimum level of the tank is determined by the DNI forecast, and the hot tank does not discharge any more, once it reaches the minimum level that is kept for potential use. A comparison of the tank level with and without forecast in Figure 18 shows that the tank without forecast always discharges to the minimum‐permitted level.…”

Section: Optimization Of Csp Plantmentioning

confidence: 99%

“…Reproduced with permission. [83] Copyright 2020, Elsevier. As shown in Figure 21, except for the demonstration plant, the turbine efficiency increases with operation temperature and ranges from 30.6% to 38.7% when the solar field outlet temperature changes from 349 to 395 C. In addition, if the CSP plant applies molten salt as HTF and the operation temperature is 550 C, the turbine efficiency can be up to 39.3%.…”

Section: Performance Of Real Operational Csp Plantmentioning

confidence: 99%

“…Reduced derivation between real and planed generation 2. Significantly improved operation performance Camacho et al [113] Three-layer hierarchical control Rohani et al [83] Storage system operation strategy Martín et al [114] Power block operation parameters; Maximized the power generation 1. Maximum of 25 MW in July typical month meteorological data 2.…”

Section: Operation Strategy Optimization Considerations Realization Amentioning

confidence: 99%

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Review on Performance Analysis of the Power Block in Concentrated Solar Power Plants

et al. 2020

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Section: Optimization Of Csp Plantmentioning

confidence: 99%

Section: Performance Of Real Operational Csp Plantmentioning

confidence: 99%

Section: Operation Strategy Optimization Considerations Realization Amentioning

confidence: 99%

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Review on Performance Analysis of the Power Block in Concentrated Solar Power Plants

et al. 2020

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“…For the simulation model of this paper the collector EuroTrough ET150 (Rohani et al, 2017;Andasol 1, 2018; System Advisor Model (SAM). NREL, 2018) is selected.…”

Section: Collectors Receiver Tube and Heat Transfer Fluidmentioning

confidence: 99%

Event-based MPC for defocusing and power production of a parabolic trough plant under power limitation

et al. 2018

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Optimal operation of a solar plant is generally understood as a tracking of the optimal working temperatures which maximize the net electric power. However, a commercial solar plant may receive a limitation from the Transmission System Operator due to saturation of the electrical grid. In these situations the plant moves to an operation mode in which the objective is not maximum production but compliance with the orders of the Transmission System Operator.The paper proposes an Event-Based Gain Scheduling Generalized Predictive Control strategy for electric power production reference tracking when power limitations are imposed by the Transmission System Operator. Gain Scheduling Generalized Predictive Controllers are proposed to control fourth and third collector defocus in order to prevent heating fluid temperature from exceeding the limits of the manufacturer and therefore, avoid oil degradation. A 50 M W parabolic solar trough plant model has been used to design and validate the strategy. Simulation results are presented showing the advantages of using the proposed strategy.

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“…There exist also more complex models using software simulation such as Matlab, where every component of the solar plant is modeled in detail to obtain a very realistic response [16,17]. This last approach is very useful to perform economic analysis [18][19][20] and operators training, but it is not adequate for control and simulation purposes because it is computationally demanding. In general, in the works published providing a comparison between the model response and the real data taken from the plant is not common.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling of the Mojave Solar Plants

Gallego

Macı́as²,

Castilla³

et al. 2019

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Competitiveness of solar energy is one of current main research topics. Overall efficiency of solar plants can be improved by using advanced control strategies. To design and tuning properly advanced control strategies, a mathematical model of the plant is needed. The model has to fulfill two important points: (1) It has to reproduce accurately the dynamics of the real system; and (2) since the model is used to test advanced control strategies, its computational burden has to be as low as possible. This trade-off is essential to optimize the tuning process of the controller and minimize the commissioning time. In this paper, the modeling of the large-scale commercial solar trough plants Mojave Beta and Mojave Alpha is presented. These two models were used to test advanced control strategies to operate the plants.

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Modelling and simulation of parabolic trough plants based on real operating data

Cited by 38 publications

References 4 publications

Review on Performance Analysis of the Power Block in Concentrated Solar Power Plants

Review on Performance Analysis of the Power Block in Concentrated Solar Power Plants

Event-based MPC for defocusing and power production of a parabolic trough plant under power limitation

Mathematical Modeling of the Mojave Solar Plants

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