Chemical conditioning and monitoring to control and minimize chemistry-related damages in Heller dry cooled combined cycle power plants

2017 ◽  
Vol 64 (2) ◽  
pp. 188-208 ◽  
Author(s):  
Omid Pourali ◽  
Hashem Ghasemi Kadijani ◽  
Farideh Mohammadi Khangheshlaghi
Keyword(s):  
Power Plants ◽  
Water Cycle ◽  
Research Work ◽  
Cooling Water ◽  
Quality Parameters ◽  
Combined Cycle ◽  
Content Type ◽  
Iron Aluminum ◽  
Sampling Points ◽  
Standards And Guidelines

Purpose An effective chemical conditioning technique was successfully tested and investigated to control and minimize the chemistry-related damages within mixed metallurgy steam and water cycle of Heller dry cooled combined cycle power plants (CCPPs), in which cooling water and condensate are completely mixed in direct contact condenser. This study aims to perform a comprehensive experimental research in four mixed metallurgy steam and water cycle. Design/methodology/approach A comprehensive experimental study was carried out in four mixed metallurgy steam and water cycle fabricated with ferrous- and aluminum-based alloys which have various corrosion resistance capabilities in contact with water. Chemical conditioning was conducted using both volatile and non-volatile alkalizing agents, and, to perform chemical conditioning effectively, quality parameters (pH, conductivity, dissolved oxygen, sodium, silica, iron, aluminum and phosphate) were monitored by analyzing grab and online samples taken at eight key sampling points. Findings Results indicated that pH was the most critical parameter which was not mainly within the recommended ranges of widely used standards and guidelines at all key sampling points that generally increases the occurrence of chemistry-related damages. The other quality parameters were mostly satisfactory. Originality/value In this research, the development of a suitable chemical conditioning technique in mixed metallurgy steam and water cycle, fabricated with ferrous and aluminum-based alloys, was studied. The obtained results in this thorough research work was evaluated by comparison with the chemistry limits of the widely used standards and guidelines, and combined use of volatile and solid alkalizing agents was considered as a promising chemical conditioning technique for utilization in mixed metallurgy units of Heller dry cooled CCPPs.

“Building as machine”: mental image of combined cycle power plants workers

Facilities ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Rezaee ◽  
Seyed Rahman Eghbali
Keyword(s):  
Data Collection ◽  
Power Plants ◽  
Thermal Power ◽  
Mental Image ◽  
Careful Analysis ◽  
Combined Cycle ◽  
Collection Method ◽  
Content Type ◽  
Environmental Threats ◽  
Data Collection Method

Purpose This paper aims to interpret the workers’ perception of combined cycle power plants through visual qualities. Design/methodology/approach In this qualitative research landscape image, the sketching technique is applied as a data collection method to extract participants’ mental images by asking them to draw sketches. The resulted sketches besides obtained verbal and written data were analyzed and coded in three stages to explain the workers’ perception. Visual qualities were studied as a mean which made it possible to interpret the workers’ perception of their workplace. Findings Careful analysis of the gathered data and the emerged concepts via open coding identify four axial categories of the concepts forming the workers’ perception of the power plants: “inconsistency with nature,” “emphasis on function and product,” “health and environmental threats” and “interpretation of the built form as a mass instead of space.” These four categories support the core category of the proposed theory which is “perceiving building as the machine.” This phrase explains how workers perceive power plants as machines, not as supportive and lively environments. This is followed by consequences, “precedence of building over human” is prominent among them. Originality/value In the relevant body of literature, visual impact and visual perception of conventional thermal power plants are largely missed, as well as visual relation to environment focusing on a single building or groups of adjacent buildings. This paper covers both areas via asking for sketches as a data collection method, in addition, to interview the participants to clarify their mental image of the work environment.

Large-scale economic load dispatch using squirrel search algorithm

2020 ◽  
Vol 14 (6) ◽  
pp. 1351-1380
Author(s):  
Sakthivel V.P. ◽  
Suman M. ◽  
Sathya P.D.
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Research Work ◽  
Superior Performance ◽  
Economic Load Dispatch ◽  
Fuel Cost ◽  
Content Type

Purpose Economic load dispatch (ELD) is one of the crucial optimization problems in power system planning and operation. The ELD problem with valve point loading (VPL) and multi-fuel options (MFO) is defined as a non-smooth and non-convex optimization problem with equality and inequality constraints, which obliges an efficient heuristic strategy to be addressed. The purpose of this study is to present a new and powerful heuristic optimization technique (HOT) named as squirrel search algorithm (SSA) to solve non-convex ELD problems of large-scale power plants. Design/methodology/approach The suggested SSA approach is aimed to minimize the total fuel cost consumption of power plant considering their generation values as decision variables while satisfying the problem constraints. It confers a solution to the ELD issue by anchoring with foraging behavior of squirrels based on the dynamic jumping and gliding strategies. Furthermore, a heuristic approach and selection rules are used in SSA to handle the constraints appropriately. Findings Empirical results authenticate the superior performance of SSA technique by validating on four different large-scale systems. Comparing SSA with other HOTs, numerical results depict its proficiencies with high-qualitative solution and by its excellent computational efficiency to solve the ELD problems with non-smooth fuel cost function addressing the VPL and MFO. Moreover, the non-parametric tests prove the robustness and efficacy of the suggested SSA and demonstrate that it can be used as a competent optimizer for solving the real-world large-scale non-convex ELD problems. Practical implications This study has compared various HOTs to determine optimal generation scheduling for large-scale ELD problems. Consequently, its comparative analysis will be beneficial to power engineers for accurate generation planning. Originality/value To the best of the authors’ knowledge, this manuscript is the first research work of using SSA approach for solving ELD problems. Consequently, the solution to this problem configures the key contribution of this paper.

Effect of can-storage parameters of finisher drawframe on combed ring spun yarn quality

2019 ◽  
Vol 23 (2) ◽  
pp. 153-167
Author(s):  
Sukhvir Singh ◽  
Niranjan Bhowmick ◽  
Anand Vaz
Keyword(s):  
Storage Time ◽  
Statistical Significance ◽  
Research Work ◽  
Quality Parameters ◽  
Vital Role ◽  
Spring Stiffness ◽  
Content Type ◽  
Yarn Quality ◽  
Spun Yarn ◽  
Ring Spun Yarn

Purpose The present work is a systematic study to understand the cause of poor quality of sliver, roving and yarn due to defective sliver storage can-spring at finisher drawframe machine in spinning preparatory. This study aims to investigate the influence of can-spring stiffness factor, sliver deposition rate and sliver coils position on yarn unevenness and thin places considering two cases of sliver storage time. Design/methodology/approach Combed ring spun yarn samples were produced by varying finisher drawframe variables, which were can-spring stiffness, delivery speed and sliver coils position in storage can. For research design, three-factor three levels of Box-Behnken experimental design was adopted. To investigate the effect of sliver storage time on combed yarn unevenness and thin places, yarn samples were produced at 8 h sliver storage time and without allowing any storage time. Sliver storage time is the time for which combed drawn sliver kept idle in storage cans before feeding to speedframe machine. The 8 h sliver storage time was considered for present study after consulting industrial experts. Adequate numbers of the samples were tested for yarn quality parameters such as yarn unevenness and thin places 50 per cent/km on standard instruments. Finally, the test results were analyzed using statistical software to check the statistical significance of all the independent variables on observed response through analysis of variance. Findings The experimental results showed that the yarn samples produced from older can-springs and bottom position sliver coils stored at 8 h storage time were showing higher yarn unevenness and thin places compared to other yarn samples. The results also showed that the effect of delivery speed is not significant on yarn unevenness for samples produced without allowing any sliver storage time. Research limitations/implications The present study is an outcome of a practical problem experienced at the finisher drawframe machine in a spinning industry. For this purpose, only scrutinized finisher drawframe variables were considered for the evaluation. There are many equally important other factors, which were not considered due to research work feasibility. Social implications This paper investigates the effect of some imperative factors at the finisher drawframe stage on combed yarn quality. The present study will boost existing knowledge of the spinner’s community regarding the effect of can-spring stiffness, sliver coils position and storage time on resultant combed yarn quality parameters. Originality/value The work is original and only a few references are available. The study reveals that storage can-spring stiffness should be chosen carefully for better sliver handling. It is observed that finisher drawframe can-spring stiffness, sliver storage time and sliver coils position play a vital role in deciding quality characteristics of stored sliver and ultimately affect yarn quality.

The Palo Verde Water Cycle Model (PVWCM) – Development of an Integrated Multi-Physics and Economics Model for Effective Water Management

2021 ◽  
Author(s):  
Bobby D. Middleton ◽  
Patrick V. Brady ◽  
Jeffrey A. Brown ◽  
Serafina T. Lawles
Keyword(s):  
Water Management ◽  
Water Resources ◽  
Sonoran Desert ◽  
Power Plants ◽  
Water Cycle ◽  
Cooling Water ◽  
Software Tool ◽  
Cycle Model ◽  
The Us ◽  
Water Strategy

Abstract Water management has become critical for thermoelectric power generation in the US. Increasing demand for scarce water resources for domestic, agricultural, and industrial use affects water availability for power plants. In particular, the population in the Southwestern part of the US is growing and water resources are over-stressed. The engineering and management teams at the Palo Verde Generating Station (PV) in the Sonoran Desert have long understood this problem and began a partnership with Sandia National Laboratories in 2017 to develop a long-term water strategy for PV. As part of this program, Sandia and Palo Verde staff have developed a comprehensive software tool that models all aspects of the PV (plant cooling) water cycle. The software tool — the Palo Verde Water Cycle Model (PVWCM) — tracks water operations from influent to the plant through evaporation in one of the nine cooling towers or one of the eight evaporation ponds. The PVWCM has been developed using a process called System Dynamics. The PVWCM is developed to allow scenario comparison for various plant operating strategies.

scholarly journals Electrical Power Prediction through a Combination of Multilayer Perceptron with Water Cycle Ant Lion and Satin Bowerbird Searching Optimizers

2021 ◽  
Vol 13 (4) ◽  
pp. 2336
Author(s):  
Hossein Moayedi ◽  
Amir Mosavi
Keyword(s):  
Power Plants ◽  
Water Cycle ◽  
Electrical Power ◽  
Optimal Solution ◽  
Population Based ◽  
Influential Factors ◽  
Combined Cycle ◽  
Power Prediction ◽  
Satin Bowerbird ◽  
Ant Lion

Predicting the electrical power (PE) output is a significant step toward the sustainable development of combined cycle power plants. Due to the effect of several parameters on the simulation of PE, utilizing a robust method is of high importance. Hence, in this study, a potent metaheuristic strategy, namely, the water cycle algorithm (WCA), is employed to solve this issue. First, a nonlinear neural network framework is formed to link the PE with influential parameters. Then, the network is optimized by the WCA algorithm. A publicly available dataset is used to feed the hybrid model. Since the WCA is a population-based technique, its sensitivity to the population size is assessed by a trial-and-error effort to attain the most suitable configuration. The results in the training phase showed that the proposed WCA can find an optimal solution for capturing the relationship between the PE and influential factors with less than 1% error. Likewise, examining the test results revealed that this model can forecast the PE with high accuracy. Moreover, a comparison with two powerful benchmark techniques, namely, ant lion optimization and a satin bowerbird optimizer, pointed to the WCA as a more accurate technique for the sustainable design of the intended system. Lastly, two potential predictive formulas, based on the most efficient WCAs, are extracted and presented.

Modeling of integrated solar combined cycle power plant (ISCC) of Hassi R'mel, Algeria

2019 ◽  
Vol 14 (3) ◽  
pp. 505-526 ◽  
Author(s):  
Nedjma Abdelhafidi ◽  
Nour El Islam Bachari ◽  
Zohra Abdelhafidi ◽  
Ali Cheknane ◽  
Abdelmotaleb Mokhnache ◽  
...  
Keyword(s):  
Power Plant ◽  
Solar Energy ◽  
Power Plants ◽  
Meteorological Data ◽  
Combined Cycle ◽  
Plant Responses ◽  
Content Type ◽  
Low Wind Speed ◽  
Gas Power Plant ◽  
Solar Electricity

Purpose Integrated solar combined cycle (ISCC) using parabolic trough collector (PTC) technology is a new power plant that has been installed in few countries to benefit from the use of hybrid solar-gas systems. The purpose of this paper is to investigate the challenges in modeling the thermal output of the hybrid solar-gas power plant and to analyze the factors that influence them. Design/methodology/approach To validate the proposal, a study was conducted on a test stand in situ and based on the statistical analysis of meteorological data of the year 2017. Such data have been brought from Abener hybrid solar-gas central of Hassi R’mel and used as an input of our model. Findings The proposal made by the authors has been simulated using MATLAB environment. The simulation results show that the net solar electricity reaches 18 per cent in June, 15 per cent in March and September, while it cannot exceed 8 per cent in December. Moreover, it shows that the power plant responses sensibly to solar energy, where the electricity output increases accordingly to the solar radiation increase. This increase in efficiency results in better economic utilization of the solar PTC equipment in such kind of hybrid solar-gas power plant. Practical implications The obtained results would be expected to provide the possibility for designing other power plants in Algeria when such conditions are met (high DNI, low wind speed, water and natural-gas availability). Originality/value This paper presents a new model able to predict the thermal solar energy and the net solar-electricity efficiency of such kind solar hybrid power plant.

Estimation of operational efficiency and its determinants using DEA

2013 ◽  
Vol 7 (4) ◽  
pp. 409-429 ◽  
Author(s):  
Sudhir Kumar Singh ◽  
Vijay Kumar Bajpai
Keyword(s):  
Sensitivity Analysis ◽  
Power Plant ◽  
Regression Model ◽  
Power Plants ◽  
Research Work ◽  
Regression Result ◽  
Truncated Regression ◽  
Specific Knowledge ◽  
Content Type

Purpose – The purpose of this study is to benchmark the performance of state-owned coal-fired power plants (CFPPs) and test whether plant-specific knowledge in terms of quality of coal, size, age and make of plant contribute to an improvement in plant efficiency. Design/methodology/approach – The methodology that is utilized in the study follows a nonparametric approach of data envelopment analysis (DEA) with sensitivity analysis and Tobit regression model. The input-oriented DEA models are applied to evaluate the overall, pure technical and scale efficiencies of the CFPPs. Further, slack analysis is conducted to identify modes to improve the efficiency of the inefficient plants. Sensitivity analysis based on peer count and the removal of variables is carried out to identify the benchmark power plant. Through Tobit and bootstrap-truncated regression model, the paper investigates whether a plant's specific knowledge influences its efficiency. Findings – The DEA analysis demonstrates that nine plants are technically purely efficient.The slack analysis reveals that reducing the consumption of oil is the most effective way to improve the efficiency of inefficient plants. Mattur plant is the benchmark for most of the inefficient plants. Regression result suggests that quality of coal and size of plant significantly affect the inefficiency of the sample plants. Bharat Heavy Electrical Limited MAKE plant achieved higher efficiency in comparison to mixed MAKE. Originality/value – This study is one of the few published studies that benchmark the performance of state-owned CFPPs. This research carried out taking some new uncontrollable parameters of power plant utilities of India. Research work also identifies the possible causes of inefficiency and provides measures to improve the efficiency of the inefficient power plant.

New way of learning in the nuclear industry: space simulation as a tool for vocational knowledge and work practices acquisition

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Raluca Ciobanu
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Qualitative Methodology ◽  
Service Providers ◽  
Research Work ◽  
Real Life ◽  
Training System ◽  
Nuclear Industry ◽  
Content Type ◽  
Effectiveness Of Training

Purpose This study aims to contribute to the project to overhaul Common Training for Nuclear Workers (Commune Intervenant du Nucléaire – CIN) aimed at service providers involved in maintenance on nuclear power plants (NPPs). Design/methodology/approach The study is devised as a methodology for designing and assessing a training system (work operation scenarios and steering method) and draws on a qualitative methodology through group interviews and observations during situational training. More specifically, the aim is to devise a training system that would enable trainees to gain a better understanding of activity in the nuclear sector, its execution, its challenges and its requirements, and to make them able to think and act individually and collectively to contend with the various types of work situations. Findings The results of this study confirm the relevance of providing different pedagogical orientations that emphasise the activity over the previous task-oriented and top-down approach. The instructors–trainees and trainees–trainees interactions take place in an open and dynamic space with an important interindividual variability to promote active learning that is based on the joint discovery and analysis of real work by the collective. In this context, the co-presence of the participants is more important than the task at stake. Moreover, this new way of learning is a challenge for the instructors and trainees, as well as for training designers. Practical implications Moreover, this new way of learning is a challenge for the instructors and trainees, as well as for training designers, and has to be taken into consideration when designing training programs. Originality/value This operational research work is being conducted by researchers, as well as industry professionals, and enjoys special access to the constrained environment of NPPs. Several studies conducted by the Organisational and Human Factors team of EDF Research and Development (Couix and Boccara, 2015; Fucks and Boccara, 2014) have focused on the effectiveness of training. In particular, they found that to be effective, training must faithfully reflect the real-life work situations of the future environment in which the worker trainees will be active.

Design for Integration of a Compact Waste Energy Recovery System for Automobile Engine Exhaust Gas and Coolant

2014 ◽  
Author(s):  
Mohammed S. Mayeed ◽  
S. Mostafa Ghiaasiaan ◽  
Thuyen Luong ◽  
Erhan Ilksoy
Keyword(s):  
Energy Recovery ◽  
Power Plants ◽  
Materials Science ◽  
Cooling Water ◽  
Combined Cycle ◽  
Operating Conditions ◽  
Exhaust Gas ◽  
Kalina Cycle ◽  
Temperature Range ◽  
Waste Energy

In this study, key components of combined cycles designed for waste energy recovery from automobile engines have been virtually designed for being light weight, small sized without compromising strengths, and based on integration with the existing components of an automobile. Originally a simulation was performed to examine the amount of waste energy that could be recovered and the consequential increase in the overall thermal efficiency through the use of Kalina, ethanol and steam cycles using Engineering Equation Solver software under typical engine operating conditions. It was found that steam cycle was better for recovering energy from the exhaust gas at the higher temperature range (689 C to 160 C) and Kalina cycle was better for recovering energy from the exhaust gas and the cooling water at the lower temperature range (122 C to 80 C) among the three cycles. It was found that using this combination of cycles about 5 kW of power could be extracted from the wasted energy. The next thing was to determine the amount of space, weight and design to incorporate a system of cycles like this with an automobile. The combined cycle generation, a process widely used in existing power plants, has become a viable option for automotive applications due to advances in materials science, nanotechnology, and MEMS (Micro-Electro Mechanical Systems) devices. Critical components of the best performing cycles have been designed using computer aided engineering for the minimization of weight and space, and integration with the typical components of an automobile.

scholarly journals Análisis térmico de una planta de potencia de ciclo combinado utilizando enfriamiento de aire a la entrada

2020 ◽  
pp. 15-20
Author(s):  
Edzel Jair Casados-López ◽  
Raúl Cruz-Vicencio ◽  
Álvaro Casados-Sánchez ◽  
Álvaro Horst-Sánche
Keyword(s):  
Air Temperature ◽  
Power Plants ◽  
Research Work ◽  
Combined Cycle ◽  
Plant Performance ◽  
Air Cooling ◽  
Refrigeration System ◽  
Power Station ◽  
Compressor Inlet ◽  
Combined Cycle Plant

In this article, a combined cycle power station (gas-steam) is analyzed, considering air cooling before entering the compressor. Currently what is sought are higher thermal efficiencies, which is why the combined cycle power plants have been chosen, since they make better use of the fuel, producing greater net power, all of which have led to innovative modifications in the combined cycle power plants, improving the performance of this. In this research work, a 243 MW combined cycle plant is taken as the base, whose air temperature when entering the compressor is 32 ° C. Knowing in advance that one of the factors that affects the operation of this plant is the condition of the air when entering the compressor, which when it cools will increase its density and with it its mass flow, obtaining an increase in the power of the gas turbine. In view of this, this work proposes that through the use of a mechanical refrigeration system, air cooling to 15 °C is carried out at the compressor inlet and with this achieve an increase in plant performance.

Sign in / Sign up

Export Citation Format

Share Document