Valuing Flexibility: The case of an Integrated Gasification Combined Cycle Power Plant

In this paper we analyze the valuation of options stemming from the flexibility in an Integrated Gasification Combined Cycle (IGCC) Power Plant. First we use as a base case the opportunity to invest in a Natural Gas Combined Cycle (NGCC) Power Plant, deriving the optimal investment rule as a function of fuel price and the remaining life of the right to invest. Additionally, the analytical solution for a perpetual option is obtained. Second, the valuation of an operating IGCC Power Plant is studied, with switching costs between states and a choice of the best operation mode. The valuation of this plant serves as a base to obtain the value of the option to delay an investment of this type. Finally, we derive the value of an opportunity to invest either in a NGCC or IGCC Power Plant, that is, to choose between an inflexible and a flexible technology, respectively. Numerical computations involve the use of one- and two-dimensional binomial lattices that support a mean-reverting process for the fuel prices. Basic parameter values refer to an actual IGCC power plant currently in operation.

A mean-reverting stochastic model for the political business cycle

In this article, we look at the political business cycle problem through the lens of uncertainty. The feedback control used by us is the famous NKPC with stochasticity and wage rigidities. We extend the New Keynesian Phillips Curve model to the continuous time stochastic set up with an Ornstein-Uhlenbeck process. We minimize relevant expected quadratic cost by solving the corresponding Hamilton-Jacobi-Bellman equation. The basic intuition of the classical model is qualitatively carried forward in our set up but uncertainty also plays an important role in determining the optimal trajectory of the voter support function. The internal variability of the system acts as a base shifter for the support function in the risk neutral case. The role of uncertainty is even more prominent in the risk averse case where all the shape parameters are directly dependent on variability. Thus, in this case variability controls both the rates of change as well as the base shift parameters. To gain more insight we have also studied the model when the coefficients are time invariant and studied numerical solutions. The close relationship between the unemployment rate and the support function for the incumbent party is highlighted. The role of uncertainty in creating sampling fluctuation in this set up, possibly towards apparently anomalous results, is also explored.

COST AND PERFORMANCE TRADEOFFS OF ALTERNATIVE SOLAR-DRIVEN S-CO2 BRAYTON CYCLE CONFIGURATIONS

This paper evaluates cost and performance tradeoffs of alternative supercritical carbon dioxide (s-CO2) closed-loop Brayton cycle configurations with a concentrated solar heat source. Alternative s-CO2 power cycle configurations include simple, recompression, cascaded, and partial cooling cycles. Results show that the simple closed-loop Brayton cycle yielded the lowest power-block component costs while allowing variable temperature differentials across the s-CO2 heating source, depending on the level of recuperation. Lower temperature differentials led to higher sensible storage costs, but cycle configurations with lower temperature differentials (higher recuperation) yielded higher cycle efficiencies and lower solar collector and receiver costs. The cycles with higher efficiencies (simple recuperated, recompression, and partial cooling) yielded the lowest overall solar and power-block component costs for a prescribed power output.

Altered movement patterns but not muscle recruitment in moderately trained triathletes during running after cycling

Previous studies have shown that cycling can directly influence neuromuscular control during subsequent running in some highly trained triathletes, despite these triathletes' years of practice of the cycle-run transition. The aim of this study was to determine whether cycling has the same direct influence on neuromuscular control during running in moderately trained triathletes. Fifteen moderately trained triathletes participated. Kinematics of the pelvis and lower limbs and recruitment of 11 leg and thigh muscles were compared between a control run (no prior exercise) and a 30 min run that was preceded by a 15 min cycle (transition run). Muscle recruitment was different between control and transition runs in only one of 15 triathletes (<7%). Changes in joint position (mean difference of 3°) were evident in five triathletes, which persisted beyond 5 min of running in one triathlete. Our findings suggest that some moderately trained triathletes have difficulty reproducing their pre-cycling movement patterns for running initially after cycling, but cycling appears to have little influence on running muscle recruitment in moderately trained triathletes.

A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources

The penetration of intermittent renewable energy sources (IRESs) into power grids has increased in the last decade. Integration of wind farms and solar systems as the major IRESs have significantly boosted the level of uncertainty in operation of power systems. This paper proposes a comprehensive computational framework for quantification and integration of uncertainties in distributed power systems (DPSs) with IRESs. Different sources of uncertainties in DPSs such as electrical load, wind and solar power forecasts and generator outages are covered by the proposed framework. Load forecast uncertainty is assumed to follow a normal distribution. Wind and solar forecast are implemented by a list of prediction intervals (PIs) ranging from 5% to 95%. Their uncertainties are further represented as scenarios using a scenario generation method. Generator outage uncertainty is modeled as discrete scenarios. The integrated uncertainties are further incorporated into a stochastic security-constrained unit commitment (SCUC) problem and a heuristic genetic algorithm is utilized to solve this stochastic SCUC problem. To demonstrate the effectiveness of the proposed method, five deterministic and four stochastic case studies are implemented. Generation costs as well as different reserve strategies are discussed from the perspectives of system economics and reliability. Comparative results indicate that the planned generation costs and reserves are different from the realized ones. The stochastic models show better robustness than deterministic ones. Power systems run a higher level of risk during peak load hours.

Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: a comparative study

The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones.

Simulation, Design and Analysis of Air-Breathing Combined-Cycle Engines for High Speed Propulsion

Desde la aparición del turborreactor, el motor aeróbico con turbomaquinaria ha demostrado unas prestaciones excepcionales en los regímenes subsónico y supersónico bajo. No obstante, la operación a velocidades superiores requiere sistemas más complejos y pesados, lo cual ha imposibilitado la ejecución de estos conceptos. Los recientes avances tecnológicos, especialmente en materiales ligeros, han restablecido el interés por los motores de ciclo combinado. La simulación numérica de estos nuevos conceptos es esencial para estimar las prestaciones de la planta propulsiva, así como para abordar las dificultades de integración entre célula y motor durante las primeras etapas de diseño. Al mismo tiempo, la evaluación de estos extraordinarios motores requiere una metodología de análisis distinta. La tesis doctoral versa sobre el diseño y el análisis de los mencionados conceptos propulsivos mediante el modelado numérico y la simulación dinámica con herramientas de vanguardia. Las distintas arquitecturas presentadas por los ciclos combinados basados en sendos turborreactor y motor cohete, así como los diversos sistemas comprendidos en cada uno de ellos, hacen necesario establecer una referencia común para su evaluación. Es más, la tendencia actual hacia aeronaves "más eléctricas" requiere una nueva métrica para juzgar la aptitud de un proceso de generación de empuje en el que coexisten diversas formas de energía. A este respecto, la combinación del Primer y Segundo Principios define, en un marco de referencia absoluto, la calidad de la trasferencia de energía entre los diferentes sistemas. Esta idea, que se ha estado empleando desde hace mucho tiempo en el análisis de plantas de potencia terrestres, ha sido extendida para relacionar la misión de la aeronave con la ineficiencia de cada proceso involucrado en la generación de empuje. La metodología se ilustra mediante el estudio del motor de ciclo combinado variable de una aeronave para el crucero a Mach 5. El diseño de un acelerador de ciclo combinado basado en el turborreactor sirve para subrayar la importancia de la integración del motor y la célula. El diseño está limitado por la trayectoria ascensional y el espacio disponible en la aeronave de crucero supersónico. Posteriormente se calculan las prestaciones instaladas de la planta propulsiva en función de la velocidad y la altitud de vuelo y los parámetros de control del motor: relación de compresión, relación aire/combustible y área de garganta. ABSTRACT Since the advent of the turbojet, the air-breathing engine with rotating machinery has demonstrated exceptional performance in the subsonic and low supersonic regimes. However, the operation at higher speeds requires further system complexity and weight, which so far has impeded the realization of these concepts. Recent technology developments, especially in lightweight materials, have restored the interest towards combined-cycle engines. The numerical simulation of these new concepts is essential at the early design stages to compute a first estimate of the engine performance in addition to addressing airframe-engine integration issues. In parallel, a different analysis methodology is required to evaluate these unconventional engines. The doctoral thesis concerns the design and analysis of the aforementioned engine concepts by means of numerical modeling and dynamic simulation with state-of-the-art tools. A common reference is needed to evaluate the different architectures of the turbine and the rocket-based combined-cycle engines as well as the various systems within each one of them. Furthermore, the actual trend towards more electric aircraft necessitates a common metric to judge the suitability of a thrust generation process where different forms of energy coexist. In line with this, the combination of the First and the Second Laws yields the quality of the energy being transferred between the systems on an absolute reference frame. This idea, which has been since long applied to the analysis of on-ground power plants, was extended here to relate the aircraft mission with the inefficiency of every process related to the thrust generation. The methodology is illustrated with the study of a variable- combined-cycle engine for a Mach 5 cruise aircraft. The design of a turbine-based combined-cycle booster serves to highlight the importance of the engine-airframe integration. The design is constrained by the ascent trajectory and the allocated space in the supersonic cruise aircraft. The installed performance of the propulsive plant is then computed as a function of the flight speed and altitude and the engine control parameters: pressure ratio, air-to-fuel ratio and throat area.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Candidate radial-inflow turbines and high-density working fluids for geothermal power systems

Optimisation of Organic Rankine Cycles (ORCs) for binary-cycle geothermal applications could play a major role in the competitiveness of low to moderate temperature geothermal resources. Part of this optimisation process is matching cycles to a given resource such that power output can be maximised. Two major and largely interrelated components of the cycle are the working fluid and the turbine. Both components need careful consideration. Due to the temperature differences in geothermal resources a one-size-fits-all approach to surface power infrastructure is not appropriate. Furthermore, the traditional use of steam as a working fluid does not seem practical due to the low temperatures of many resources. A variety of organic fluids with low boiling points may be utilised as ORC working fluids in binary power cycle loops. Due to differences in thermodynamic properties, certain fluids are able to extract more heat from a given resource than others over certain temperature and pressure ranges. This enables the tailoring of power cycle infrastructure to best match the geothermal resource through careful selection of the working fluid and turbine design optimisation to yield the optimum overall cycle performance. This paper presents the rationale for the use of radial-inflow turbines for ORC applications and the preliminary design of several radial-inflow turbines based on a selection of promising ORC cycles using five different high-density working fluids: R134a, R143a, R236fa, R245fa and n-Pentane at sub- or trans-critical conditions. Numerous studies published compare a variety of working fluids for various ORC configurations. However, there is little information specifically pertaining to the design and implementation of ORCs using realistic radial turbine designs in terms of pressure ratios, inlet pressure, rotor size and rotational speed. Preliminary 1D analysis leads to the generation of turbine designs for the various cycles with similar efficiencies (77%) but large differences in dimensions (139289 mm rotor diameter). The highest performing cycle (R134a) was found to produce 33% more net power from a 150°C resource flowing at 10 kg/s than the lowest performing cycle (n-Pentane).

High strong order methods for non-commutative stochastic ordinary differential equation systems and the Magnus formula

In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.

Mode matching pursuit for estimating dominant modes in bulk power grid

This study presents a general approach to identify dominant oscillation modes in bulk power system by using wide-area measurement system. To automatically identify the dominant modes without artificial participation, spectral characteristic of power system oscillation mode is applied to distinguish electromechanical oscillation modes which are calculated by stochastic subspace method, and a proposed mode matching pursuit is adopted to discriminate the dominant modes from the trivial modes, then stepwise-refinement scheme is developed to remove outliers of the dominant modes and the highly accurate dominant modes of identification are obtained. The method is implemented on the dominant modes of China Southern Power Grid which is one of the largest AC/DC paralleling grids in the world. Simulation data and field-measurement data are used to demonstrate high accuracy and better robustness of the dominant modes identification approach.

Comparison of CO2 and steam in transcritical Rankine cycles for concentrated solar power

High temperature, high pressure transcritical condensing CO2 cycle (TC-CO2) is compared with transcritical steam (TC-steam) cycle. Performance indicators such as thermal efficiency, volumetric flow rates and entropy generation are used to analyze the power cycle wherein, irreversibilities in turbo-machinery and heat exchangers are taken into account. Although, both cycles yield comparable thermal efficiencies under identical operating conditions, TC-CO2 plant is significantly compact compared to a TC-steam plant. Large specific volume of steam is responsible for a bulky system. It is also found that the performance of a TC-CO2 cycle is less sensitive to source temperature variations, which is an important requirement of a solar thermal system. In addition, issues like wet expansion in turbine and vacuum in condenser are absent in case of a TC-CO2 cycle. External heat addition to working fluid is assumed to take place through a heat transfer fluid (HTF) which receives heat from a solar receiver. A TC-CO2 system receives heat though a single HTF loop, whereas, for TC-steam cycle two HTF loops in series are proposed to avoid high temperature differential between the steam and HTF. (C) 2013 P. Garg. Published by Elsevier Ltd.

MOMENT ANALYSIS OF A SCROLL EXPANDER USED IN AN ORGANIC RANKINE CYCLE

Recent studies on small-scale power generation with the organic Rankine cycle suggest superior performance of positive displacement type of expanders compared to turbines. Scroll expanders in particular achieve high isentropic efficiencies due to lower leakage and frictional losses. Performance of scroll machines may be enhanced by the use of non-circular involute curves in place of the circular involutes resulting non-uniform wall thickness. In this paper, a detailed moment analysis is performed for such an expander having volumetric expansion ratio of 5 using thermodynamic models proposed earlier by one of the present authors. The working fluid considered in the power cycle is R-245fa with scroll inlet temperature of 125 degrees C for a gross power output of similar to 3.5 kW. The model developed in this paper is verified with an air scroll compressor available in the literature and then applied to an expander Prediction of small variation of moment with scroll motion recommends use of scroll expander without a flywheel over other positive displacement type of expanders, e.g. reciprocating, where a flywheel is an essential component.

COUPLED OPTICAL-THERMAL-FLUID MODELING OF A DIRECTLY HEATED TUBULAR SOLAR RECEIVER FOR SUPERCRITICAL CO2 BRAYTON CYCLE

Recent studies have evaluated closed-loop supercritical carbon dioxide (s-CO2) Brayton cycles to be a higher energy density system in comparison to conventional superheated steam Rankine systems. At turbine inlet conditions of 923K and 25 MPa, high thermal efficiency (similar to 50%) can be achieved. Achieving these high efficiencies will make concentrating solar power (CSP) technologies a competitive alternative to current power generation methods. To incorporate a s-CO2 Brayton power cycle in a solar power tower system, the development of a solar receiver capable of providing an outlet temperature of 923 K (at 25 MPa) is necessary. The s-CO2 will need to increase in temperature by similar to 200 K as it passes through the solar receiver to satisfy the temperature requirements of a s-CO2 Brayton cycle with recuperation and recompression. In this study, an optical-thermal-fluid model was developed to design and evaluate a tubular receiver that will receive a heat input similar to 2 MWth from a heliostat field. The ray-tracing tool SolTrace was used to obtain the heat-flux distribution on the surfaces of the receiver. Computational fluid dynamics (CFD) modeling using the Discrete Ordinates (DO) radiation model was used to predict the temperature distribution and the resulting receiver efficiency. The effect of flow parameters, receiver geometry and radiation absorption by s-CO2 were studied. The receiver surface temperatures were found to be within the safe operational limit while exhibiting a receiver efficiency of similar to 85%.

Application of PMUs to Coordinate Hydroelectric and Wind Power Plant Operation

It is acknowledged that wind power is a stochastic energy source compared to hydroelectric generation which is easily scheduled. In this paper a scheme for coordinating wind power plant and hydroelectric power plant is presented by using PMUs to measure and control the state of wind and hydro power plants. Hydroelectric generation is proposed as a method of energy reserve and compensation in the context of wind power fluctuation in order to avoid full or partial curtailment of wind generation to benefit wind providers. The feasibility of this proposed scheme is investigated by power flow calculation and stability analysis using the IEEE 30-bus power system model.