Browsing by Author "Gosai, Priyesh"

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    Open Access
    A modelling methodology to quantify the impact of plant anomalies on ID fan capacity in coal fired power plants
    (2020) Khobo, Rendani Yaw-Boateng Sean; Rousseau, Pieter; Gosai, Priyesh
    In South Africa, nearly 80 % of electricity is generated from coal fired power plants. Due to the complexity of the interconnected systems that make up a typical power plant, analysis of the root causes of load losses is not a straightforward process. This often leads to losses incorrectly being ascribed to the Induced Draught (ID) fan, where detection occurs, while the problem actually originates elsewhere in the plant. The focus of this study was to develop and demonstrate a modelling methodology to quantify the effects of major plant anomalies on the capacity of ID fans in coal fired power plants. The ensuing model calculates the operating point of the ID fan that is a result of anomalies experienced elsewhere in the plant. This model can be applied in conjunction with performance test data as part of a root cause analysis procedure. The model has three main sections that are integrated to determine the ID fan operating point. The first section is a water/steam cycle model that was pre-configured in VirtualPlantTM. The steam plant model was verified via energy balance calculations and validated against original heat balance diagrams. The second is a draught group model developed using FlownexSETM. This onedimensional network is a simplification of the flue gas side of the five main draught group components, from the furnace inlet to the chimney exit, characterising only the aggregate heat transfer and pressure loss in the system. The designated ID fan model is based on the original fan performance curves. The third section is a Boiler Mass and Energy Balance (BMEB) specifically created for this purpose to: (1) translate the VirtualPlant results for the steam cycle into applicable boundary conditions for the Flownex draught group model; and (2) to calculate the fluid properties applicable to the draught group based on the coal characteristics and combustion process. The integrated modelling methodology was applied to a 600 MW class coal fired power plant to investigate the impact of six major anomalies that are typically encountered. These are: changes in coal quality; increased boiler flue gas exit temperatures; air ingress into the boiler; air heater inleakage to the flue gas stream; feed water heaters out-of-service; and condenser backpressure degradation. It was inter alia found that a low calorific value (CV) coal of 14 MJ/kg compared to a typical 17 MJ/kg reduced the fan's capacity by 2.1 %. Also, having both HP FWH out of service decreased the fan's capacity by 16.2 %.
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    Open Access
    Online boiler convective heat exchanger monitoring: a comparison of soft sensing and data-driven approaches
    (2018) Prinsloo, Gerto; Rousseau, Pieter; Gosai, Priyesh
    Online monitoring supports plant reliability and performance management by providing real time information about the condition of equipment. However, the intricate geometries and harsh operating environment of coal fired power plant boilers inhibit the ability to do online measurements of all process related variables. A low-cost alternative lies in the possibility of using knowledge about boiler operation to extract information about its condition from standard online process measurements. This approach is evaluated with the aim of enhancing online condition monitoring of a boiler’s convective pass heat exchanger network by respectively using a soft sensor and a data-driven method. The soft sensor approach is based on a one-dimensional thermofluid process model which takes measurements as inputs and calculates unmeasured variables as outputs. The model is calibrated based on design information. The data-driven method is one developed specifically in this study to identify unique fault signatures in measurement data to detect and quantify changes in unmeasured variables. The fault signatures are initially constructed using the calibrated one-dimensional thermofluid process model. The benefits and limitations of these methods are compared at the hand of a case study boiler. The case study boiler has five convective heat exchanger stages, each composed of four separate legs. The data-driven method estimates the average conduction thermal resistance of individual heat exchanger legs and the flue gas temperature at the inlet to the convective pass. In addition to this, the soft sensor estimates the average fluid variables for individual legs throughout the convective pass and therefore provides information better suited for condition prognosis. The methods are tested using real plant measurements recorded during a period which contained load changes and on-load heat exchanger cleaning events. The cleaning event provides some basis for validating the results because the qualitative changes of some unmeasured monitored variables expected during this event are known. The relative changes detected by both methods are closely correlated. The data-driven method is computationally less expensive and easily implementable across different software platforms once the fault signatures have been obtained. Fault signatures are easily trainable once the model has been developed. The soft sensors require the continuous use of the modelling software and will therefore be subject to licencing constraints. Both methods offer the possibility to enhance the monitoring resolution of modern boilers without the need to install any additional measurements. Implementation of these monitoring frameworks can provide a simple and low-cost contribution to optimized boiler performance and reliability management.
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    Open Access
    Viability assessment of enhancing dry cooling systems using thermal storage ponds
    (2014) Gosai, Priyesh; Malan, A G; Pretorius, J P
    Dry cooled systems are employed to reject heat in modern power plants. Unfortunately, these cooling systems become less effective under windy conditions and when ambient temperatures are high. One proposed solution to this problem is to augment the cooling capacity of the dry cooled system by means of utilizing evaporative cooling ponds which can be operated in parallel during adverse ambient conditions. This study investigates a concept for a South African power station. The system utilises waste-water from evaporation ponds which will supply a surface condenser connected in parallel to the dry cooled system. The development of this system requires an accurate model to predict the transient thermal response of the pond. No such pond model is available in open literature due to the pond under consideration having a unique size as well as size to depth ratio. Various heat transfer modes are numerically modelled for large evaporation ponds, including free surface evaporation which is a transient and complex phenomenon. Evaporation at the surface is the primary heat and only mass transfer driver. The modified Ryan equation proposed by an experimentally validated study was used to estimate evaporation on the surface. Convection is modelled using a correlation that was derived and experimentally tested for applications in the natural environment. Heat transfer via conduction to the ground is solved using a one dimensional finite difference solution to the heat conduction equation, and radiation is modelled using widely accepted correlations. These correlations were coupled and implemented into a computer model using C++. Through numerical analysis the relevance and accuracy of each transfer mode was rigorously analysed. Once validated, the intended loading conditions at the power station were imposed onto the pond model in order to assess its cooling viability. It is concluded that the pond not only poses a sustainable and environmentally neutral cooling augmentation device, but is also cost effective.