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Locating the causes of malfunctions in complex energy systems is an extremely difficult task, since more than one fault mode may produce similar and possibly undistinguishable patterns of effects. This paper shows how fuzzy expert systems can exploit the available measurements from the data acquisition system to identify different component and sensor fault modes. Real sensor data (mass flow rates, pressures, temperatures, and key operating parameters) are compared with the expected values of the same quantities that are calculated using numerical models of local subsystems. This comparison simply determines if the differences between measured and expected values are 'negative,' 'zero,' or 'positive' in fuzzy logic terms. The final objective is to verify the existence of some patterns of these attributes that univocally identify the considered fault modes. These patterns are then implemented as the set of rules forming the knowledge base of a fuzzy expert system. The proposed diagnostic methodology is tested on the gas section of a real combined-cycle cogeneration plant, and the effect of measurement noise is also discussed. [DOI: 10.1115/1.4000175]

Energy system performance may differ from the expected one during actual operation because of the effects of faults, anomalies, and wear and tear due to normal use. One of the main issues of diagnosis, i.e., the procedure to discover the causes of malfunctions, is to find the way back from measured altered performance to the original cause. Several procedures were proposed in the literature to solve the diagnostic problem, usually based on the comparison between a reference nonmalfunctioning condition and an actual possibly malfunctioning, condition. A different strategy is suggested in the paper A direct search of the possible causes of malfunctions is performed by means of an evolutionary algorithm: a component fault is arbitrarily introduced in a model of the healthy system by substituting the reference characteristic curve with an altered one, and the algorithm is used to search for a combination of different kinds of performance modifiers that generates the same measured effects of the actual anomaly. A global and a local approach are proposed and applied to a real test case plant, also in presence of measurement noise. The local approach demonstrates to be more effective in terms of accuracy and computational effort. [DOI: 10.1115/1.4000172]

Diagnosis procedures primarily aim at locating the control volumes where anomalies occurred. This is not a simple task since the effects of anomalies generally propagate through the whole system and affect the behavior of several components. Some components may therefore present a reduced efficiency, although they are not sources of operation anomalies, due to nonflat efficiency curves. These induced effects are a big obstacle in the use of thermoeconomic techniques for the search of the origin of the anomalies. On the other hand, the real cause of the alteration of component behavior is the modification of its characteristic curve, due to degradation or failures. According to this concept, a new approach, based on an indicator measuring the alteration of the characteristic curve of the component affected by the operation anomaly, is proposed and applied to a test case power plant. [DOI: 10.1115/1.2424960]

Thermoeconomic diagnosis procedures in the literature rely on the assumption that specific consumptions of resources in the components are the key to interpret the effects of malfunctions and then to trace a path towards the sources of anomalies. The main obstacle to a successful application of these approaches is represented by the actual interactions existing among components which cause a propagation of the alteration of component specific consumptions and therefore mask those effects that would allow a direct identification of the origin of malfunction. This paper presents an extensive discussion of potentialities and limits of diagnosis procedures proposed in the literature in distinguishing the effects induced by component interactions from those that are intrinsically generated by the anomaly, which is considered here as the main task to locate effectively causes of malfunctions in energy systems. [DOI: 10.1115/1.2358148]

Contrary to conventional turbomachinery, cross-flow fan flow field is non-axisymmetrical and its complex configuration strongly affects performance and efficiency characteristic curves. The formulation of a theory on cross-flow fan operation is made even tougher since the strength and the eccentricity of the vortex that forms within the impeller are deeply influenced by the geometry of the impeller and of the casing as well. In this paper, a numerical reconstruction of the flow field, validated against an extensive systematic database of global and local experimental measurements, is analyzed. The aim is to achieve a general interpretation of performance and efficiency curves, and to lead them back to one theoretical archetype, whatever the fan configuration being considered.

Several empirical assumptions deriving from observations and measurements of the physical processes are involved in the modeling of Solid Oxide Fuel Cells (SOFCs). An insight of the main models proposed in the literature is given to present the characteristics and limits of these assumptions for the various existing configurations. The basic structure and equations of the models are discussed in details, focusing particularly on the parameters that are to be set to achieve reliability and accuracy. According to this discussion, a zero-dimensional model for a tubular Solid Oxide Fuel Cell (SOFC) is then presented. The model demonstrates good capability in predicting SOFC characteristic curves as they appear in the literature.

This paper describes a multi-objective optimization method for the design of stall-regulated horizontal-axis wind turbines. Two modules are used for this purpose: an aerodynamic model implementing the blade-element theory and a multi-objective evolutionary algorithm. The former provides a sufficiently accurate solution of the flow field around the rotor disc; the latter handles the decision variables of the optimization problem, i.e., the main geometrical parameters of the rotor configuration, and promotes function optimization. The scope of the method is to achieve the best trade-off performance between two objectives: annual energy production per square meter of wind park (to be maximized) and cost of energy (to be minimized). Examples of the best solutions found by the method are described and their performance compared with those of commercial wind turbines. Keywords: HAWT, Stall-Regulated Turbines, Aerodynamic Design, Evolutionary Computation, Genetic Algorithms, Multi-Objective Design

The use of residual biomass streams for production of liquid fuels will help in achieving the goal of renewable transportation fuels and sustainable society. Hence, efficient, and reliable processes offering a flexible product distribution proven at commercial scale are required. This study explores the technical feasibility of producing gasoline and diesel range hydrocarbons from thermochemical processing of biomass via the production of light olefins (C2-C4) and their subsequent oligomerization through mathematical modelling and simulation using MATLAB software. Different biomass processing scenarios were considered, including a standalone biomass gasification plant and integrated biomass pyrolysis- char gasification (O2- or air-blown) process. Process analysis indicated that the integrated plant offers 10-11% higher carbon efficiency. The processing step with the highest carbon penalty for all the cases is the syngas composition tailoring via water-gas shift reaction. [ABSTRACT FROM AUTHOR]