13 research outputs found
A methodology to determine best-suited waiting-time periods for turbine start-up under fluctuating resources
No full text— It is not uncommon for engineering process
plants to comprise energy recovery. When power generation
takes place under such circumstances, the nature of
interlinked processes may result in fluctuating resource
availability. Such fluctuations may, however, result in
turbines tripping due to insufficient availability at times.
Power generation under such conditions typically comprises
turbine protection measurements in an attempt to prevent
unnecessary trip occurrences. One such measurement is to
avoid a possible restart-trip scenario in close proximity, by
enforcing adequate start-up constraints. These constraints
dictate the minimum waiting-time period that needs to be
enforced, where resource availability is sufficient to keep
the turbine(s) operational.
Start-up protection measurements are typically enforced
without changing the time-constraint over time. Although
such a measurement is required it entails time intervals
where potential power generation goes to waste due to a
turbine’s non-operational status. As the enforced waitingtime period increases more power generation potential goes
to waste; however, reduced periods may result in turbines
being restarted, only to trip in near future. A trip does not
only necessitate another waiting-time period, but reduces a
turbine’s life expectancy.
This paper presents two models; the first maximises power
generation amongst two turbines where waiting-time periods
are incorporated as a variable. These results can then be
used in combination of the second proposed model.
The second model is a unique methodology that can be used
to investigate the effect of turbine start-up waiting-time
periods and how it influences the combination of power
generation and turbine trips. This methodology is,
furthermore, incorporated to determine what the ideal startup period should be for an energy recovery plant that
operates under fluctuating resource availability.
A case study is presented that demonstrates the working
ability of the proposed method and results show that by
incorporating this methodology the engineering plant can
generate an additional 0.46 MW per annu
Simulation of a predominantly passive natural air cooling system
No full textClimate control is an everyday challenge. With the rapid surge in electricity prices over the past few years, air conditioning operating expenses necessarily increased. The effects, furthermore, of global warming result in increased cooling, and therefore, energy demand. The purpose of this paper is to propose two models that simulate a natural air cooling system. The first model simulates cooling through an earth to air heat exchanger, utilising the soil as a heat sink. The second model simulates the transient cooling of a control volume, which receives cooled air and is open to the environment. A scale model of an earth-to-air heat exchanger system was designed, constructed and used to verify results from the proposed models. Following verification, a real-life size heat exchanger was simulated in order to cool down a room of 60 m3within one hour, using only the underground soil as a heat sink. Results showed that a room at an initial 30 °C can be cooled down to 20.5 °C with a 1.2 m underground heat exchanger and down to 17.8 °C if the length is increased to 2.0 m. Only fan power is needed to increase the air's dynamic pressure, resulting in flow conditions. As a result a coefficient of performance between 60 and 80 can be achieve
Implementing an optimisation model for turbine investment selection under fluctuating steam productions
No full textEngineering plants typically have a variety of interlinked production chains, where process flows are dependent on upstream or downstream events. Raw material feeds may fluctuate over time, resulting in fluctuating off-gas and steam productions, and therefore an inefficient energy resource usage. It is common practice to generate steam from burnable offgases, in boiler houses, where excess steam is allocated for power generation after plant usages. Over time fluctuating steam flow may result in turbine trips. A problem is that unused off-gases are flared where the energy potential goes to waste. This paper investigates turbine investment choices under fluctuating steam productions. A mathematical model is used that determines how steam should be distributed between turbines in a fluctuating environment, for optimal power generation. Investment options can be explored regarding which combination of turbines will result in higher power generation for the same combined power generation capabilities and how each turbine configuration will influence the total number of turbine trips due to steam shortages. A number of simulations are performed for various turbine configurations and it was found that an increase in the number of turbines for a fixed maximum total power generation capacity will deliver slightly higher power generation but significant more turbine trips. All simulations are based on real world dat
A control algorithm approach for optimizing energy resources through power generation for a South African steel works plant
No full textNumerous engineering plants have varieties of processes, where individual process flows are dependent on previous processes and operated by default or manual settings. Initial raw material feeds may fluctuate over time, possibly resulting in inefficient use of energy resources. This paper describes a study on power generation capabilities of such a plant.
Off-gasses from various steel production processes are utilized in boilers; producing steam for the Works. Excess steam is used for power generation. The Works experienced unstable power generation, due to fluctuations in available steam. This resulted in regular turbine trips, causing power generation losses, additional gas flaring and reducing machine life expectancy.
To address this problem; off-gas and steam production data were analyzed over three months. A control approach was set up, where the algorithm’s objective was optimum power generation, for a 5MW and 30 MW turbine. Results showed potential power generation increase over 26% was possible, still not eliminating trips. The algorithm incorporated the possibility of burning natural gas in a boiler, when needed. This scenario could have led to no trips and an increased generation capacity of over 48%. Additional power generation’s financial impact overcame the high cost of utilizing natural gas for power generation purpose
The use of optimisation modelling for energy recovery investment decision making
No full textInvestment decision making is a common occurrence
for any engineering company. These investments include any
possibility from relative inexpensive to extremely costly
equipment. When power generation turbine procurements are
considered for energy recovery plants, these may typically be
viewed as expensive and long-term investments. Such an
investment cannot merely be discarded and replaced under suboptimal conditions.
If energy recovery takes place under fluctuating process flow
conditions, investment choices for power generation turbines may,
however, prove challenging to determine. Under conditions where
resource availabilities are fluctuating to such an extent that, at
times, supply outside a turbine’s operating limits are present, a
number of factors need to be considered. Such decisions typically
include questions regarding a turbine’s operating limits, efficiency,
allowable trips, procurement cost and quantity thereof.
This paper demonstrates how investment choices are influenced
through the use of an optimisation investment model. A number of
scenario simulations are shown, where results indicate not only
what turbine investment decisions need to be exercised, but also
the power generation that can be expected over time, and therefore,
the true payback period. Results are presented in the form of power
generation and the predicted net present value of possible
investments to be mad
Utilising fluctuating off-gases more efficiently in a power co-generation environment through less flaring
No full textCommon engineering practice is to generate steam from burnable off-gases, in boiler houses, where excess steam is allocated for power generation after plant requirements are met. If the quantities or chemical composition of raw material feeds are not constant, off-gases and therefore steam productions may fluctuate over time. Fluctuating steam flows may cause turbines to trip due to insufficient availability at times. All off-gases not utilised are flared to atmosphere, nullifying its energy potential.This paper investigates the effect for when the volume quantity of off-gas flaring is regulated and the improved potential that this could have on power co-generation, taking into account the maximum combined boiler houses' capacities. Although flaring must always take place for line pressure control; for the engineering works under consideration 46.9 % of all the off-gas productions were flared. A mathematical model is used that distributes steam between turbines for optimal power generation to assist with the investigation in determining the power generation capabilities of the available and potential steam flow. Significant increases in potential power generation were observed when regulated flare percentages were decrease
Investment and operational optimisation of an energy recovery engineering plant
No full textPhD (Business Mathematics), North-West University, Potchefstroom CampusBurnable off-gases generated from operational processes in engineering plants are regularly utilised as energy sources. A common practice is to use this for steam production in boiler houses, where excess steam is allocated to power generation turbines. Fluctuations in off-gas productions may, however, result in turbines shutting down, due to insuficient steam. Some investment models exist, which are typically based on cost minimisations or for the purpose of meeting energy demands. These models do not, however, take into account plant-specific steam flow patterns and typically use average-based pro les for decision making. The operational control of turbines are typically performed by means of a fixed-sequence philosophy. Turbines are loaded in a predetermined order until a fixed set point. This operational philosophy incurs signi cant power generation losses from turbine shut-downs, as a result of the inability to distribute steam dynamically. Such an operating philosophy is easy to implement and, therefore, commonly used in industry. Another philosophy is that of dynamic control where steam distribution between the turbines are computed at each time period by means of an in-time operating control algorithm. In this thesis, a number of novel model formulations are proposed, which addresses optimal power generation and turbine investments under a fixed-sequence philosophy, as well as dynamic control. Seven conceptual formulations are applied to demonstrate basic power generation optimisation. These conceptual formulations are to incorporate either a fixed-sequence philosophy, dynamic control or both. The main contributions of this study entail a further seven formulations where six are optimisation models. Each of these six formulations utilises plant signature steam flow profiles in order to determine, either optimal power generation, or optimal turbine investments in terms of the net present value (NPV), or both. All investment formulations include turbine shut-downs in the decision making process by penalising the NPV with each occurrence. The first three of these model formulations are for turbines operating under a fixed-sequence philosophy, two for optimal power generation and one for optimal turbine investments. For optimal power generation the formulations determine in which fixed order the turbines should operate. Optimal turbine investments, as determined by the third formulation, is the combination that yields the highest NPV. For this combination the optimal fixed turbine order and power generation are determined. Optimal investment results indicate that when future trip costs are taken into account as an NPV penalisation, a single turbine should rather be procured. The final three of these proposed formulations are for turbines operating under dynamic control. The first formulation optimises power generation between any number of turbines. The second formulation optimises turbine investments in terms of NPV. Comparing optimal power generation results, increases between 3.5% and 13.2% are observed for turbines under dynamic control compared to a fixed-sequence philosophy. Optimal NPV's under dynamic control are between 7.3% and 19.3% higher than those of a fixed-sequence philosophy. All optimal outcomes yield that two turbines should be procured. A formulation is proposed that optimises turbine investments, which incorporates the procurement of a supplementary energy resource to assist during low o -gas, and therefore, low steam flow periods. Such a resource is typically very expensive and does not make sense to procure under normal operating conditions. However, in a uctuating steam flow environment it proves to increase the NPV, while safeguarding turbines from shut-down occurrences. Depending on the procurement and projected shut-down costs, results indicate that an investment into a supplementary resource under optimal investments can yield an NPV improvement 10.6% to 118.0% versus a fixed-sequence philosophy, and 3.0% to 82.7% compared to dynamic control. Results further indicate that involuntary turbine shut-downs, owing to low steam flow periods, are reduced up to a 100%.Doctora
Simulation of externally fired gas turbine configurations for micro-scale biomass applications
No full textMEng (Mechanical Engineering), North-West University, Potchefstroom CampusMost rural communities in South Africa are forced to rely on alternative energy resources such as biomass, gas, liquid fuels and waste materials for the provision of energy to fulfil their lighting and cooking needs since electrification in rural areas is problematically low. Biomass as a source of renewable energy is a promising, ecological and sustainable solution for electricity generation. A micro-scale externally fired gas turbine (EFGT) fuelled by biomass provides a suitable solution for electricity generation in rural areas. The EFGT holds the advantage of being able to operate with poor quality and a variety of biomass fuels since the combustion gasses is not in direct contact with the working fluid of the cycle. The purpose of this study is to evaluate different EFGT configurations using thermal-fluid simulation models developed for micro-scale EFGT biomass applications, typically with an electricity generation capacity in the region of 5 kW that will be suitable for a small rural community. The conceptual simulation models can be used to assist farming and rural communities, who are interested and capable of implementing micro-scale generation to fulfil their basic electricity needs, to gain practical insight into different cycle configurations and its operating conditions.
Verification was done by comparing the results of the simple EFGT cycle configuration against that found in the literature of a similar biomass cycle. The comparative results were within 5% correlation. Within this study, four different system configurations of a micro-scaled EFGT cycle were modelled with different levels of complexity, but with rural applications in mind. The different cycle configurations were evaluated for different operating conditions and component efficiencies. The performance of the EFGT cycles was investigated to evaluate the effect of varying parameters such as turbine inlet temperature, mass flow of air, combustion heat and COP of the pre-cooling unit respectively. The individual models showed promising results, such as cycle efficiencies ranging from 12.58% for the simple cycle 30.07% for the heat recovery cycle with pre-cooled air.Master
CFD modelling of air flow through a finned coil heat exchanger to improve heat transfer and pressure drop predictions
No full textMEng (Mechanical Engineering), North-West University, Potchefstroom CampusIn the current study, a method of lessening computational expense and model design effort is investigated for finned coil heat exchangers (FCHXs) by using STAR-CCM+ as simulation tool. The simulation model prediction accuracy, in terms of the air side thermal-hydraulic characteristics of a staggered tube, true-to-industry (TTI) sized FCHX model, is compared to a repeatable, representative segment (RS) model of the same FCHX across a wide air flow continuum ranging between laminar to fully turbulent. The level of confidence of these models is validated based on a comparison with previous experimental data from a renowned source using the Colburn j-factor and Fanning friction factor (f-factor) as reference and illustrate a reasonable agreement. The RS model type is found to be a suitable approach, limiting computational expense compared to the TTI model, which showed a minor improvement of the heat transfer and pressure drop predictions by only 1.18% and 1.83%, respectively. In order to reduce simulation model design effort in the next phase of the study, the model prediction results of a plain fin RS model are compared to a wavy fin RS model. Wavy fin FCHXs are commonly found in industry and create a few extra design challenges for simulation purposes when compared to a plain fin FCHX. The results of a plain fin RS model is found to yield large inaccuracies compared to the wavy fin RS model and beckons the need to parametrically test the effects of geometrically modifying a plain fin RS model in order to increase model prediction accuracy. Detailed analysis of the effect on the heat transfer and pressure drop performance is done by evaluating related parameters such as the fin pitch, longitudinal tube pitch and transverse tube pitch. The increase in fin pitch is found to cause an increase in heat transfer performance (in terms of the Nusselt number) due to a substantial hydraulic diameter increase, although a decrease in the heat transfer coefficient and pressure drop is seen. A decrease in the longitudinal and transverse tube pitches causes an increase in heat transfer and pressure drop performance, whereby the effect of the transverse tube pitch is found to yield the closest results comparison in relation to the wavy fin RS model’s results. The average prediction accuracy for the entire flow range was found for the heat transfer to be predicted with an error deviation of 3.22% and pressure drop of 4.44%, which was acceptably accurate. Although the variation in transverse tube pitch proved to be acceptable for this study, more research has to be done in future to confirm this finding using a wavy fin model incorporating a variation of waviness heights (and waviness angles) and a different set of geometrical parameters before a final conclusion can be made.Master
