2006
DOI: 10.1016/j.enbuild.2005.11.008
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Optimisation of consumer benefits from microCombined Heat and Power

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Cited by 25 publications
(21 citation statements)
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“…For example, assessment of FCs (Dorer et al, 2005;Alanne et al, 2006;, assessment of ICEs (Possidente et al, 2006), assessment of SEs (Boait et al, 2006) and comparative assessments between different technologies (Cockroft and Kelly, 2006;Peacock and Newborough, 2006;De Paepe and Mertens, 2007) have been conducted. The effects of uncertainties of objectives such as operation cost and constraints such as CO concentration in PEMFC on the energy system synthesis/design and operation/control optimisation have been also studied (Kim, 2008).…”
Section: Residential μChpmentioning
confidence: 99%
“…For example, assessment of FCs (Dorer et al, 2005;Alanne et al, 2006;, assessment of ICEs (Possidente et al, 2006), assessment of SEs (Boait et al, 2006) and comparative assessments between different technologies (Cockroft and Kelly, 2006;Peacock and Newborough, 2006;De Paepe and Mertens, 2007) have been conducted. The effects of uncertainties of objectives such as operation cost and constraints such as CO concentration in PEMFC on the energy system synthesis/design and operation/control optimisation have been also studied (Kim, 2008).…”
Section: Residential μChpmentioning
confidence: 99%
“…In the past it has been common to model the performance of SE micro-cogeneration devices using performance-map methods wherein the device's electrical and thermal efficiencies are treated as constant or are a parametric function of the device's loading [13][14][15]. This approach essentially decouples the modelling of the SE micro-cogeneration device from that of the house and other aspects of the thermodynamic system and as such precludes an accurate treatment of the thermal coupling to the building and its HVAC system, as demonstrated by [16].…”
Section: Introductionmentioning
confidence: 99%
“…With an exponential distribution the large spikes in domestic electricity demand can be simulated quite accurately compared to empirical data from [21], [34], [37]. In creating individual domestic heat demand profiles, samples are taken from normal distributions, with the expected values equaling the average heat demand at that time period.…”
Section: ) Model Inputmentioning
confidence: 99%