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Research Papers: Energy Systems Analysis

Micro Combined Heat and Power System Transient Operation in a Residential User Microgrid

[+] Author and Article Information
Francesco Ippolito

Dipartimento di Ingegneria,
Università degli Studi di Ferrara,
Via Giuseppe Saragat, 1,
Ferrara 44121, Italy

Mauro Venturini

Dipartimento di Ingegneria,
Università degli Studi di Ferrara,
Ferrara 44121, Italy
Via Giuseppe Saragat, 1,
e-mail: mauro.venturini@unife.it

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received January 14, 2018; final manuscript received November 27, 2018; published online December 24, 2018. Assoc. Editor: Esmail M. A. Mokheimer.

J. Energy Resour. Technol 141(4), 042006 (Dec 24, 2018) (9 pages) Paper No: JERT-18-1044; doi: 10.1115/1.4042231 History: Received January 14, 2018; Revised November 27, 2018

This paper presents an analysis of the transient operation of a micro combined heat and power (CHP) system, equipped with both thermal and electric storage units and connected with both electric and district heating grids. Analysis is carried out by means of a simulation model developed by the authors for reproducing the transient behavior of micro-CHP systems operating within a microgrid. The prime mover considered in this paper is an internal combustion reciprocating engine. A residential user, characterized by electric and thermal energy demand during one representative summer day, is analyzed by using literature data. The transient response of each component is evaluated separately to quantify the relative deviation (RD) between the user-demand and micro-CHP system transient response. Therefore, this paper provides a measure of the RD over 1 day in terms of the energy required by the user versus the energy provided to the user itself.

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Figures

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Fig. 1

Architecture of the complete simulation model [45]

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Fig. 2

Control logic in thermal load following mode [45]

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Fig. 3

Residential user power demand in summer [1,45]

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Fig. 4

Influence of PM delay time (scenario #1)

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Fig. 5

Influence of DHG delay time (scenario #1)

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Fig. 6

Combined influence of PM and DHG delay time (scenario #1)

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Fig. 7

Influence of TES delay time (scenario #2)

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Fig. 8

Influence of DHG delay time (scenario #2)

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Fig. 9

Combined influence of TES and DHG delay time (scenario #2)

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Fig. 10

Influence of EG delay time (scenario #3)

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Fig. 11

Influence of EES delay time (scenario #4)

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Fig. 12

Relative deviation of thermal energy versus delay time magnitude (scenario #1)

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Fig. 13

Relative deviation of thermal energy versus delay time magnitude (scenario #2)

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