scholarly journals Predictive Maintenance for Pump Systems and Thermal Power Plants: State-of-the-Art Review, Trends and Challenges

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2425 ◽  
Author(s):  
Jonas Fausing Olesen ◽  
Hamid Reza Shaker
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Health Management ◽  
Thermal Power ◽  
Predictive Maintenance ◽  
Data Driven ◽  
Thermal Power Plants ◽  
Broad Concept ◽  
Automatic Maintenance ◽  
Critical Components

Thermal power plants are an important asset in the current energy infrastructure, delivering ancillary services, power, and heat to their respective consumers. Faults on critical components, such as large pumping systems, can lead to material damage and opportunity losses. Pumps plays an essential role in various industries and as such clever maintenance can ensure cost reductions and high availability. Prognostics and Health Management, PHM, is the study utilizing data to estimate the current and future conditions of a system. Within the field of PHM, Predictive Maintenance, PdM, has been gaining increased attention. Data-driven models can be built to estimate the remaining-useful-lifetime of complex systems that would be difficult to identify by man. With the increased attention that the Predictive Maintenance field is receiving, review papers become increasingly important to understand what research has been conducted and what challenges need to be addressed. This paper does so by initially conceptualising the PdM field. A structured overview of literature in regard to application within PdM is presented, before delving into the domain of thermal power plants and pump systems. Finally, related challenges and trends will be outlined. This paper finds that a large number of experimental data-driven models have been successfully deployed, but the PdM field would benefit from more industrial case studies. Furthermore, investigations into the scale-ability of models would benefit industries that are looking into large-scale implementations. Here, examining a method for automatic maintenance of the developed model will be of interest. This paper can be used to understand the PdM field as a broad concept but does also provide a niche understanding of the domain in focus.

Ultimate Trough: The New Parabolic Trough Collector Generation for Large Scale Solar Thermal Power Plants

2011 ◽  
Author(s):  
Klaus-Ju¨rgen Riffelmann ◽  
Daniela Graf ◽  
Paul Nava
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Thermal Power ◽  
Thermal Storage ◽  
Solar Thermal ◽  
Thermal Power Plants ◽  
Large Power ◽  
Solar Thermal Power ◽  
Aperture Width ◽  
Solar Field

From 1984 to 1992, the first commercial solar thermal power plants — SEGS I to IX — were built in the Californian Mojave desert. The first generation of trough collectors (LS1) used in SEGS I showed an aperture area of about 120 m2 (1’292 ft2), having an aperture width of 2.5 m (8.2 ft). With the second generation collector (LS2), used in SEGS II to VI, the aperture width was doubled to 5 m (16.4 ft). The third generation (LS3) has been increased regarding width (5.76 m or 18.9 ft) and length (96 m or 315 ft) to about 550 m2 (5’920 ft2) aperture. It was used in the last SEGS plants VIII and IX, those plants having a capacity of 80 MW each. After more than 10 years stagnancy, several commercial plants in the US (the 64 MW Nevada Solar One project) and Spain (the ANDASOL projects, 50 MW each with 8 h thermal storage) started operation in 2007/2008. New collectors have been developed, but all are showing similar dimensions as either the LS2 or the LS3 collector. One reason for this is the limited availability of key components, mainly the parabolic shaped mirrors and heat collection elements. However, in order to reduce cost, solar power projects are getting larger and larger. Several projects in the range of 250 MW, with and without thermal storage system, are going to start construction in 2011, requiring solar field sizes of 1 to 2.5 Million m2. FLABEG, market leader of parabolic shaped mirrors and e.g. mirror supplier for all SEGS plants and most of the Spanish plants, has started the development of a new collector generation to serve the urgent market needs: lower cost and improved suitability for large solar fields. The new generation will utilize accordingly larger reflector panels and heat collection elements attended by advanced design, installation methods and control systems at the same time. The so-called ‘Ultimate Trough’ collector is showing an aperture area of 1’667 m2 (17’944 ft2), with an aperture width of 7.5 m (24.6 ft). Some design features are presented in this paper, showing how the new and huge dimensions could be realized without compromising stiffness, and bending of the support structure and improving the optical performance at the same time. Solar field layouts for large power plants are presented, and solar field cost savings in the range of 25% are disclosed.

scholarly journals The Application of Cyber Physical System for Thermal Power Plants: Data-Driven Modeling

Energies ◽  
2018 ◽  
Vol 11 (4) ◽  
pp. 690 ◽  
Author(s):  
Yongping Yang ◽  
Xiaoen Li ◽  
Zhiping Yang ◽  
Qing Wei ◽  
Ningling Wang ◽  
...  
Keyword(s):  
Physical System ◽  
Power Plants ◽  
Thermal Power ◽  
Data Driven ◽  
Cyber Physical System ◽  
Thermal Power Plants ◽  
Data Driven Modeling

scholarly journals Combined PSO and IBF Algorithm for Short Term Hydro Thermal Scheduling

2019 ◽  
Vol 8 (4S2) ◽  
pp. 418-424
Keyword(s):  
Power Generation ◽  
Power Plant ◽  
Convergence Rate ◽  
Power Plants ◽  
Large Scale ◽  
Thermal Power ◽  
Research Work ◽  
Thermal Power Plants ◽  
Scheduling Problems ◽  
Short Term

Hydro and thermal power plants are planned to reduce the overall operation cost of the thermal power plants by optimally allocating the hydro units and thermal units in the power generation system. In this research work a combined particle swarm optimization (PSO) and improved bacterial foraging algorithm (IBFA) is proposed for short term hydro thermal scheduling (STHTS) with prohibited operating zones (POZs). The PSO algorithm yields the fastest convergence rate and possesses maximum capability of finding the global optimal solutions to the HTS (Hydro Thermal Scheduling) problems. Also BFA has succeeded in solving several issues in optimization, but it demonstrates poor convergence characteristics for large-scale issues such as the STHTS problem. Critical improvements to the basic BFA are implemented to tackle this complex issue in view of its high-dimension search space. The chemotactic step is changed in IBF, so that the convergence becomes dynamic rather than static. The combined PSO-IBF algorithm is assessed on a typical power generation plants consists of a hydroelectric power plant and an equivalent thermal power plant with a time slot of six 12-hour intervals and simulated using the MATLAB software. The simulation result shows that the combined PSO-IBF algorithm yields minimum cost value and optimal convergence rate than the existing algorithms.

Dry Cooling in Solar Thermal Power Plants

2011 ◽  
Author(s):  
Jaya Goswami
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Large Scale ◽  
Thermal Power ◽  
Solar Thermal ◽  
Passive Cooling ◽  
Thermal Power Plants ◽  
Solar Thermal Power ◽  
Cooling Methods ◽  
Dry Cooling

The purpose of this study is to evaluate the performance metrics of a solar thermal power plant with dry cooling and further implement a method to increase the cycle efficiency, using passive cooling techniques within the dry cooling cycle. Current methods implementing dry cooled condensation use an air-cooled condenser for heat rejection. While this reduces the water consumption of the plant, it results in performance penalties in the overall plant between 5–10% [1]. Passive cooling methods can be used to alleviate the performance penalties. While passive cooling methods have been studied and used on a small scale, this model explores the possibilities of applying these methods to large-scale solar thermal power plants. Based on the model developed, it was found that underground-cooling techniques can improve the performance of the overall dry cooled solar thermal power plant by up to 3% at peak dry bulb temperatures. This study finds that there is a possibility to apply these passive cooling techniques on a large scale to yield positive results.

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