Energy storage needs for the substitution of fossil fuel power plants with renewables

2020 ◽  
Vol 145 ◽  
pp. 951-962 ◽  
Author(s):  
Matthew D. Leonard ◽  
Efstathios E. Michaelides ◽  
Dimitrios N. Michaelides
2021 ◽  
Vol 03 (03) ◽  
pp. 1-1
Author(s):  
Efstathios E. Michaelides ◽  

The impending adverse effects of Global Climate Change encourages the substitution of fossil fuels with non-carbon sources for electricity generation. However, while fossil fuel power plants may generate electric power at demand, the most abundant renewable energy sources–wind and solar–are intermittent or periodically variable. This necessitates the development of adequate energy storage at the utility/grid level. Using actual data for the hourly energy demand in the ERCOT electricity grid, this study examines the electricity supply-demand equilibrium and determines the necessary energy storage capacity for the substitution, first, of the coal power plants and, secondly, of all the fossil fuel power plants. The calculations show that, if the natural gas, intermediate-load power plants continue to be available, all coal units may be substituted with wind farms without the need for energy storage. When all the fossil fuel units are to be substituted, significant energy storage capacity is required, approximately 45.3 million m3. The calculations also show that the further development of nuclear energy and additional solar energy units reduce the requirements for energy storage and, also lessen the energy dissipation in the storage-recovery process.


1985 ◽  
Vol 107 (4) ◽  
pp. 267-269 ◽  
Author(s):  
S. Z. Wu ◽  
D. N. Wormley ◽  
D. Rowell ◽  
P. Griffith

An evaluation of systems for control of fossil fuel power plant boiler and stack implosions has been performed using computer simulation techniques described in a companion paper. The simulations have shown that forced and induced draft fan control systems and induced draft fan bypass systems reduce the furnace pressure excursions significantly following a main fuel trip. The limitations of these systems are associated with actuator range and response time and stack pressure excursions during control actions. Preliminary study suggests that an alternative control solution may be achieved by discharging steam into the furnace after a fuel trip.


2019 ◽  
Vol 11 (9) ◽  
pp. 1117 ◽  
Author(s):  
Haopeng Zhang ◽  
Qin Deng

The frequent hazy weather with air pollution in North China has aroused wide attention in the past few years. One of the most important pollution resource is the anthropogenic emission by fossil-fuel power plants. To relieve the pollution and assist urban environment monitoring, it is necessary to continuously monitor the working status of power plants. Satellite or airborne remote sensing provides high quality data for such tasks. In this paper, we design a power plant monitoring framework based on deep learning to automatically detect the power plants and determine their working status in high resolution remote sensing images (RSIs). To this end, we collected a dataset named BUAA-FFPP60 containing RSIs of over 60 fossil-fuel power plants in the Beijing-Tianjin-Hebei region in North China, which covers about 123 km 2 of an urban area. We compared eight state-of-the-art deep learning models and comprehensively analyzed their performance on accuracy, speed, and hardware cost. Experimental results illustrate that our deep learning based framework can effectively detect the fossil-fuel power plants and determine their working status with mean average precision up to 0.8273, showing good potential for urban environment monitoring.


2021 ◽  
Vol 79 (7) ◽  
pp. 728-738
Author(s):  
Caique Lara ◽  
Julie Villamil ◽  
Anthony Abrahao ◽  
Aparna Aravelli ◽  
Guilherme Daldegan ◽  
...  

Fossil fuel power plants are complex systems containing multiple components that require periodic health monitoring. Failures in these systems can lead to increased downtime for the plant, reduction of power, and significant cost for repairs. Inspections of the plant’s superheater tubes are typically manual, laborious, and extremely time-consuming. This is due to their small diameter size (between 1.3 and 7.6 cm) and the coiled structure of the tubing. In addition, the tubes are often stacked close to each other, limiting access for external inspection. This paper presents the development and testing of an electrically powered pipe crawler that can navigate inside 5 cm diameter tubes and provide an assessment of their health. The crawler utilizes peristaltic motion within the tubes via interconnected modules for gripping and extending. The modular nature of the system allows it to traverse through straight sections and multiple 90° and 180° bends. Additional modules in the system include an ultrasonic sensor for tube thickness measurements, as well as environmental sensors, a light detecting and ranging (LiDAR) sensor, and camera. These modules utilize a gear system that allows for 360° rotation and provides a means to inspect the entire internal circumference of the tubes.


1971 ◽  
Vol 13 (1) ◽  
pp. 391-401 ◽  
Author(s):  
B.P. Breen ◽  
A.W. Bell ◽  
N. Bayard de Volo ◽  
F.A. Bagwell ◽  
K. Rosenthal

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