Giovanni Petrecca

A review of hydrogen applications: Technical and economic aspects

This paper aims to investigate the economic and technical aspects related to the use of hydrogen, particularly in fuel cells, focusing on both energy and environmental impacts as decisional factors. The study has examined the overall chain, from hydrogen production (mainly through electrolysis and gas reforming) to electric energy production, in order to point out energy efficiency and energy costs of the different phases of the chain. A range of fuel cells from few to thousands of kW of electric power has been considered.

Neural networks for energy flows prediction in facility systems

A procedure for the short-term prediction of the thermal energy consumption of a hospital is shown in this paper. First, linear ARX models are built in order to obtain information on the influence of the input variables on the output of the system. Therefore, nonlinear models based on feedforward neural networks (NNARX) are built using the information provided by the linear estimate. The results obtained from the ARX and NNARX models are compared, concluding that NNARX models provide better results than ARX models, but the analysis of ARX models is necessary to obtain guidelines in the choice of the best regression vector as input for the neural models.

The role of electricity in energy efficiency power conversion: a MarkAl application for energy planning

Energy saving technologies based on the use of electricity are in many cases an alternative to thermal energy from fuels. They are lighting, electrical drives, heat pumps, microwave, induction heating, mechanical recompression of vapor, distributed control system in industry and buildings, energy storage, renewable energy sources, electric and hybrid vehicles, smart grid applications. A wider use of these technologies is supported by the continuous increase of utility plant efficiency up to 60% combined with climate change awareness.

System identification for the prediction of the electric energy consumption of a dairy firm

A system identification method based on black-box techniques for the prediction of the electric energy consumption in a dairy firm is presented. This prediction is required by the Italian free energy market where the energy sellers aim at selling energy according to a load flow scheduled some days in advance. The black-box identification is employed as an alternative to an energy investigation of the firm. The inputs of the system are the work shifts of each process unit and the output is the electric energy consumption. Two black-box parametric models have been evaluated-linear and neural-and the principal component analysis method has been employed to preprocess the data.

A simplified tool for the simulation of biomass based power plants

This paper reports the results of studies on energy production by using biomasses. The use of biomasses is encouraged worldwide due to the increasing prices of oil and natural gas and concern for pollution and CO2 emissions as well as to the possibility of using local resources and help local economies. Biomasses have been classified according to type and production chain. The main techniques for the energy transformation of biomasses are investigated and some practical examples are explained in details by means of a simplified tool. The paper outlines also a simplified energy planning of a district area.

Linear and neural dynamical models for energy flows prediction in facility systems

A procedure for the short-term prediction of the thermal energy consumption of an hospital is shown in this paper. At first, linear ARX models are built to get information on the influence of the input variables on the output of the system. Therefore, non-linear models based on feedforward neural networks (NNARX) are built using the information provided by the linear estimate. The results obtained from the ARX and NNARX models are compared, concluding that NNARX models provide better results than ARX models, but the analysis of ARX models is necessary to obtain guidelines in the choice of the best regression vector as input for neural models.

Energy Efficiency Technologies for Industry and Tertiary Sectors: the European Experience and Perspective for the Future

This paper reports practical examples of energy saving systems implemented in Europe by combined actions in both facilities and process equipment. The basic technologies employed can be widely applied to industry and tertiary sectors with slight modifications. Based on these experiences, prospects for further energy savings are presented focusing on renewable energy applications, new energy storage systems, the use of information technology and power electronics to improve plant control systems, new technologies such as a wider use of electricity instead of thermal energy from fuels. The use of electricity is encouraged by the continuous increase of utility plant efficiency up to 60% and also by the main beneficial environmental features of a concentrated emission production. A similar approach can also be used for buildings whose consumptions are expected to drop down to 30-40% of the current ones.

Black-box identification of the electromagnetic torque of induction motors: polynomial and neural models

In this paper we examine the problem of knowing the value of steady-state electromagnetic torque in induction motors installed in industrial plants. The models derived from two parametric black-box identification techniques (polynomial and neural) are implemented and tested for two motors and compared with the analytical model provided by the equivalent circuit theory. Both provide better performances when compared to the latter; the best performance is given by the neural model.

Facilities—Industrial Cooling Systems

Refrigeration systems for process application and air conditioning convert work into a flow of heat from a process source or from a refrigerated space to an environmental sink. The main types can be described as vapor compression, absorption, and Brayton cycles.

World Energy Demand

Trends in energy use are expected to increase all over the world as the population is growing together with its need for goods and comfort.