Concentrated Solar Thermal Plants Research Articles

Case Studies and Parametric Analysis of Heliostat Performance with a Tradeoff-informed Technoeconomic Analysis Metric

Abstract The Heliostat Consortium (HelioCon) was launched in 2021 to advance heliostat technology. This work presents a collection of baseline case studies for the technoeconomic analysis (TEA) of candidate heliostat improvements for concentrating solar power (CSP) and concentrated solar thermal (CST) systems that employ central receivers. The case studies we develop include a large-scale CSP plant, a smaller, modular CSP plant, and a small CST plant used for industrial process heat. In this work, we propose a novel metric for TEA of a plant component technology that recasts relative changes in levelized system costs into component-specific capital cost budgets. This measure, which we refer to as the equivalent breakeven installed cost, is the maximum budget for the technology component that leads to improved levelized costs. Finally, we perform a parametric analysis to show the impact of candidate technologies on levelized cost of heat and, by extension, equivalent breakeven installed cost.

A stochastic-MILP dispatch optimization model for concentrated solar thermal under uncertainty

Concentrated Solar Thermal (CST) offers a promising solution for large-scale solar energy utilization as Thermal Energy Storage (TES) enables electricity generation independent of daily solar fluctuations, shifting to high-priced electricity intervals. The development of dispatch planning tools is mandatory to account for uncertainties associated with weather and electricity price forecasts. A Stochastic Mixed-Integer Linear Program (SMILP) is proposed to maximize Sample Average Approximation (SAA) of expected profit within a specified scenario space. The SMILP exhibits robust performance, yet its computational time poses a challenge. Three heuristic solutions are developed which run a set of deterministic optimizations on different historical weather profiles to generate candidate Dispatch Plans (DPs). Subsequently, the DP with the best average performance on all profiles is selected. The new methods are applied to a hypothetical 115 MW CST plant in South Australia. When the historical database has a limited set of historical weather profiles, the SMILP achieves 6–9 % higher profit than the closest heuristic when the DPs are applied to novel weather conditions. With a large historical weather dataset, the performance of the SMILP and closet heuristic becomes nearly identical since the SMILP can only utilize a limited number of trajectories for optimization without becoming computationally infeasible. In this case, the heuristic emerges a practical alternative, providing similar average profit in a reasonable time. Taken together, the results illustrate the importance of considering uncertainty in DP optimization and indicate that straightforward heuristics on a large database are a practical method for addressing uncertainty.

Techno-economic assessment from a transient simulation of a concentrated solar thermal plant to deliver high-temperature industrial process heat

The need for new technologies to provide economically viable sources of high-temperature heat without any net CO2 emissions for industrial chemical processes has become a global priority. Concentrated solar thermal heat generation can play an important role in meeting this challenge. We report a detailed bottom-up techno-economic analysis of a concentrated solar thermal plant to deliver process heat at a temperature of 1100 °C at the scale anticipated for a commercial demonstrator. The system consists of a 50 MWth solar concentration subsystem with heliostats and a tower, a novel solar expanding-vortex particle receiver (SEVR) and a packed bed storage system, together with a combustion back-up to allow continuous operation. The system was optimized to determine the minimum levelized cost of heat (LCOH) from a detailed transient model of the complete system. Significantly, the system with the maximum efficiency for the receiver or storage alone does not deliver the best annual energetic performance, highlighting the need to understand the detailed interplay between the two systems to optimize overall performance. While this system is not yet optimized for the lowest cost of industrial heat, the sensitivity analysis provides important insight as to how to move toward this optimum. This system yields the lowest values of LCOH for the solar component of between 37 and 39 USD/GJ for a corresponding annual solar share (SSann) of 28% and 53% of the total heat demand of the industrial process, respectively. However, importantly, this solar share can be almost doubled for only a 5% increase in LCOH.

Innovative lifetime testing protocol for high-temperature secondary reflector materials used in concentrated solar thermal energies

The actual energy market based on fossil fuels is the responsible of more than half of the greenhouse gases generated worldwide. Renewable energies play a fundamental role to lead the transformation towards an energy market less damaging for the environment. Concentrated solar thermal (CST) energy is essential to achieve this objective because it is the most profitable renewable technology to store energy in the form of heat. In recent years, solar tower (ST) systems are the most installed CST plants thanks to their high operating temperatures that allow reaching greater efficiency. Developers are presently considering the integration of secondary concentrators on the top of the tower to improve its optical and thermal behavior, and hence, to increase the performance and feasibility of the system. However, no commercial high-temperature secondary reflector materials for ST systems are marketed because their durability is currently unpredictable. In this work, a new methodology based on accelerated aging tests is developed to predict the lifetime of secondary reflector materials in short time. Additionally, operating conditions that typically take place on a ST are simulated in a solar furnace to validate the reliability of the aging tests. The protocol developed was applied to a novel secondary material recently developed. According to the results obtained for this exemplary material, the main degradation is suffered due to the high temperature during operation. The correlation was validated under representative operating conditions with deviation of 0.2% of the reflectance comparing the accelerated aging and the operating conditions tests.

Plasmon silica aerogel for improving high-temperature solar thermal conversion

The next generation concentrated solar thermal (CST) plants need to move toward higher operation temperatures to achieve higher thermodynamic efficiency. However, solar absorbers operating at high temperatures have a significant radiative thermal loss. In present study, a hybrid plasmon aerogel doped with ITO nanocylinders was proposed for improving the photothermal conversion in high-temperature CST plants. For the first time, the localized surface plasmon resonance was applied in high-temperature photothermal conversion to achieve the greenhouse effect of aerogel. The effects of nanoparticle morphology, size, and doping concentration on the infrared absorption performance of the hybrid aerogel were investigated by the combination of the T-matrix and Monte Carlo method. The operation temperature of the solar absorber was calculated to evaluate the insulation performance of the hybrid plasmon aerogels. The results show that, at the solar concentration ratio C = 20, the maximum increase of 113.9 °C in operation temperature can be achieved withaerogel thickness l = 5 mm and ITO nanocylinder doping concentration f v = 0.016%. This study sheds light on high-efficiency hybrid plasmon aerogel serving as a transparent thermal insulation barrier for high-temperature CST plants with high solar transmittance, low thermal conductivity, and low radiative thermal loss. • A kind of hybrid plasmon aerogel based on ITO nanocylinders and silica aerogel matrix is proposed and optimal designed for the CST plants. • The combination of T-matrix method and Monte Carlo method is applied to compute the radiative properties of the hybrid aerogel. • The operation temperature of solar absorber is calculated to assess the thermal insulating performance of the hybrid plasmon aerogel.

Lifetime prediction model of reflector materials for concentrating solar thermal energies in corrosive environments

Concentrated solar thermal technologies play an essential role in the energetic transition which is currently facing our society. The energy generation in this technology vastly depends on the optical behaviour of the reflector materials of the solar field. Corrosion of solar reflectors might be an issue in locations with high corrosive environments because an excessive corrosion of the solar mirror could be catastrophic for the profitability of the concentrated solar thermal plant. This research is focusing on modelling the durability of four different solar reflector materials exposed outdoors by accelerated aging tests. For this purpose, ten locations suitable for concentrating solar thermal applications were classified depending on their corrosive aggressiveness. Commercial, free-lead and low-cost reflectors samples were exposed in all the sites to determine the influence of the corrosion in its durability. Corrosion defects appeared in the solar reflectors during outdoor exposure were properly reproduced by CASS test. Novel lifetime prediction models were developed for all the solar reflectors depending on the corrosive aggressiveness of the place. Number and thickness of the paint coatings employed in the solar mirrors were identified as one of the most important parameters to improve the energy generation of a CSP plant in corrosive environments. A reduction of the capital invested in the solar mirror purchase is expected for sites with low corrosivity.

Clear-sky direct normal irradiance estimation based on adjustable inputs and error correction

The accurate estimation of direct normal irradiance (DNI) under clear sky conditions plays an important role in the concentrated solar thermal plant. A hybrid model with adjustable inputs is proposed to calculate the clear-sky DNI, including a base clear-sky model and an error-correction model. The base clear-sky model is able to estimate the clear-sky DNI at any place with only the local date and location information, and the error-correction model serves as a supplementary to improve the calculating accuracy with available meteorological data. The error-correction model effectively integrates a linear part and a nonlinear part, and its inputs are adjustable according to the available meteorological observations. Several experiments have been conducted to evaluate the performance of the proposed model with data from three observation stations provided by the National Renewable Energy Laboratory open database. The results show that the hybrid model is able to provide great improvement over the base clear-sky model with 28%–70% on normalized root mean square error, and it also performs better than those using a linear or nonlinear error correction model. It is concluded that the performance of the hybrid model is comparable with other published methods in calculating the clear-sky DNI with concrete statistics.

Thermoeconomic assessment of a novel integrated CHP system incorporating solar energy based biogas-steam reformer with methanol and hydrogen production

This paper deals with a novel solar-biogas fueled combined heat and power system with methanol and hydrogen production. The proposed energy system consists following subsystems: solar based biogas-steam reformer, gas turbine cycle, Rankine and organic Rankine cycles, pressure swing adsorption, carbon capture and sequestration and methanol synthesis unit. The selected solar system is molten salt tower-based concentrated solar thermal plant that provides required thermal energy for reforming process. The multigeneration system is comprehensive analyzed thermoeconomically and exergoenvironmentally. A parametric study is conducted to find the effects of key parameters on the system performance. The considered key parameters include steam to carbon ratio of reforming process, operating temperature and pressure of reformer. The results show that Tr is the most effective parameters for improving system performance. A 200 K increase in reforming temperature, from 923 K to 1123 K, leads to decreases of 15% and 10% in the energy and exergy efficiencies, respectively. The opposite trend is observed for net power output and mass flow rate of produced methanol when key parameters change. Nevertheless, mass flow rate of produced methanol plays most important role for evaluating energy and exergy efficiencies. Also, gas turbine cycle and reformer have highest exergy destruction rate of 140 MW and 134 MW, respectively when system operates in optimum condition. Moreover, best exergoenvironmental parameters are obtained at higher value of reforming temperature and lower values of reforming pressure and steam to carbon ratio of reforming process.

Optimal integration of linear Fresnel reflector with gas turbine cogeneration power plant

Solar energy is an abundant resource in many countries in the Sunbelt, especially in the middle east, countries, where recent expansion in the utilization of natural gas for electricity generation has created a significant base for introducing integrated solar‐natural gas power plants (ISGPP) as an optimal solution for electricity generation in these countries. ISGPP reduces the need for thermal energy storage in traditional concentrated solar thermal plants and results in dispatchable power on demand at lower cost than stand-alone concentrated thermal power and much cheaper than photovoltaic plants. Moreover, integrating concentrated solar power (CSP) with conventional fossil fuel based thermal power plants is quite suitable for large-scale central electric power generation plants and it can be implemented in the design of new installed plants or during retrofitting of existing plants. The main objective of the present work is to investigate the possible modifications of an existing gas turbine cogeneration plant, which has a gas turbine of 150 MWe electricity generation capacity and produces steam at a rate of 81.4 at 394°C and 45.88bars for an industrial process, via integrating it with concentrated solar power system. In this regard, many simulations have been carried out using Thermoflow software to explore the thermo-economic performance of the gas turbine cogeneration plant integrated with LFR concentrated solar power field. Different electricity generating capacities of the gas turbine and different areas of solar collectors have been examined. Thermoflow software simulation results have been used to identify the optimal configuration and sizing of the gas turbine and the solar field of the integrated solar gas turbine cogeneration plant (ISGCPP) required to achieve the required steam generation with the minimum cost and environmental impact. The study revealed that ISGCPP can reduce the levelized electricity cost by 76–85% relative to the fully-solar-powered LFR power plant. Moreover, the study identified the configuration of ISGCPP with a gas turbine size of 50 MWe capacity and 93ha of LFR solar field as the optimally integrated plant. It reduces the annual CO2 emission by 100k Tonne (18%) in comparison with that emitted by the corresponding conventional plant with 50 MWe and 400k tonne (43.75%) compared with that emitted by the original conventional plant with a gas turbine if 150 MWe power generation capacity. The study revealed also that integrating the LFR technology with a gas turbine cogeneration power plant in locations with high solar insolation was proved to have more economic feasibility than CO2 capturing technology. Under Dhahran weather conditions, the LEC of about 5 USȻ/kWh is obtained using the proposed optimally configured ISGCPP compared with about 7.5 USȻ/kWh obtained by the corresponding conventional cycle integrated with carbon capture technology. In other words, the ISGCPP reduces the LEC by 50% while achieving the same reduction of CO2 emission by an equivalent conventional plant integrated with carbon capture technology.

Clear-sky model for wavelet forecast of direct normal irradiance

Direct normal irradiance (DNI) is vital for concentrated solar thermal plants, and its value under clear sky condition is usually used as an important input of some forecasting models for solar irradiance. First of all, a semi-empirical model is developed for calculating the clear-sky DNI, and it is used to transform DNI into clear-sky index to remove the impact of the sun's position on DNI. Then, a wavelet forecasting model, using the clear-sky index as input, is proposed for estimating the inter-hour DNI under any sky conditions. The non-stationary series of the clear-sky index is decomposed by wavelet technology to obtain four sub-series with different frequencies, and forecasting sub-models are constructed according to the features of corresponding sub-series, respectively. Finally, model validation is conducted with data from the open database of the National Renewable Energy Laboratory. The result shows that the performance of the clear-sky model is satisfactory comparing with some other published clear-sky models, and that the wavelet forecasting model achieves great performance with nMAE = 0.84–7.66% and nRMSE = 1.89–10.99% for four different stations and also outperforms other published forecasting models.

Evaluating the benefits of using short-term direct normal irradiance forecasts to operate a concentrated solar thermal plant

Past studies about using direct normal irradiance (DNI) forecasts to operate a concentrated solar thermal (CST) plant have not considered intra-day forecasts. This is a critical research gap because short-term forecasts are recommended for managing variable output from renewable energy generators, including CST plants. This study evaluates the benefits of using 1-h forecasts to decide updated bids for a CST plant after making initial bids from 48-h forecasts. The benefits are represented by the financial value calculated from revenue and reserve generation (RG) payments, and the reliability calculated from the equivalent forced outage rate (EFOR).Simulating a CST plant operating in the Australian National Electricity Market for one year showed that using 1-h forecasts increases financial value by $1.04–1.13million and reduces EFOR by 20–21% points for a 50 Megawatt (MW) CST plant with 7.5h of storage, and increases financial value by $0.7–$0.9million and reduces EFOR by 20–23% points for a 50MW CST plant without storage. Reduced RG costs contributed towards 76–98% of the financial value increase for both CST plants. A CST plant without storage that uses 1-h forecasts achieves an EFOR of 10–11%, whereas a CST plant with storage that does not use 1-h forecasts achieves an EFOR of 21–22%, so using 1-h forecasts may improve reliability more than adding storage to a CST plant without storage. Using 1-h forecasts does not achieve the same total net value as a perfect 48-h forecast, but it achieves close to maximum value per unit electricity generated. Overall, CST plants should use short-term forecasts if permitted under local electricity market regulations because they can achieve higher financial value and reliability. Future studies should use short-term forecasts when allowed by the local electricity market to more accurately demonstrate the value of CST plants.

Off-design simulation and performance of molten salt cavity receivers in solar tower plants under realistic operational modes and control strategies

Solar irradiation is intermittent, but concentrated solar thermal (CST) plants are typically designed and analyzed solely based on their steady design point. Unlike coal power plants, however, CST plants frequently experience thermal loads well above and below their rated design point, leading to off-design operation for much of the operational year. Importantly, if a latent heat thermal energy storage (LHTES) system is employed, the receiver inlet temperature can vary under these conditions. To date, there is a clear lack of knowledge for how to handle off-design conditions in terms of developing appropriate control strategies to maximize the receiver thermal output and its operational region. In this study, a thermal model was developed and validated that is suitable for design/off-design performance analyses of molten salt cavity receivers in both steady state and transient conditions. The study investigated two control strategies – a fixed receiver flow rate (FF) and fixed receiver outlet temperature (FT) – for their off-design performance in each of two off-design operational modes (storage and non-storage). Solar field utilization (SFU) is variable in non-storage mode, but in the storage mode, it is whether variable or fixed at design point (SFU=1). The feasible operating region in this study refers to the zone restricted by maximum allowable operational parameters defined based on design point analysis, mainly maximum receiver outlet temperature, maximum flow rate, and maximum receiver surface temperature.Through this analysis, it was found that receiver inlet temperatures above the design point (560K) degrade the receiver performance in both control strategies and under all operational modes. The results also revealed that the maximum allowable receiver inlet temperature that maintains the receiver operation inside the feasible region could not go beyond ∼700K or 600K with the FF and FT strategies (in the storage mode with variable or fixed SFU), respectively. These values also indicate the charging cut-off temperature for the fluid flowing out in LHTES systems. In the non-storage mode, the receiver inlet temperature is remained constant at design point by varying the SFU over the time. While the design point direct normal irradiation (DNI) was 900Wm−2, the maximum allowable DNI is 700Wm−2 and 500Wm−2 with the FF and FT strategies, respectively. These results motivate a hybrid control strategy that switches between the FF and FT strategies to maximize the performance and the number of operational hours of a CST plant during the day. As a final aspect of this study, off-design receiver efficiency correlations are developed that can be used in any simulation environment to accurately predict receiver performance.

Calculating the financial value of a concentrated solar thermal plant operated using direct normal irradiance forecasts

This study examines the effect of direct normal irradiance (DNI) forecast accuracy on the financial value of a concentrated solar thermal (CST) plant. Other factors such as electricity market regulations, plant site local climate, and operating strategy are not considered. A CST model varied over 11 combinations of solar field sizes and storage sizes is used to simulate plant operation for three forecast methods and a perfect forecast. The financial value is calculated using revenue and reserve generation payments resultant from plant operation.Results show when the root mean square error (RMSE) of a 48-h DNI forecast is between 325 and 400W/m2, a 1W/m2 improvement increases the financial value by $400–1300 per 6months operation for a CST plant with solar multiple between 1.25 and 2, and storage size between 0 and 20h. Similarly, when the mean absolute error (MAE) is between 250 and 300W/m2, a 1W/m2 improvement shows an increase of $1000–3600 per 6months operation. If two forecast methods have similar MAE or RMSE, then the method that tends to over-predict DNI achieves higher value. For all forecast methods, increasing solar multiple or storage size increases financial value. Financial value expressed using only revenue is overstated by 14–64% compared to using both revenue and reserve generation payments, depending on the CST plant configuration and the forecast method. CST plants with small solar fields or small storage sizes gain proportionally more from investing to obtain better DNI forecasts because more accurate forecasts help these CST plants generate more electricity from the limited solar field thermal output, and use more of the limited stored thermal energy to increase revenue instead of reduce reserve generation payments caused by forecast errors.

Direct normal irradiance forecasting and its application to concentrated solar thermal output forecasting – A review

Solar irradiance forecasting can reduce the uncertainty of solar power plant output caused by solar irradiance intermittency. Concentrated solar thermal (CST) plants generate electricity from the direct normal irradiance (DNI) component of solar irradiance. Different forecasting methods have been recommended for a range of forecast horizons relevant to electricity generation. High DNI forecast accuracy is important for achieving accurate forecasts of CST plant output which are shown to increase CST plant profitability. This paper reviews the DNI forecast accuracy of numerical weather prediction models, time series analysis methods, cloud motion vectors, and hybrid methods. The results of the reviewed papers are summarised to identify the best DNI forecast accuracy for particular forecast horizons. The application of DNI forecasts to operate CST plants is also briefly reviewed.This paper found that additional research is required for time series analysis methods to corroborate current results and for satellite-based cloud motion vectors to establish DNI forecast accuracy. It was also concluded that future research should use the same error metrics to report results to facilitate fair comparison of DNI forecast accuracy from different studies. In addition, the creation of a common high quality DNI data set to evaluate all forecasting methods would also help to verify best forecast accuracy. The review of DNI forecasting for CST plants found that using accurate 2-day ahead DNI forecasts can increase revenue and decrease penalty costs. Future research should investigate benefits from using short-term DNI forecasts from the intra-hour forecast horizon up to the 6-h forecast horizon to determine CST plant operation. Another aspect to research is to determine whether the benefit of DNI forecasts for a CST plant is affected by different regulations in different electricity markets.

Dense suspension of solid particles as a new heat transfer fluid for concentrated solar thermal plants: On-sun proof of concept

This paper demonstrates the capacity of dense suspensions of solid particles to transfer concentrated solar power from a tubular receiver to an energy conversion process by acting as a heat transfer fluid. Contrary to a circulating fluidized bed, the dense suspension of particles’ flows operates at low gas velocity and large solid fraction. A single-tube solar receiver was tested with 64µm mean diameter silicon carbide particles for solar flux densities in the range 200–250kW/m2, resulting in a solid particle temperature increase ranging between 50°C and 150°C. The mean wall-to-suspension heat transfer coefficient was calculated from experimental data. It is very sensitive to the particle volume fraction of the suspension, which was varied from 26 to 35%, and to the mean particle velocity. Heat transfer coefficients ranging from 140W/m2K to 500W/m2K have been obtained, thus corresponding to a 400W/m2K mean value for standard operating conditions (high solid fraction) at low temperature. A higher heat transfer coefficient may be expected at high temperatures because the wall-to-suspension heat transfer coefficient increases drastically with temperature. The suspension has a heat capacity similar to a liquid heat transfer fluid, with no temperature limitation but the working temperature limit of the receiver tube. Suspension temperatures of up to 750°C are expected for metallic tubes, thus opening new opportunities for high efficiency thermodynamic cycles such as supercritical steam and supercritical carbon dioxide.