Machines for Distributed Microgeneration Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (20 November 2022) | Viewed by 1484

Special Issue Editors

Department of Energy, Systems, Territory and Constructions Engineering (D.E.S.T.eC), University of Pisa, 56126 Pisa, Italy
Interests: fluid machinery; internal combustion engine; solar energy
Special Issues, Collections and Topics in MDPI journals
Department of Energy, Systems, Territory and Construction Engineering (D.E.S.T.eC), University of Pisa, 56126 Pisa, Italy
Interests: solar energy conversion; thermal engines; CSP
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Distributed microgeneration is a strategy that consists of the decentralized production of electrical energy, usually below 1 MW, in order for consumers to satisfy their energy demands. Different technologies, such as micro combined heat and power engines, ORC cycles, waste recovery applications, and micro-wind, are available for microgeneration applications. Consequently, several studies have suggested that distributed microgeneration might be able to reduce pollutant emissions and energy losses in energy production transmission and distribution, ensure sustainable development, and improve the security of the energy supply. 

In microgeneration applications, the machine responsible for the conversion of the available energy is crucial, because its performance determines the power output and the cost of the system; therefore, developments in the analysis of expander devices are expected.

This Special Issue aims to provide an overview that focuses on the performance of the expanders available for microgeneration units by emphasizing design criteria, thermal and fluid dynamic aspects, performance analysis, control strategies, and feasibility assessment. Contributions that present both numerical and experimental studies that deal with machines suitable for microgeneration systems are welcome.

Dr. Marco Francesconi
Dr. Marco Antonelli
Guest Editors

Manuscript Submission Information

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Keywords

  • distributed microgeneration
  • cogeneration
  • renewable energies
  • ORC systems
  • waste heat recovery
  • CHP systems
  • engines
  • volumetric expanders
  • turbines
  • CFD techniques
  • experimental analysis
  • numerical modelling
  • performance analysis
  • control strategies
  • electrical grid
  • feasibility assessment
  • LCA analysis

Published Papers (1 paper)

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Research

14 pages, 3370 KiB  
Article
Algorithm for Cycle-To-Cycle Firing TDC Identification Based on Wasted Spark Duration Measurements in Small Engines
by Adrian Irimescu, Simona Silvia Merola and Bianca Maria Vaglieco
Appl. Sci. 2023, 13(3), 1362; https://0-doi-org.brum.beds.ac.uk/10.3390/app13031362 - 19 Jan 2023
Cited by 1 | Viewed by 1022
Abstract
Spark ignition (SI) engines are often used as distributed power generation applications. They ensure quick deployment, cost effective electricity, and are a valid choice for back-up power. An essential aspect for small size engines is to improve control margins without increasing the number [...] Read more.
Spark ignition (SI) engines are often used as distributed power generation applications. They ensure quick deployment, cost effective electricity, and are a valid choice for back-up power. An essential aspect for small size engines is to improve control margins without increasing the number of sensors. It is not uncommon to employ fixed ignition timing for such power units, with so called wasted spark systems. These feature two spark events per cycle, one during compression and one during the exhaust stroke. On the other hand, ever more complex control systems are applied for this engine category in the search for better efficiency and lower emissions. Control of actuators that is phased with the working cycle could represent a significant advantage in this context. A method previously developed for identifying top dead center (TDC) phasing offline was applied as an algorithm capable of performing the required task while the engine is running. It is based on current measurements in the secondary ignition circuit of systems that feature wasted spark operation. Validation was performed on a 50 cm3 SI unit connected to a 1 kW power generator. Statistical distribution during sequences of 1000 cycles recorded at five different levels of load was used for testing TDC identification capabilities. Results were also compared to evaluations based on engine speed measurements. The overall TDC identification success rate of the proposed algorithm was found to be over 99.8%. Full article
(This article belongs to the Special Issue Machines for Distributed Microgeneration Systems)
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