Regulator design for the bilinear distributed-parameter model of a solar-power plant

This chapter provides a broad overview of solar thermal energy systems. The aim is to describe the context of distributed collector solar fields used in plants that apply parabolic trough technology. Furthermore, the temperature control problem associated to distributed collector solar fields is explained and the use of adaptive control to solve it is motivated. In contrast to subsequent chapters that use mathematics to explain control algorithms and the models upon which they rely, the approach in this chapter resorts to qualitative explanations together with some plant data to introduce the main ideas.

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“…Lyapunov methods, but using a quadratic function, are also the realm of Carotenuto et al (1985Carotenuto et al ( , 1986.…”

Section: Literature Overviewmentioning

confidence: 99%

Solar Energy Collector Systems

Lemos

Neves-Silva

Igreja

2014

Adaptive Control of Solar Energy Collector Systems

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“…Hence, (x) = 1 if the tube at position x is exposed to solar radiation, and (x) = 0 otherwise. The model (1) is a somewhat simpli ed model compared to the models described in (Klein et al 1974, Rorres et al 1980, Orbach et al 1981, Carotenuto et al 1985, Carotenuto et al 1986, Camacho et al 1997. In particular, heat losses and the conductivity of the tube are neglected.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Rorres et al (1980) and Orbach et al (1981) suggests an optimal control formulation based on a distributed nonlinear model where the objective i s t o maximize net produced power when the pumping power is taken into consideration. An alternative approach is taken by (Carotenuto et al 1985, Carotenuto et al 1986, where a quadratic control Lyapunov function is formulated for the distributed parameter model, and a stabilizing control law is derived. The approach presented in this paper is similar, but relies on using a storage function with a physical interpretation leading to a conceptually simpler control law with more transparent tuning parameters, see also (Ydstie and Alonso 1997) for a general treatment of thermodynamic storage functions in control.…”

Section: Introductionmentioning

confidence: 99%

“…The distributed solar collector eld may be described by a distributed parameter model of the temperature (Klein et al 1974, Rorres et al 1980, Orbach et al 1981, Carotenuto et al 1985, Carotenuto et al 1985, Camacho et al 1997. It is widely recognized that the performance og PI and PID type controllers will be inferior to model based approaches (Camacho et al 1992, Meaburn and Hughes 1995, Camacho et al 1997.…”

Section: Introductionmentioning

confidence: 99%

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Energy-based control of a distributed solar collector field

Johansen

Storaa

2002

Automatica

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Model-based control of the outlet temperature of a distributed solar collector eld is studied. An energy-based cont r o l l e r i s d e r i v ed using internal energy as a storage function and controlled variable. The controller relies on a distributed parameter nonlinear plant model and includes feedforward from the solar irradiation and inlet temperature. Stability of the closed loop is proved, and the method is experimentally veri ed to perform well on a pilot-scale solar power plant.

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“…without any a priori knowledge about the plant, in this work, the goal was to increase performance by the development of an adaptive predictive controller embedding in its design the relevant physical characteristics of the plant. The ACUREX field used in these experiments is described in available literature (Camacho et al, 1992;Camacho et al, 1988) and has motivated a wide range of research work on more sophisticated controllers of which (Barão et al, 2002;Berenguel and Camacho, 1995;Camacho, Berenguel and Rubio, 1997;Camacho et al, 1992;Coito et al, 1997;Carotenuto et al, 1985;Carotenuto et al, 1986;Johansen et al, 2000;Johansen et al, 2002;Lemos, Rato and Mosca, 2000;Meaburn and Hughes, 1994;Orbach et al, 1981;Rorres et al, 1980;Rubio et al, 1995;Rubio et al, 1996;Silva et al, 1997) are significant examples.…”

Section: Introductionmentioning

confidence: 99%

Time scaling internal state predictive control of a solar plant

Silva¹,

Rato

Lemos

2003

Control Engineering Practice

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The control of a distributed collector solar field is addressed in this work, exploiting the plant's transport characteristic. The plant is modeled by a hyperbolic type partial differential equation (PDE) where the transport speed is the manipulated flow, i.e. the controller output. The model has an external distributed source, which is the solar radiation captured along the collector, approximated to depend only of time. From the solution of the PDE, a linear discrete state space model is obtained by using time-scaling and the redefinition of the control input. This method allows overcoming the dependency of the time constants with the operating point. A model-based predictive adaptive controller is derived with the internal temperature distribution estimated with a state observer. Experimental results at the solar power plant are presented, illustrating the advantages of the approach under consideration.

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Regulator design for the bilinear distributed-parameter model of a solar-power plant

Cited by 18 publications

References 6 publications

Solar Energy Collector Systems

Solar Energy Collector Systems

Energy-based control of a distributed solar collector field

Time scaling internal state predictive control of a solar plant

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