Evaluating and optimizing the cold energy efficiency of power generation and wastewater treatment in LNG-fired power plant based on data-driven approach

2021 ◽  
pp. 130149
Author(s):  
Jiaqi Tan ◽  
Shutao Xie ◽  
Wencong Wu ◽  
Peijia Qin ◽  
Tiancheng Ouyang
2017 ◽  
Vol 190 ◽  
pp. 18-28 ◽  
Author(s):  
Xin Wang ◽  
Zhengwei Li ◽  
Haixing Meng ◽  
Jiang Wu

2019 ◽  
Vol 23 (Suppl. 4) ◽  
pp. 1143-1151 ◽  
Author(s):  
Karol Sztekler ◽  
Wojciech Kalawa ◽  
Sebastian Stefanski ◽  
Jaroslaw Krzywanski ◽  
Karolina Grabowska ◽  
...  

At present, energy efficiency is a very important issue and it is power generation facilities, among others, that have to confront this challenge. The simultaneous production of electricity, heat and cooling, the so-called trigeneration, allows for substantial savings in the chemical energy of fuels. More efficient use of the primary energy contained in fuels translates into tangible earnings for power plants while reductions in the amounts of fuel burned, and of non-renewable resources in particular, certainly have a favorable impact on the natural environment. The main aim of the paper was to investigate the contribution of the use of adsorption chillers to improve the energy efficiency of a conventional power plant through the utilization of combined heat and power waste heat, involving the use of adsorption chillers. An adsorption chiller is an item of industrial equipment that is driven by low grade heat and intended to produce chilled water and desalinated water. Nowadays, adsorption chillers exhibit a low coefficient of performance. This type of plant is designed to increase the efficiency of the primary energy use. This objective as well as the conservation of non-renewable energy resources is becoming an increasingly important aspect of the operation of power generation facilities. As part of their project, the authors have modelled the cycle of a conventional heat power plant integrated with an adsorption chiller-based plant. Multi-variant simulation calculations were performed using IPSEpro simulation software.


2016 ◽  
Vol 7 (5) ◽  
pp. 2466-2476 ◽  
Author(s):  
Hamid Shaker ◽  
Hamidreza Zareipour ◽  
David Wood

2020 ◽  
Vol 11 (2) ◽  
pp. 1229-1238 ◽  
Author(s):  
Huishi Liang ◽  
Jin Ma ◽  
Rongfu Sun ◽  
Yanling Du

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6400
Author(s):  
Sara Antomarioni ◽  
Marjorie Maria Bellinello ◽  
Maurizio Bevilacqua ◽  
Filippo Emanuele Ciarapica ◽  
Renan Favarão da Silva ◽  
...  

Power plants are required to supply the electric demand efficiently, and appropriate failure analysis is necessary for ensuring their reliability. This paper proposes a framework to extend the failure analysis: indeed, the outcomes traditionally carried out through techniques such as the Failure Mode and Effects Analysis (FMEA) are elaborated through data-driven methods. In detail, the Association Rule Mining (ARM) is applied in order to define the relationships among failure modes and related characteristics that are likely to occur concurrently. The Social Network Analysis (SNA) is then used to represent and analyze these relationships. The main novelty of this work is represented by support in the maintenance management process based not only on the traditional failure analysis but also on a data-driven approach. Moreover, the visual representation of the results provides valuable support in terms of comprehension of the context to implement appropriate actions. The proposed approach is applied to the case study of a hydroelectric power plant, using real-life data.


2019 ◽  
Vol 14 (4) ◽  
pp. 1453-1462
Author(s):  
Jonggeun Kim ◽  
Hansoo Lee ◽  
Jungwon Yu ◽  
Jaeyel Jang ◽  
Jaeyeong Yoo ◽  
...  

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