The transition towards a sustainable and renewable energy future is essential to mitigate climate change and reduce greenhouse gas emissions. Small–medium combined heat and power (CHP) systems are increasingly popular for distributed energy generation, as they offer improved energy efficiency and reduced emissions compared to traditional power generation systems. This article reviews recent research articles related to small–medium CHP systems, including their role in renewable energy systems, use of biofuels, steam injection, diagnostics, and carbon capture. Throughout the research, the high potential of coastal regions has been observed and studied as a solid base for the later development of CHP systems. Based on the reviewed literature, the highest potential solutions are proposed to be further investigated as an efficient, economical solution for generating electricity and heat for various small-scale applications.

One of the aims of this work is the study of the geometry of a micro-cogenerator using a Stirling engine with four double effect pistons. The complex geometry of the heat exchangers was determined by optical measurements. Results of three thermodynamic models: Direct Method from Finite Speed Thermodynamics (FST), isothermal model (Schmidt), and adiabatic model (Finkelstein) are confronted to experimental ones. Direct Method consists of the study and the evaluation of the irreversibilities of thermal machines by analyzing the cycle, step by step, and directly integrating the equation of the First Law for processes with finite speed combined with Second Law of Thermodynamics, for each process of the cycle. The expression of efficiency and power, depending on the speed of the processes and geometric and functional parameters, is then obtained in a straightforward manner. The isothermal and adiabatic models are based on the division of Stirling engine in 3, respectively 5 control volumes, for which the ideal gas law and the equations of mass and energy balance are applied. Analysis of the process of heat transfer and flow of the working gas, taking place in the Stirling engine, is carried out taking into account instantaneous representation of the working fluid volume in the engine. A system of differential equations is solved by iteration using Matlab/Simulink software. The theoretical results are compared to experimental ones. This comparison allows to point out a good accuracy of the Direct Method and the Adiabatic Model, for the thermal operating parameters of the system, noting the different assumptions of each analysis. Copyright © 2015 John Wiley & Sons, Ltd.

This case study analyzes a cryogenic air separation unit (ASU) with a production of ${\dot{V}}_{O_2}=\mathrm{58,300} \left[\frac{m^{3}N}{h}\right]$ of gaseous oxygen with a concentration greater than 98.5%, operating in Romania on a steel plant platform. The goal of the paper is to provide an extensive model of exergetic analysis that could be used in an optimization procedure when decisional parameters are changed or structural design modifications are implemented. For each key part of the Air Separation Unit, an exergetic product and fuel were defined and, based on their definition, the coefficient of performance of each functional zone was calculated. The information about the magnitude of the exergetic losses offers solutions for their future recovery. The analysis of the exergy destructions suggests when it is worth making a larger investment. The exergetic analysis of the compression area of the ASU points out an exergy destruction and loss of 37% from the total plant’s electrical energy input. The exergy loss with the heat transferred to the cooling system of compressors can be recovered; for the exergy destruction portion, the challenge between investment and operating costs should be considered. The exergy destruction of the air separation columns found the High Pressure Column (HPC) to be more destructive than the Low Pressure Column. The share of the exergy destruction in the total plant’s electrical energy input is 8.3% for the HPC. The local COP of the HPC, calculated depending on the total exergy of the local product and fuel, is 62.66%. The calculus of the air separation column is performed with the ChemSep simulator.

The paper presents experimental tests and theoretical studies of a Stirling engine cycle applied to a β-type machine. The finite physical dimension thermodynamics (FPDT) method and 0D modeling by the imperfectly regenerated Schmidt model are used to develop analytical models for the Stirling engine cycle. The purpose of this study is to show that two simple models that take into account only the irreversibility due to temperature difference in the heat exchangers and imperfect regeneration are able to indicate engine behavior. The share of energy loss for each is determined using these two models as well as the experimental results of a particular engine. The energies exchanged by the working gas are expressed according to the practical parameters, which are necessary for the engineer during the entire project, namely the maximum pressure, the maximum volume, the compression ratio, the temperature of the heat sources, etc. The numerical model allows for evaluation of the energy processes according to the angle of the crankshaft (kinematic–thermodynamic coupling). The theoretical results are compared with the experimental research. The effect of the engine rotation speed on the power and efficiency of the actual operating machine is highlighted. The two methods show a similar variation in performance, although heat loss due to imperfect regeneration is evaluated differently.

The purpose of the study is to show that two simple models that take into account only the irreversibility due to temperature difference in the heat exchangers and imperfect regeneration are able to indicate refrigerating machine behavior. In the present paper, the finite physical dimensions thermodynamics (FPDT) method and 0-D modeling using the Schmidt model with imperfect regeneration were applied in the study of a β type Stirling refrigeration machine.The 0-D modeling is improved by including the irreversibility caused by imperfect regeneration and the finite temperature difference between the gas and the heat exchangers wall. A flowchart of the Stirling refrigerator exergy balance is presented to show the internal and external irreversibilities. It is found that the irreversibility at the regenerator level is more important than that at the heat exchangers level. The energies exchanged by the working gas are expressed according to the practical parameters, necessary for the engineer during the entire project. The results of the two thermodynamic models are presented in comparison with the experimental results, which leads to validation of the proposed FPDT model for the functional and constructive parameters of the studied refrigerating machine.

An irreversible Carnot cycle engine operating as a closed system is modeled using the Direct Method and the First Law of Thermodynamics for processes with Finite Speed. Several models considering the effect on the engine performance of external and internal irreversibilities expressed as a function of the piston speed are presented. External irreversibilities are due to heat transfer at temperature gradient between the cycle and heat reservoirs, while internal ones are represented by pressure losses due to the finite speed of the piston and friction. Moreover, a method for optimizing the temperature of the cycle fluid with respect to the temperature of source and sink and the piston speed is provided. The optimization results predict distinct maximums for the thermal efficiency and power output, as well as different behavior of the entropy generation per cycle and per time. The results obtained in this optimization, which is based on piston speed, and the Curzon–Ahlborn optimization, which is based on time duration, are compared and are found to differ significantly. Correction have been proposed in order to include internal irreversibility in the externally irreversible Carnot cycle from Curzon–Ahlborn optimization, which would be equivalent to a unification attempt of the two optimization analyses.