Transfer functions of solar collectors for dynamical analysis and control design

Buzás, J.; Kicsiny, Richárd

doi:10.1016/j.renene.2014.01.037

Cited by 46 publications

(13 citation statements)

References 27 publications

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“…A solution to this problem involves their conversion to a transfer function form using the Laplace transform. An analysis of the transient states of the collector using the Laplace transform was used both for the HWB equation [21], its numerous modifications [31][32][33][34][35][36], as well as collector models based on innovative concepts, e.g., piston flow [37,38]. Models belonging to this group are usually used to simulate the operation of existing solar collectors.…”

Section: An Overview Of Test Methods For Flat-plate Solar Collectorsmentioning

confidence: 99%

Comparison of Solar Collector Testing Methods—Theory and Practice

2020

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One of the most important problems of operating solar heating systems involves variable efficiency depending on operating conditions. This problem is more pronounced in hybrid energy systems, where a solar installation cooperates with other segments based on conventional carriers of energy or renewable sources of energy. The operating cost of each segment of a hybrid system depends mainly on the resulting efficiency of solar installation. For over 40 years, the procedures of testing solar collectors have been undergoing development, testing, comparison and verification in order to create a procedure that would allow determining the thermal behavior of a solar collector without performing expensive and complicated experimental tests, usually based on the steady state condition. The proper determination of the static and dynamic properties of a solar collector is of key significance, as they constitute a basis for the design of a solar heating installation, as well as a control system. It is therefore important to conduct simulating and operating tests enabling the performance of a comparative analysis intended to indicate the degree to which the static and dynamic properties of a solar collector depend on the method used for their determination. The paper compares the static and dynamic properties of a flat solar collector determined by means of various methods. Based on the produced results, it has been concluded that the static and dynamic properties of a collector determined using various methods may differ from each other even by 50%. This means that it is possible to increase the efficiency of a solar heating installation via the use of an adaptive control algorithm, enabling real-time calculation of the values of characteristic parameters of solar installation, e.g., the time constant under operating conditions.

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Section: An Overview Of Test Methods For Flat-plate Solar Collectorsmentioning

confidence: 99%

Comparison of Solar Collector Testing Methods—Theory and Practice

2020

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“…The changing weather and alteration of day and night enforced us to incorporate heat storage technology into supply energy continuously. Buzas et al have proposed the modeling of the solar thermal plant. For modeling of STPP, first the need is to model solar field.…”

Section: System Consideredmentioning

confidence: 99%

“…

G (s) = \frac{K_{S}}{1 + T_{S}},

where K s is the gain of solar field, T i is the inlet temperature of the fluid, and T o is the outlet temperature of the fluid. Thus, the steam will be produced in heat exchangers and it drives the turbine

where T_{S} = \frac{1}{\frac{U_{L} A}{2 C} + \frac{v}{V}},

U L is the collector overall heat loss coefficient (W/[m 2 K]), A is the collector surface area (m 2 ), V is the heat transfer fluid volume in the collector (m 3 ), v is the collector (or pump) flow rate (m 3 /s), and C is the collector fluid heat capacity (J/K) …”

Section: System Consideredmentioning

confidence: 99%

Analysis of moth flame optimization optimized cascade proportional‐integral‐proportional‐derivative controller with filter for automatic generation control system incorporating solar thermal power plant

Acharyulu¹,

Mohanty

Hota

2020

Optim Control Appl Methods

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In the fast developing electric power system network, ancillary services like automatic generation control (AGC) plays a vital and significant role to ensure good quality of power supply in the system. To distribute good quality of power, a hybrid AGC system along with an efficient and intelligent controller is compelled. So, in this article, a cascaded proportional-integral (PI)-proportional-derivative (PD) controller with filter (PI-PDF) is proposed as secondary controller for AGC system. A nature inspired optimization algorithm named as moth flame optimization (MFO) algorithm is employed for simultaneous optimization of controller gains. Initially, a two-area interconnected nonreheat thermal power system is investigated. Analysis revealed that MFO-tuned PI controller performs better than the different optimization techniques tuned PI controller for the same system and PI-PDF controller performs better than PI controller does. Then, the study is extended to a three-area interconnected hybrid system with proper generation rate constraint. Area-1 consists of solar thermal-thermal unit; area-2 consists of thermal-hydro unit and area-3 thermal-gas unit as generating sources. Performance of PI-PDF controller is compared with classical controllers such as PI, PID, PIDF, and PI-PD controller without filter. Result analysis divulges that MFO-tuned PI-PDF controller performs better than all other controllers considered in this article. Robustness of the PI-PDF controller is evaluated using parameter variations and random load variation.

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“…For modelling of solar thermal power plant, first the need is to model solar field. Buzás et al [25] have proposed the modelling of the same. The rate of change of output temperature is given by Eq.…”

Section: Solar Thermal Power Plantmentioning

confidence: 99%