Global trade of green hydrogen will probably become a vital factor in reaching climate neutrality. The sunbelt of the Earth has a great potential for large-scale hydrogen production. One promising pathway to solar hydrogen is to use economically priced electricity from photovoltaics (PV) for electrochemical water splitting. However, storing electricity with batteries is still expensive and without storage only a small operating capacity of electrolyser systems can be reached. Combining PV with concentrated solar power (CSP) and thermal energy storage (TES) seems a good pathway to reach more electrolyser full load hours and thereby lower levelized costs of hydrogen (LCOH). This work introduces an energy system model for finding cost-optimal designs of such PV/CSP hybrid hydrogen production plants based on a global optimization algorithm. The model includes an operational strategy which improves the interplay between PV and CSP part, allowing also to store PV surplus electricity as heat. An exemplary study for stand-alone hydrogen production with an alkaline electrolyser (AEL) system is carried out. Three different locations with different solar resources are considered, regarding the total installed costs (TIC) to obtain realistic LCOH values. The study shows that a combination of PV and CSP is an auspicious concept for large-scale solar hydrogen production, leading to lower costs than using one of the technologies on its own. For today’s PV and CSP costs, minimum levelized costs of hydrogen of 4.04 USD/kg were determined for a plant located in Ouarzazate (Morocco). Considering the foreseen decrease in PV and CSP costs until 2030, cuts the LCOH to 3.09 USD/kg while still a combination of PV and CSP is the most economic system.

Photovoltaic (PV) - concentrated solar power (CSP) hybrid power plants are an attractive option for supplying cheap and dispatchable solar electricity. Hybridization options for both technologies were investigated, combining their benefits by a deeper integration. Simulations of the different systems were performed for seven different sites by varying their design parameters to obtain the optimal configurations under certain boundary conditions. A techno-economic analysis was performed using the levelized cost of electricity (LCOE) and nighttime electricity fraction as variables for the representation. Hybrid power plants were compared to pure CSP plants, PV-battery plants, and PV plants with an electric resistance heater (ERH), thermal energy storage (TES), and power block (PB). Future cost projections were also considered.

The issue of reflector soiling becomes more important as concentrating solar thermal power plants (CSP) are being implemented at sites subject to high dust loads. In an operational power plant, a trade-off between reducing cleaning costs and cleaning related collector availability on the one hand and keeping the solar field cleanliness (ξfield) high to minimize soiling induced losses on the other hand must be found. The common yield analysis software packages system advisor model (SAM) and greenius only allow the input of a constant mean ξfield and constant cleaning costs. This oversimplifies real conditions because soiling is a highly time-dependent parameter and operators might adjust cleaning activities depending on factors such as soiling rate and irradiance. In this study, time-dependent soiling and cleaning data are used for modeling the yield of two parabolic trough plant configurations at two sites in Spain and Morocco. We apply a one-year soiling rate dataset in daily resolution measured with the tracking cleanliness sensor (TraCS). We use this as a basis to model the daily evolution of the cleanliness of each collector of a solar field resulting from the application of various cleaning strategies (CS). The thus obtained daily average ξfield is used to modify the inputs to the yield analysis software greenius. The cleaning costs for each CS are subtracted from the project's financial output parameters to accurately predict the yield of a CSP project over its lifetime. The profits obtained with different CSs are compared in a parameter variation analysis for two sites and the economically best CS is identified. The profit can be increased by more than 2.6% by the application of the best strategy relative to a reference strategy that uses a constant cleaning frequency. The error in profit calculated with constant soiling and cleaning parameters compared to the simulation with variable soiling and cleaning can be as high as 9.4%. With the presented method, temporally variable soiling rates and CS can be fully integrated to CSP yield analysis software, significantly increasing its accuracy. It can be used to determine optimum cleaning parameters.

An existing software tool for annual performance calculation of concentrating solar power and other renewable energy plants has been extended to enable the simulation of solar tower power plants. The methodology used is shown and a demonstrative example of a 50 MWe tower plant in southern Spain is given. The influence of design power and latitude on solar field layout is discussed. Furthermore, a comparison of the tower plant with a 50 MWe parabolic trough and a Linear Fresnel plant at the same site is given.

Industrial energy accounts for a large percentage of global consumption and, thus, it is a target for decarbonization by renewable and in particular solar energy adoption. Low uncertainty simulation tools can reduce the financial risk of solar projects, fostering the transition to a sustainable energy system. Several simulation tools are readily available to developers; differences exist in the format of input data and complexity of physical and numerical models. These tools can provide a variety of results from technical to financial and sensitivity analysis, often producing significant differences in yield assessment and uncertainty levels. IEA SHC Task 64/SolarPACES Task IV—Subtask C aims to address the lack of standard simulation tools for Solar Heating of Industrial Processes (SHIP) plants. This article describes the collaborative work developed by the researchers participating in the task. The identification and classification of several currently available simulation tools are performed on the basis of their capabilities and simulation approaches. A case study of solar heat supply to a copper mining operation is defined, allowing a comparison of the results produced by equivalent simulation tools. The proposed methodology identifies the main sources of differences among the simulation tools, the assessment of the deviation considering a series of statistical metrics for different time scales, and identifies their limitations and bias. The effects of physical characteristics of SHIP plants and different simulation approaches are discussed and quantified. The obtained results allow us to develop a basic guideline for a standardized yield assessment procedure with known uncertainties. Creating this common framework could partially reduce the risk perceived by the finance industry regarding SHIP systems.

This study compares the levelized cost of energy (LCOE) of parabolic trough solar power plants using thermal oil or two different molten salt mixtures located at three different sites and with different thermal storage capacities. The necessity of using appropriate model approaches for the temperatures along a loop of the solar field is discussed, as well as the utilization of heat from thermal storage for freeze protection of the molten salt plants. The ternary salt mixture with a lower temperature limit of 170 °C and an upper temperature limit of 500 °C shows the lowest LCOE for all sites and almost all investigated storage capacities. Molten salts as heat transfer fluids are particularly favorable for sites with high irradiation and plants with large storage capacities of more than six full load hours.