Parabolic Trough Solar Thermal Power Plant Research Articles

Modelling of Solar Thermal Electricity Plants in the POSYTYF Research Project for an Extensive Integration of Renewable Energy Sources

This article presents a simplified simulation model of a concentrated solar thermal power plant developed in the framework of the European research project POSYTYF (POwering SYstem flexibiliTY in the Future through RES). Increasing the share of Renewable Energy Sources (RES) in modern power grids is of critical importance for the transformation of the energy markets worldwide. However, the stability of the grid and the limited participation in ancillary services of RES limit their use, especially when high penetration is expected from them. A solution to overcome these issues is to increase the share of so-called dispatchable RES (hydropower, biomass, concentrating solar thermal power). The main objective of the POSYTYF project is to group several renewable and non-renewable energy sources into a Dynamic Virtual Power Plant (DVPP). The simplified simulation model of a parabolic-trough solar thermal power plant developed consists of sub-models for the solar field, thermal energy storage system and power block and it has been validated with real DNI profiles and production data of a commercial STE plant in Spain. The differences between the simulation and real data of daily net production for the days analysed are lower than 1%. Parts of this paper were published as journal article “Using time-windowed solar radiation profiles to assess the daily uncertainty of solar thermal electricity production forecasts”, Journal of Cleaner Production, Volume 379, Part 2, 2022. Mario Biencinto, Lourdes González, Loreto Valenzuela (https://doi.org/10.1016/j.jclepro.2022.134821).

ANALYSIS OF A HYBRID CASCADED LATENT/SENSIBLE STORAGE SYSTEM FOR PARABOLIC-TROUGH SOLAR THERMAL PLANTS

The molten-salt two-tank system is the state-of-the-art thermal storage technology employed in the more mature parabolic-trough solar thermal power generation using synthetic oil as the heat-transfer fluid (HTF). This storage technology requires high storage-material inventory, making it very expensive. The use of latent-heat storage (LHS) system offers smaller storage size and material inventory. However, such a storage system faces two challenges: there are limited number of commercially-available phase-change materials (PCMs) are suitable in the operating temperature range; and these materials have very low thermal conductivities. The use of finned tubes, nevertheless, can overcome the later shortcoming. In this study, the analysis of a hybrid storage system, consisting of a three cascaded finned-tube LHS stages and a sensible concrete tube register stage, was carried out through modelling and simulation. A procedure for the design of the finned-tube cascaded LHS stages was developed. For a typical 50 MW parabolic-trough solar thermal power plant, the dimensions of a storage system with 6 hours of operation at full load were obtained. The three-stage cascaded LHS sub-system provides 45.5% of the total storage capacity of the entire system and has a volumetric specific capacity of 54% greater than that of the two-tank system. The volumetric specific capacity of the entire storage system is 9.3% greater than that of the two-tank system.

Estimation of the energy production of a parabolic trough solar thermal power plant using analytical and artificial neural networks models

The accurate estimation of a concentrated solar power plant production is an important issue because of the fluctuations in meteorological parameters like solar radiation, ambient temperature, wind speed, and humidity. In this work, three models were conducted in order to estimate the hourly electric production of a parabolic trough solar thermal power plant (PTSTPP) located at Ain Beni-Mathar in Eastern Morocco. First, two analytical models are considered. The first analytical model (AM I) is based on calculating the heat losses of parabolic trough collectors (PTCs), while the second analytical model (AM II) is based on the thermal efficiency of PTCs. The third model is an artificial neural networks (ANN) model derived from artificial intelligence techniques. All models are validated using one year of real operating data. The simulation results indicate that the ANN model performs much better than the analytical models. Accordingly, the ANN model results show that the estimated annual electrical energy is about 42.6 GW h/year, while the operating energy is approximately 44.7 GWh/year. The frequency of occurrence shows that 86.77% of hourly values were estimated with a deviation of less than 3 MW h. The developed ANN model is readily useable to estimate energy production for PTSTPP.

Modeling and Hourly Time-Scale Characterization of the Main Energy Parameters of Parabolic-Trough Solar Thermal Power Plants Using a Simplified Quasi-Dynamic Model

A simplified mathematical model of parabolic-trough solar thermal power plants, which allow one to carry out an energetic characterization of the main thermal parameters that influence the solar field performance, was evaluated through a comparison of simulation results. Two geographical locations were selected to evaluate the mathematical model proposed in this work—one in each hemisphere—and design considerations according with the practical/operational experience were taken. Furthermore, independent simulations were performed using the System Advisor Model (SAM) software, their results were compared with those obtained by the simplified model. According with the above, the mathematical model allows one to carry out simulations with a high degree of flexibility and adaptability, in which the equations that allow the plant to be energetically characterized are composed of a series of logical conditions that help identify boundary conditions between dawn and sunset, direct normal irradiance transients, and when the thermal energy storage system must compensate the solar field energy deficits to maintain the full load operation of the plant. Due to the above, the developed model allows one to obtain satisfactory simulation results; referring to the net electric power production, this model provides results in both hemispheres with a relative percentage error in the range of [0.28–8.38%] compared with the results obtained with the SAM, with mean square values of 4.57% and 4.21% for sites 1 and 2, respectively.

Potential assessment of a parabolic trough solar thermal power plant considering hourly analysis: ANN-based approach

One of the major challenges of developing and growing of parabolic trough solar thermal power plants (PTSTPPs) is enhancing the techno-economic performance. The goal of this study is to develop a unique artificial neural network (ANN) model that gives the best approach to predict the levelized cost of electricity (LCOE) of two different PTSTPPs integrated with thermal energy storage and fuel backup system; the first one is using thermic oil as primary heat transfer fluid in the solar field, while the other one is based on molten salt. By this way, the optimum designs of the two plants were determined in the LCOE analysis by using the obtained weights and biases of the best ANN topology. The techno-economic potentials of using molten salt in comparison to thermic oil of the two optimized plants were investigated considering both hourly and annual performances.The results show that it is possible to get minimum values of LCOE of 8.3 and 7.0 cent$/kWh for oil and salt configurations, respectively. Moreover, because of the difference in dispatch of thermal energy system and solar field aperture area of the plants, the annual power generation and capacity factor of salt plant are much higher than those of oil plant with a difference of around 26%.

ANN-based optimization of a parabolic trough solar thermal power plant

Design and optimization of a solar power plant are very complex and require many calculations, data and time. From this point of view, artificial neural network (ANN) models are desired options to determine techno-economic performances of this kind of plants. Therefore, the objective of this study is to investigate the feed-forward back-propagation learning algorithm with three different variants; Levenberge Marguardt (LM), Scaled Conjugate Gradient (SCG), and Pola-Ribiere Conjugate Gradient (CGP), used in the ANN to find the best approach for prediction and techno-economic optimization of parabolic trough solar thermal power plant (PTSTPP) integrated with fuel backup system and thermal energy storage. The obtained statistical parameters showed that LM algorithm with 38 neurons in a single hidden layer looks as the best ANN model to predict the annual power generation (PGnet) and levelized cost of electricity (LCOE) of the presented PTSTPP. Moreover, the obtained weights from this topology were used in the LCOE analysis for determining the optimum system design. It is therefore available to get a minimum LCOE of 8.88Cent/kWh from the new optimized plant when the plant characteristics are; 34°C and 850W/m2 for both design ambient temperature and solar radiation, 23m for row spacing, 1.7 for solar multiple, and 2.5h number of hours for the storage system.

Quasi-steady state simulations of thermal vapor compression multi-effect distillation plants coupled to parabolic trough solar thermal power plants

AbstractThe evaluation of the coupling of a 50 MWe parabolic trough solar thermal power plant (PT-STP) and a 10,000 m3/d multi-effect distillation plant with thermal vapor compression (MED-TVC) was performed. To that end, a model for the entire system has been developed and implemented within Engineering Equation Solver (EES) and Matlab software environments. Two coupling arrangements between the PT-STP plant and the MED-TVC unit were selected: one taking low-pressure steam (at 1.224 bar) from the power block to feed the MED-TVC and the other one taking high-pressure steam (at 20.6 bar), and the simulations of the electricity and fresh water production of the PT-STP + MED-TVC plant to be located in Spain were carried out during three days in summer (21–23 June) and three days in winter (21–23 December). Results obtained showed that the use of the low-pressure steam to feed the MED-TVC plant reduces the electricity penalization compared with the use of high-pressure steam but also decreases the fresh water...

Performance model and annual yield comparison of parabolic-trough solar thermal power plants with either nitrogen or synthetic oil as heat transfer fluid

The majority of commercial parabolic-trough plants in the world operate with synthetic oil as heat transfer fluid in the solar field. However, the synthetic oils that are available at affordable cost present some challenges such as their flammability, environmental toxicity and a temperature limitation of around 400°C. As alternative, this work proposes the use of pressurized nitrogen as heat transfer fluid. In order to analyze the feasibility of this technology, a comparison between a plant with nitrogen and a conventional plant with synthetic oil has been carried out. In both cases, 50MWe parabolic-trough plants with 6h of thermal storage are used as reference. A performance model including the solar field, the thermal storage system and the power block has been developed for each plant in the TRNSYS simulation software. This paper also describes the specifications, design and sizing of the solar field and explains the basic operation strategy applied in each model. Both annual simulations have been performed considering the same location, Almería (Spain), and meteorological data. In summary, the results show that similar net annual electricity productions can be attained for parabolic-trough plants with the same collection area using either nitrogen or synthetic oil as heat transfer fluid.

Switching moving boundary models for two-phase flow evaporators and condensers

The moving boundary method is an appealing approach for the design, testing and validation of advanced control schemes for evaporators and condensers. When it comes to advanced control strategies, not only accurate but fast dynamic models are required. Moving boundary models are fast low-order dynamic models, and they can describe the dynamic behavior with high accuracy. This paper presents a mathematical formulation based on physical principles for two-phase flow moving boundary evaporator and condenser models which support dynamic switching between all possible flow configurations. The models were implemented in a library using the equation-based object-oriented Modelica language. Several integrity tests in steady-state and transient predictions together with stability tests verified the models. Experimental data from a direct steam generation parabolic-trough solar thermal power plant is used to validate and compare the developed moving boundary models against finite volume models.

Analysis & Design of Parabolic Trough Solar Thermal Power Plant for Typical Sites of Pakistan

This paper investigates the feasibility of a Parabolic Trough Solar Thermal Power Plant (PTSTPP) for typical sites of Pakistan. The solar resource of the country is assessed against the required insolation levels. An optimum potential site with suitable irradiance level is identified and evaluated on the basis of certain parameters like wind speed, slope, land use, transmission lines, road & railway network, water resources & natural gas availability etc. A location near Nawabshah in Nara desert with total annual direct normal irradiance (DNI) of 2057.6 kWh per m 2 was found suitable for the construction of PTSTPP. A 30MW PTSTPP without any thermal energy storage is proposed on the selected site. The design comprises 56 collector loops with 4 parabolic trough collectors (PTC) per loop. The proposed design is verified with the help of simulation. The designed plant can generate 31.54 MW net on an average day in the month of June. The levelized cost of electricity (LCOE) is found to be 15.47 cents per kWh. The capacity factor of the proposed power plant comes out to be 20.5%. Cost comparison with conventional fossil fuel & renewable energy power plants already operational in Pakistan predicts that the proposed PTSTP plant can compete well in the current energy market of the country.

Effects of relative volume-ratios on dynamic performance of a direct-heated supercritical carbon-dioxide closed Brayton cycle in a solar-thermal power plant

The effect of the relative hot-to-cold side volume-ratios on dynamic characteristics of a CBC (closed Brayton cycle) with sCO2 (supercritical carbon-dioxide) as the working-fluid is investigated in this study. The analysis of the CBC is conducted in the context of power generation in a direct-heated (no thermal-oil loop) and dry-cooled parabolic-trough solar thermal power plant, using a control-oriented model of the CBC. Dynamic performance of the sCO2 CBC with different relative volume-ratios between the hot and cold sides of the sCO2 CBC is compared using simulations for conditions on a representative summer day. The CBC hot-to-cold side volume-ratio influences CO2 mass movement and hence power output. Increasing the hot-to-cold side volume-ratio in the CBC results in a slower, more gradual dynamic response when there are fluctuations in solar heat input and ambient air temperatures. The dynamic response characteristics of a CBC with a hot-to-cold side volume-ratio less than one are shown to differ significantly from a CBC with a volume-ratio greater than or equal to one.

Parabolic-trough solar thermal power plant simulation scheme, multi-objective genetic algorithm calibration and validation

Abstract The dynamic simulator design and development of a direct steam generation parabolic-trough solar thermal power plant is detailed in this paper. The dynamic simulator is not only the equation-based object-oriented model but also includes features to facilitate the simulation process. A whole simulator scheme has been developed for that purpose. This simulator scheme considers the issues of fetching and converting sensors data to model inputs and obtaining suitable initial values for the boundary condition problem in the numerical integration. The calibration and validation processes have been tackled, using Matlab as the primary tool. However, several tools were studied and tested. A multi-objective genetic algorithm approach has been chosen for calibrating the dynamic model.

Chattering in dynamic mathematical two-phase flow models

This paper presents a chattering problem which arises in a dynamic mathematical two-phase flow model. The real system under study is also introduced, the DISS test facility, a parabolic-trough solar thermal power plant. The heat transfer fluid in the DISS facility is the steam-water mixture. A dynamic model of this plant, using Modelica as the modeling language, was previously developed in order to study its behavior. Chattering arises in the pipe model reducing the computational performance and hence limiting the applicability of the model. The problem source is studied and analysed together with an approach to the problem which is based on the smooth interpolation of some thermodynamic properties.