System advisor model (SAM) simulation modelling of a concentrating solar thermal power plant with comparison to actual performance data

Ezeanya, Emeka K.; Massiha, G.H.; Simon, William E.; Raush, Jonathan; Chambers, Terrence L.

doi:10.1080/23311916.2018.1524051

Cited by 42 publications

(15 citation statements)

References 10 publications

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“…These user-friendly and budget-friendly tools combine wind resource models, such as the WIND Toolkit, with power curve databases and loss assumptions to produce site-specific annual energy production estimates. While validations of SAM exist for solar technology using actual plant performance data (Freeman et al, 2013;Rudié et al, 2014;Ezeanya et al, 2018;Freeman et al, 2019), we were unable to determine similar validations of SAM for small wind systems. Similarly, no validation of Wind Report using turbine production observations was able to be identified.…”

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confidence: 74%

Validation of Wind Resource and Energy Production Simulations for Small Wind Turbines in the United States

Sheridan

Phillips

Orrell

et al. 2021

Preprint

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Abstract. Due to financial and temporal limitations, the small wind community relies upon simplified wind speed models and energy production simulation tools to assess site suitability and produce energy generation expectations. While efficient and user-friendly, these models and tools are subject to errors that have been insufficiently quantified at small wind turbine heights. This study leverages observations from meteorological towers and sodars across the United States to validate wind speed estimates from the Wind Integration National Dataset (WIND) Toolkit, the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), revealing average biases within ±0.5 m s−1 at small wind hub heights. Observations from small wind turbines across the United States provide references for validating energy production estimates from the System Advisor Model (SAM), Wind Report, and MyWindTurbine.com, which are seen to overestimate actual annual capacity factors by 2.5, 4.2, and 11.5 percentage points, respectively. In addition to quantifying the error metrics, this paper identifies sources of model and tool discrepancies, noting that interannual fluctuation in the wind resource, wind speed class, and loss assumptions produce more variability in estimates than different horizontal and vertical interpolation techniques. The results of this study provide small wind installers and owners with information about these challenges to consider when making performance estimates and thus possible adjustments accordingly. Looking to the future, recognizing these error metrics and sources of discrepancies provides model and tool researchers and developers with opportunities for product improvement that could positively impact small wind customer confidence and the ability to finance small wind projects.

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confidence: 74%

Validation of Wind Resource and Energy Production Simulations for Small Wind Turbines in the United States

Sheridan

Phillips

Orrell

et al. 2021

Preprint

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“…The tool facilitates sensitivity and parametric analyses, studies of weather variability (P50/P90), and Monte Carlo simulation [26]. Several studies on CSP techno-economics have been conducted using this tool, such as that presented in [14,16,27,28].…”

Section: Methodology and Materialsmentioning

confidence: 99%

Comparative Analysis of Rankine Cycle Linear Fresnel Reflector and Solar Tower Plant Technologies: Techno-Economic Analysis for Ethiopia

et al. 2022

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The need to meet the world’s growing demand for energy in an environmentally sustainable manner has led to the exploration of various renewable energy (RE) resources for power generation. The objective of this study is to examine the techno-economic potential of concentrated solar power plants (i.e., linear Fresnel reflector (LFR) and central receiver system (CRS) for electricity generation in Eastern African countries with a case study on Ethiopia. The study was conducted using the System Advisor Model (SAM). In order to estimate the economics of the two power plants, the Levelized cost of energy (LCOE) and the net present value (NPV) metrics were used. According to results obtained from the simulations, the LFR produced annual energy of 528 TWh at a capacity factor (CF) of 60.3%. The CRS also produced a total of 540 TWh at a CF of 61.9%. The LCOE (real) for the CRS is found to be 9.44 cent/kWh against 10.35 cent/kWh for the LFR. The NPV for both technologies is found to be positive for inflation rates of 2% and below. An inflation rate above 2% renders the two power plants financially impracticable. A real discount rate above 9% also renders both projects economically unviable. Based on the obtained results, the CRS system is identified as the best technology for electricity generation under the Jijiga climatic condition in Ethiopia.

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“…From the literature review, it can be seen that the performance analysis of CSP plants has been performed using simulation tools including SAM: 2021-12-02 [35], IPSEpro7.0 [14], Epsilon15.0 [23], Transys18.0 [36], Matlab2019 [27], Modelica3.5 [37], and other relevant software utilizing the material and energy balance approach based on the thermodynamics' first and second laws. In this study, the IPSEpro software (CSP library) is used in the numerical simulation of the 50 MW CSP plant [38,39].…”

Section: Methods and Methodologymentioning

confidence: 99%

Performance Analysis of the 50 MW Concentrating Solar Power Plant under Various Operation Conditions

et al. 2022

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Power generation using concentrating solar energy is a potential solution to provide clean, green, and sustainable power generation in the long term. The objective of this paper is to analyze the performance of a parabolic trough collector-based concentrating solar power (CSP) plant by selecting four different reference days (i.e., 22 March, 22 June, 22 September, and 22 December), representing four seasons in Mongolian climate conditions. Numerical simulation of the 50 MW CSP plant was performed, both at nominal and part-load conditions using the heat balance method considering variations of power load owing to the direct normal irradiation (DNI). The results revealed that the 50 MW CSP plant could operate well throughout the year, and it showed the highest value of operating performance for the 22 June due to the higher DNI and small solar incidence angle. The operating performance for the 22 March and 22 September is nearly similar. The lowest value of operating performance occurred on the 22 December. Moreover, the operating performance of the CSP plant in the part-load conditions was significantly reduced compared to the nominal load owing to the DNI fluctuation. This study also revealed that the CSP plant could significantly contribute to environmental protection and climate change mitigation.

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System advisor model (SAM) simulation modelling of a concentrating solar thermal power plant with comparison to actual performance data

Cited by 42 publications

References 10 publications

Validation of Wind Resource and Energy Production Simulations for Small Wind Turbines in the United States

Validation of Wind Resource and Energy Production Simulations for Small Wind Turbines in the United States

Comparative Analysis of Rankine Cycle Linear Fresnel Reflector and Solar Tower Plant Technologies: Techno-Economic Analysis for Ethiopia

Performance Analysis of the 50 MW Concentrating Solar Power Plant under Various Operation Conditions

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