scholarly journals Land-Use Requirements for Solar Power Plants in the United States

2013 ◽  
Author(s):  
S. Ong ◽  
C. Campbell ◽  
P. Denholm ◽  
R. Margolis ◽  
G. Heath
Keyword(s):  
United States ◽  
Land Use ◽  
Power Plants ◽  
Solar Power ◽  
The United States ◽  
Solar Power Plants

A comparison of CO2 emissions from fossil and solar power plants in the United States

Energy ◽  
1990 ◽  
Vol 15 (12) ◽  
pp. 1181-1198 ◽  
Author(s):  
Frank Kreith ◽  
Paul Norton ◽  
Daryl Brown
Keyword(s):  
United States ◽  
Co2 Emissions ◽  
Power Plants ◽  
Solar Power ◽  
The United States ◽  
Solar Power Plants

scholarly journals Solar Energy in the United States: Development, Challenges and Future Prospects

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8142
Author(s):  
Sanzana Tabassum ◽  
Tanvin Rahman ◽  
Ashraf Ul Islam ◽  
Sumayya Rahman ◽  
Debopriya Roy Dipta ◽  
...  
Keyword(s):  
United States ◽  
Renewable Energy ◽  
Solar Energy ◽  
Financial Incentives ◽  
Power Plants ◽  
Solar Power ◽  
Renewable Energy Sources ◽  
The United States ◽  
Heating And Cooling ◽  
The U.S

The ambitious target of net-zero emission by 2050 has been aggressively driving the renewable energy sector in many countries. Leading the race of renewable energy sources is solar energy, the fastest growing energy source at present. The solar industry has witnessed more growth in the last decade than it has in the past 40 years, owing to its technological advancements, plummeting costs, and lucrative incentives. The United States is one of the largest producers of solar power in the world and has been a pioneer in solar adoption, with major projects across different technologies, mainly photovoltaic, concentrated solar power, and solar heating and cooling, but is expanding towards floating PV, solar combined with storage, and hybrid power plants. Although the United States has tremendous potential for exploiting solar resources, there is a scarcity of research that details the U.S. solar energy scenario. This paper provides a comprehensive review of solar energy in the U.S., highlighting the drivers of the solar industry in terms of technology, financial incentives, and strategies to overcome challenges. It also discusses the prospects of the future solar market based on extensive background research and the latest statistics. In addition, the paper categorizes the U.S. states into five tiers based on their solar prospects calculated using analytical hierarchy process and regression analysis. The price of solar technologies in the U.S. is also predicted up to 2031 using Wright’s law, which projected a 77% reduction in the next decade.

scholarly journals Optimization under Uncertainty to Reduce the Cost of Energy for Parabolic Trough Solar Power Plants for Different Weather Conditions

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3131 ◽  
Author(s):  
Adarsh Vaderobli ◽  
Dev Parikh ◽  
Urmila Diwekar
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Power Plants ◽  
Solar Power ◽  
The United States ◽  
Black Box ◽  
Optimization Under Uncertainty ◽  
Parabolic Trough ◽  
Levelized Cost Of Electricity ◽  
Solar Power Plants

Renewable energy use can mitigate the effects of climate change. Solar energy is amongst the cleanest and most readily available renewable energy sources. However, issues of cost and uncertainty associated with solar energy need to be addressed to make it a major source of energy. These uncertainties are different for different locations. In this work, we considered four different locations in the United States of America (Northeast, Northwest, Southeast, Southwest). The weather and cost uncertainties of these locations are included in the formulation, making the problem an optimization-under-uncertainty problem. We used the novel Better Optimization of Nonlinear Uncertain Systems (BONUS) algorithm to solve these problems. The performance and economic models provided by the System Advisory Model (SAM) system from NREL were used for this optimization. Since this is a black-box model, this adds difficulty for optimization and optimization under uncertainty. The objective function and constraints in stochastic optimization (stochastic programming) problems are probabilistic functionals. The generalized treatment of such problems is to use a two-loop computationally intensive procedure, with an inner loop representing probabilistic or stochastic models or scenarios instead of the deterministic model, inside the optimization loop. BONUS circumvents the inner sampling loop, thereby reducing the computational intensity significantly. BONUS can be used for black-box models. The results show that, using the BONUS algorithm, we get 41%–47% of savings on the expected value of the Levelized Cost of Electricity (LCOE) for Parabolic Trough Solar Power Plants. The expected LCOE in New York is 57.42%, in Jacksonville is 38.52%, and in San Diego is 17.57% more than in Las Vegas. This difference is due to the differences in weather and weather uncertainties at these locations.

scholarly journals Techno-economic performances of future concentrating solar power plants in Australia

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Alberto Boretti ◽  
Stefania Castelletto
Keyword(s):  
High Frequency ◽  
Power Plants ◽  
Solar Power ◽  
The United States ◽  
Electricity Production ◽  
Real World Data ◽  
Statistical Parameters ◽  
Real Cost ◽  
Solar Power Plants ◽  
And Performance

AbstractThe prediction of the techno-economic performances of future concentrated solar power (CSP) solar tower (ST) with thermal energy storage (TES) plants is challenging. Nevertheless, this information is fundamental to energy policymakers. This work aims to fill the knowledge gap regarding estimations of costs, amount, and quality of electricity produced by these plants over their lifetime. Every estimate should be based on real-world data of actual costs incurred to build and maintain constructed plants, and their actual electricity production, sampled with high frequency, to be reliable. Here we discuss as the available information is insufficient. There has been so far very limited transparency on the real cost and performance of CSP plants built and operated worldwide, and in the very few cases where data has been made public, for example, Crescent Dunes in the United States, costs have been much higher than expected, while annual average capacity factors have been much less. Important statistical parameters such as the standard deviation of the capacity factor with high-frequency sampling have never been provided. We conclude as the techno-economic performances of these plants are therefore unpredictable with accuracy until a significant number of plants will be built and operated, their costs and operating parameters will be shared, and their delivered techno-economic performances will be compared to the modeled values, finally permitting validation of the techno-economic analysis tools.

Sign in / Sign up

Export Citation Format

Share Document