New integration mechanism of solar energy into 300 MW coal-fired power plant: performance and techno-economic analysis

Energy ◽  
2021 ◽  
pp. 122005
Author(s):  
Enkhbayar Shagdar ◽  
Yong Shuai ◽  
Bachirou Guene Lougou ◽  
Azeem Mustafa ◽  
Dashpuntsag Choidorj ◽  
...  
2019 ◽  
Vol 125 ◽  
pp. 10003 ◽  
Author(s):  
Jaka Windarta ◽  
Ardhito Pratama ◽  
Denis ◽  
Agung Nugroho

Indonesia is a country that is geographically located right in the equator and variously advantage and the wide for the use of solar energy. Indonesia has a relatively high radiation level, which is 4.80 kWh / m2 / day. Cemara Island is a tourist place but does not have electricity from PLN because access to its location is still difficult to reach. So from that chosen the planning system for the use of electrical energy using solar energy. However, economic analysis is needed so that the estimated weaknesses of the off-grid solar system can be estimated so as to reduce the risk of losses. The testing of each component in the Solar Power Plant system also needs to be done to determine the condition and quality of the components to be used. The economic analysis of the Cemara Island Solar Power Plant System with an initial investment of Rp 52,553,000, in scenario 1 uses interest at 6%, then in scenario 2 without using interest. Through calculations by looking for the value of COE (Energy Cost), NPC (Net Present Cost) and BEP (Break-Even Point), so that costs can be calculated by the manager with the number of 11 managers per month.


2016 ◽  
Author(s):  
Mercedes Ibarra ◽  
Miguel Frasquet ◽  
Abdulaziz Al Rished ◽  
Arttu Tuomiranta ◽  
Sami Gasim ◽  
...  

Modelling ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 43-62
Author(s):  
Kshirasagar Naik ◽  
Mahesh D. Pandey ◽  
Anannya Panda ◽  
Abdurhman Albasir ◽  
Kunal Taneja

Accurate modelling and simulation of a nuclear power plant are important factors in the strategic planning and maintenance of the plant. Several nonlinearities and multivariable couplings are associated with real-world plants. Therefore, it is quite challenging to model such cyberphysical systems using conventional mathematical equations. A visual analytics approach which addresses these limitations and models both short term as well as long term behaviour of the system is introduced. Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) is used to extract features from the data, k-means clustering is applied to label the data instances. Finite state machine representation formulated from the clustered data is then used to model the behaviour of cyberphysical systems using system states and state transitions. In this paper, the indicated methodology is deployed over time-series data collected from a nuclear power plant for nine years. It is observed that this approach of combining the machine learning principles with the finite state machine capabilities facilitates feature exploration, visual analysis, pattern discovery, and effective modelling of nuclear power plant data. In addition, finite state machine representation supports identification of normal and abnormal operation of the plant, thereby suggesting that the given approach captures the anomalous behaviour of the plant.


Author(s):  
Mohamed Ashfaaq Riphque ◽  
Hadi Nabipour-Afrouzi ◽  
Chin-Leong Wooi ◽  
SanChuin Liew ◽  
Kamyar Mehranzamir ◽  
...  

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