Simulation models for supporting the solar thermal power plant operator

Kalathakis, C.; Aretakis, N.; Roumeliotis, Ioannis; Alexiou, A.; Mathioudakis, K.

doi:10.1016/j.energy.2018.11.041

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…Environmentally benign treatment processes of wastewater driven by renewable energy have long been on the agenda. Therefore, solar energy has been utilized in many areas, including thermal power generation 36,37 and water purication. 26,33 This section discusses and presents a schematic diagram of the prospects for simultaneous solar thermal power generation coupled with wastewater treatment in order to fully understand the theory of the hybrid solar energy strategy in this work.…”

Section: Prospects For Power Generation Coupled With Wastewater Treat...mentioning

confidence: 99%

A rational strategy for substantially enhancing the solar-utilization efficiency and organic-pollutant-degradation rate via mediated central processing unit filling

Wang

Tao

et al. 2023

Sustainable Energy Fuels

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Section: Prospects For Power Generation Coupled With Wastewater Treat...mentioning

confidence: 99%

A rational strategy for substantially enhancing the solar-utilization efficiency and organic-pollutant-degradation rate via mediated central processing unit filling

Wang

Tao

et al. 2023

Sustainable Energy Fuels

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“…More recently, Kalathakis et al [24] proposed a simulation environment allowing both steady-state and transient modelling to perform everyday operation and maintenance management for an SPTS.…”

Section: Literature Reviewmentioning

confidence: 99%

Design parameter modelling of solar power tower system using adaptive neuro-fuzzy inference system optimized with a combination of genetic algorithm and teaching learning-based optimization algorithm

Khosravi

Malekan

Pabón

et al. 2020

Journal of Cleaner Production

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Determining the optimal sizing of a solar power tower system (SPTS) with a thermal energy storage system is subject to finding the optimum values of design parameters including the solar multiple (SM), design direct normal irradiance (DNI) and thermal storage hours. These design parameters are determined for each station separately and have remarkable effects on the thermo-economic performance of the system. This paper aims to demonstrate how artificial intelligence (AI) techniques may play an important role in addressing the above-mentioned need and help determine the optimum design parameters for different stations. For this purpose, we developed a thermo-economic model of a 100 MW SPTS with a molten salt storage system for five stations (two stations in India, and one each in Bangladesh, Pakistan, and Afghanistan). A method-based AI is utilized in this paper to ascertain the design parameters of the system. Additionally, a novel hybrid method based on adaptive neuro-fuzzy inference system optimized with a combination of genetic algorithm and teaching-learning-based optimization algorithm (ANFIS-GATLBO) is employed. The input parameters are latitude, longitude, design point DNI and SM, while the annual energy produced, levelized cost of energy and capacity factor are the target variables. The results of the study show that although the annual energy produced by SPTS rises by increasing the SM and decreasing design point DNI, optimum design parameters should be determined by the economic factors. In addition, it was found that the ANFIS-GATLBO method used in this study successfully predicted the targets with a correlation coefficient close to 1.

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Optimum Height and Tilt Angle of the Solar Receiver for a 30 kWe Solar Tower Power Plant for the Electricity Production in the Sahelian Zone

Faye

Thiam

Faye

2021

International Journal of Photoenergy

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This work investigated the prediction of the optimum height and tilt angle of the solar receiver of a 30 kWe solar tower power plant for the electricity production in the Sahelian zone. Initially, the solar field is sized to determine the total reflecting surface area of the mirrors and the number of heliostats. A PS10-like radially staggered heliostat field is used to design the heliostat layout in the field using a Matlab code. The concentrated solar flux at the input of the receiver was determined using Soltrace software by the Monte Carlo ray tracing (MCRT) method. The sizing results show that the total reflecting surface area is 350 m2 for an optical efficiency of 76.4% and a reference DNI of 600 W/m2. The solar field layout indicates 175 heliostats of 2 m2 surface area and 1.5 m height each. The simulation results show that the optimum height and tilt angle of the solar receiver are 26 m and 65°, respectively.

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Simulation models for supporting the solar thermal power plant operator

Cited by 3 publications

References 20 publications

A rational strategy for substantially enhancing the solar-utilization efficiency and organic-pollutant-degradation rate via mediated central processing unit filling

A rational strategy for substantially enhancing the solar-utilization efficiency and organic-pollutant-degradation rate via mediated central processing unit filling

Design parameter modelling of solar power tower system using adaptive neuro-fuzzy inference system optimized with a combination of genetic algorithm and teaching learning-based optimization algorithm

Optimum Height and Tilt Angle of the Solar Receiver for a 30 kWe Solar Tower Power Plant for the Electricity Production in the Sahelian Zone

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