OPERATIONAL PLANNING IN COMBINED HEAT AND POWER SYSTEMS

This dissertation presents methodologies for operational planning in Combined Heat and Power (CHP) systems. The subject of experimentation is the University of Massachusetts CHP system, which is a 22 MWe/640 MBh system for a district energy application. Systems like this have complex energy flow networks due to multiple interconnected thermodynamic components like gas and steam turbines, boilers and heat recovery steam generators and also interconnection with centralized electric grids. In district energy applications, heat and power requirements vary over 24 hour periods (planning horizon) due to changing weather conditions, time-of-day factors and consumer requirements. System thermal performance is highly dependent on ambient temperature and operating load, because component performances are nonlinear functions of these parameters. Electric grid charges are much higher for on-peak than off-peak periods, on-site fuel choices vary in prices and cheaper fuels are available only in limited quantities. In order to operate such systems in energy efficient, cost effective and least polluting ways, optimal scheduling strategies need to be developed. For such problems, Mixed-Integer Nonlinear Programming (MINLP) formulations are proposed. Three problem formulations are of interest; energy optimization, cost optimization and emission optimization. Energy optimization reduces system fuel input based on component nonlinear efficiency characteristics. Cost optimization addresses price fluctuations between grid on-peak and off-peak periods and differences in on-site fuel prices. Emission optimization considers CO2 emission levels caused by direct utilization of fossil fuels on-site and indirect utilization when importing electricity from the grid. Three solution techniques are employed; a deterministic algorithm, a stochastic search and a heuristic approach. The deterministic algorithm is the classical branch-and-bound method. Numerical experimentation shows that as planning horizon size increases linearly, computer processing time for branch-and-bound increases exponentially. Also in the problem formulation, fuel availability limitations lead to nonlinear constraints for which branch-and-bound in unable to find integer solutions. A genetic algorithm is proposed in which genetic search is applied only on integer variables and gradient search is applied on continuous variables. This hybrid genetic algorithm finds more optimal solutions than branch-and-bound within reasonable computer processing time. The heuristic approach fixes integer values over the planning horizon based on constraint satisfaction. It then uses gradient search to find optimum continuous variable values. The heuristic approach finds more optimal solutions than the proposed genetic algorithm and requires very little computer processing time. A numerical study using actual system operation data shows optimal scheduling can improve system efficiency by 6%, reduce cost by 11% and emission by 14%

Operational Risk Assessment of Routing Flare Gas to Boiler for Cogeneration

Flaring is a controlled combustion process in which unwanted or excess hydrocarbon gases are released to flare stack for disposal. Flaring has a significant impact on environment, energy and economy. Flare gas integration to cogeneration plant is an alternative to mitigate flaring, benefiting from utilizing waste flare gas as a supplemental fuel to boilers and or gas turbines. Earlier studies have shown the energy and economic sustainability through integration. However, the impact of flare gas quality on cogeneration plants are yet to be identified. This paper studies the effect of flare gas composition and temperature from an ethylene plant to an existing boiler during abnormal flaring. The study proposes a unique framework which identifies the process hazards associated with variation in fuel conditions through process simulation and sensitivity analysis. Then, a systematic approach is used to evaluate the critical operational event occurrences and their impacts through scenario development and quantitative risk assessment, comparing a base case natural gas fuel with a variable flare gas fuel. An important outcome from this study is the identification of critical fuel stream parameters affecting the fired boiler operation through process simulation. Flare stream temperature and presence of higher molecular weight hydrocarbons in flare streams showed minimal effect on boiler condition. However, hydrogen content and rich fuel-air ratio in the boiler can affect the boiler operating conditions. Increase in the hydrogen content in flare to fuel system can increase the risk contour of cogeneration plant, affecting the boiler gas temperature, combustion mixture and flame stability inside the firebox. Quantitative risk analysis through Bayesian Network showed a significant risk escalation. With 12 hours of flare gas frequency per year, there is a substantial rise in the probability of occurrence of boiler gas temperature exceeding design limit and rich fuel mixture in the firebox due to medium and high hydrogen content gas in flare. The influence of these events on flame impingement and tube rupture incidents are noteworthy for high hydrogen content gas. The study also observed reduction in operational time as the hydrogen content in flare gas is increased from low to high. Finally, to operate fire tube steam boiler with flare gas containing higher amount of hydrogen, the existing cogeneration system needs to update its preventive safeguards to reduce the probability of loss control event

Operational Risk Assessment of Routing Flare Gas to Boiler for Cogeneration

Flaring is a controlled combustion process in which unwanted or excess hydrocarbon gases are released to flare stack for disposal. Flaring has a significant impact on environment, energy and economy. Flare gas integration to cogeneration plant is an alternative to mitigate flaring, benefiting from utilizing waste flare gas as a supplemental fuel to boilers and or gas turbines. Earlier studies have shown the energy and economic sustainability through integration. However, the impact of flare gas quality on cogeneration plants are yet to be identified. This paper studies the effect of flare gas composition and temperature from an ethylene plant to an existing boiler during abnormal flaring. The study proposes a unique framework which identifies the process hazards associated with variation in fuel conditions through process simulation and sensitivity analysis. Then, a systematic approach is used to evaluate the critical operational event occurrences and their impacts through scenario development and quantitative risk assessment, comparing a base case natural gas fuel with a variable flare gas fuel. An important outcome from this study is the identification of critical fuel stream parameters affecting the fired boiler operation through process simulation. Flare stream temperature and presence of higher molecular weight hydrocarbons in flare streams showed minimal effect on boiler condition. However, hydrogen content and rich fuel-air ratio in the boiler can affect the boiler operating conditions. Increase in the hydrogen content in flare to fuel system can increase the risk contour of cogeneration plant, affecting the boiler gas temperature, combustion mixture and flame stability inside the firebox. Quantitative risk analysis through Bayesian Network showed a significant risk escalation. With 12 hours of flare gas frequency per year, there is a substantial rise in the probability of occurrence of boiler gas temperature exceeding design limit and rich fuel mixture in the firebox due to medium and high hydrogen content gas in flare. The influence of these events on flame impingement and tube rupture incidents are noteworthy for high hydrogen content gas. The study also observed reduction in operational time as the hydrogen content in flare gas is increased from low to high. Finally, to operate fire tube steam boiler with flare gas containing higher amount of hydrogen, the existing cogeneration system needs to update its preventive safeguards to reduce the probability of loss control event

A performance analysis of solar chimney thermal power systems

The objective of this study was to evaluate the solar chimney performance theoretically (techno-economic). A mathematical model was developed to estimate the following parameter: Power output, Pressure drop across the turbine, the max chimney height, Airflow temperature, and the overall efficiency of solar chimney. The mathematical model was validated with experimental data from the prototype in Manzanares power. It can be concluded that the differential pressure of collector-chimney transition section in the system, is increase with the increase of solar radiation intensity. The specific system costs are between 2000 Eur/kW and 5000 Eur/kW depending on the system size, system concept and storage size. Hence, a 50 MWe solar thermal power plant will cost 100-250 Eur million. At very good sites, today’s solar thermal power plants can generate electricity in the range of 0.15 Eur/kWh, and series production could soon bring down these costs below 0.10 Eur /kWh

parameters identification for scroll expander semi empirical model by using genetic algorithm

Abstract In this paper a small Organic Rankine Cycle (ORC) plant was tested under different operating conditions and by using refrigerants (R245fa) as working fluids. In particular, attention was posed towards the scroll expander of the power plant in order to identify experimental parameters to use in its predictive semi-empirical model. Experimental results obtained by imposing different operating conditions at the expander inlet section (i.e. temperature, pressure, mass flow rate) and different temperature at the condensation section, were used to validate the mathematical model. An in-house code (MatLab®/Scilab® based) using CoolProp® library for the accurate evaluation of fluid properties, was optimized by using a genetic algorithm implemented in modeFrontier® software. Thus, the validated model was used in predictive mode to evaluate the machine performances

Computational Fluid Dynamics Simulations

Fluid flows are encountered in our daily life as well as in engineering industries. Identifying the temporal and spatial distribution of fluid dynamic properties is essential in analyzing the processes related to flows. These properties, such as velocity, turbulence, temperature, pressure, and concentration, play important roles in mass transfer, heat transfer, reaction rate, and force analysis. However, obtaining the analytical solution of these fluid property distributions is technically difficult or impossible. With the technique of finite difference methods or finite element methods, attaining numerical solutions from the partial differential equations of mass, momentum, and energy have become achievable. Therefore, computational fluid dynamics (CFD) has emerged and been widely applied in various fields. This book collects the recent studies that have applied the CFD technique in analyzing several representative processes covering mechanical engineering, chemical engineering, environmental engineering, and thermal engineering

Sustainable Design of Industrial Energy Supply Systems - Development of a model-based decision support framework

Energy and media supply systems and related infrastructure at industrial sites have grown historically and is largely dependent on the use of fossil fuels. High fuel prices and the emission reduction targets of companies challenge existing supply concepts. Supply concepts usually remain in place for decades due to the long-lived nature of generation technologies and distribution systems. Today's investment decisions are therefore confronted with a changing environment in which the share of volatile renewables from solar and wind is continuously increasing. The long planning horizons make design decisions very complex. Optimization-based design approaches automatically derive cost- or carbon-optimal selections of generation technologies and procurement tariffs. Thus, they enable faster and more accurate planning decisions in techno-economic feasibility studies. In this work, a novel optimization model for techno-economic feasibility studies in industrial sites is developed. The optimization model uses a generic technology formulation with base classes, which takes into account the large variety of technologies and procurement tariffs at industrial sites. The optimization model also includes two reserve concepts: an operating reserve concept for short-term disruptions and a redundancy concept for long-term plant failures. The two concepts ensure security of supply for production-related energy requirements and thereby contributes to avoidance of costly production outages. The optimization model is integrated into an optimization framework to effectively calculate decarbonization strategies. The framework uses time series aggregation and heuristic decomposition techniques. Time series aggregation is performed by an integer program and results in a robust selection of representative days. The selection of representative days is used in a multi-year planning model to derive transformation roadmaps. Transformation roadmaps analyze the evolution of energy supply systems to long-term trends and consider adaptive investment decisions. A transformation strategy with myopic foresight (MYOP) solves the multi-year planning problem sequentially and is solved up to 98 % faster than a transformation approach with perfect foresight (PERF). The high uncertainties in early planning phases and the resulting need for detailed sensitivity analysis make this approach the preferred choice for many feasibility studies. The newly developed optimization framework is used in numerous research and consulting projects for urban districts, microgrids and factories. In this work, the capabilities of the framework are demonstrated for three use cases (automotive, pharmaceutical, dairy) of factory sites in southern Germany. In the use cases, decarbonization strategies for electricity, steam, heating and cooling supply are analyzed. Simulation evaluations identify changing operating patterns of combined heat and power (CHP) plants along the 15-year planning horizon. In addition, electrification of heating demand leads to a significant increase of total electricity demands. The results derived with the framework provide decision makers in industrial companies a clear view of the long-term impact of their investment decisions on decarbonization strategies

Assessment of low-frequency aeroacoustic emissions of a wind turbine under rapidly changing wind conditions based on an aero-servo-elastic CFD simulation

A meteorologically challenging situation that represents a demanding control task (rotational speed, pitch and yaw) for a wind turbine is presented and its implementation in a simulation is described. A high-fidelity numerical process chain, consisting of the computational fluid dynamics (CFD) solver FLOWer, the multi-body system (MBS) software SIMPACK and the Ffowcs Williams-Hawkings code ACCO, is used. With it, the aerodynamic, servoelastic and aeroacoustic (<20 Hz) behaviour of a generic wind turbine during a meteorological event with strong and rapid changes in wind speed and direction is investigated. A precursor simulation with the meteorological model system PALM is deployed to generate realistic inflow data. The simulated strong controller response of the wind turbine and the resulting aeroelastic behaviour are analysed. Finally, the low-frequency sound emissions are evaluated and the influence of the different operating and flow parameters during the variable inflow is assessed. It is observed that the wind speed and, linked to it, the rotational speed as well as the turbulence intensity are the main influencing factors for the emitted low-frequency sound power of the wind turbine. Yawed inflow, on the other hand, has little effect unless it changes the operational mode to load reduction, resulting in a swap of the main emitter from the blades to the tower

Thermal barrier coating life prediction model development

A methodology was established to predict thermal barrier coating life in an environment simulative of that experienced by gas turbine airfoils. Specifically, work is being conducted to determine failure modes of thermal barrier coatings in the aircraft engine environment. Analytical studies coupled with appropriate physical and mechanical property determinations are being employed to derive coating life prediction model(s) on the important failure mode(s). An initial review of experimental and flight service components indicates that the predominant mode of TBC failure involves thermomechanical spallation of the ceramic coating layer. This ceramic spallation involves the formation of a dominant crack in the ceramic coating parallel to and closely adjacent to the metal-ceramic interface. Initial results from a laboratory test program designed to study the influence of various driving forces such as temperature, thermal cycle frequency, environment, and coating thickness, on ceramic coating spalling life suggest that bond coat oxidation damage at the metal-ceramic interface contributes significantly to thermomechanical cracking in the ceramic layer. Low cycle rate furnace testing in air and in argon clearly shows a dramatic increase of spalling life in the non-oxidizing environments