dc.contributor.author |
Rentizelas, AA |
en |
dc.contributor.author |
Tatsiopoulos, IP |
en |
dc.contributor.author |
Tolis, A |
en |
dc.date.accessioned |
2014-03-01T01:29:50Z |
|
dc.date.available |
2014-03-01T01:29:50Z |
|
dc.date.issued |
2009 |
en |
dc.identifier.issn |
0961-9534 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/19369 |
|
dc.subject |
Bioenergy |
en |
dc.subject |
Biomass |
en |
dc.subject |
District heating and cooling |
en |
dc.subject |
Investment analysis |
en |
dc.subject |
Logistics |
en |
dc.subject |
Modelling |
en |
dc.subject |
Optimization |
en |
dc.subject |
Supply chain |
en |
dc.subject |
Tri-generation |
en |
dc.subject.classification |
Agricultural Engineering |
en |
dc.subject.classification |
Biotechnology & Applied Microbiology |
en |
dc.subject.classification |
Energy & Fuels |
en |
dc.subject.other |
Artificial intelligence |
en |
dc.subject.other |
Biological materials |
en |
dc.subject.other |
Biomass |
en |
dc.subject.other |
Cooling |
en |
dc.subject.other |
Cost reduction |
en |
dc.subject.other |
Decision support systems |
en |
dc.subject.other |
Decision theory |
en |
dc.subject.other |
District heating |
en |
dc.subject.other |
Energy conversion |
en |
dc.subject.other |
Energy management |
en |
dc.subject.other |
Heating |
en |
dc.subject.other |
Optimization |
en |
dc.subject.other |
Renewable energy resources |
en |
dc.subject.other |
Risk assessment |
en |
dc.subject.other |
Supply chain management |
en |
dc.subject.other |
Supply chains |
en |
dc.subject.other |
Bioenergy |
en |
dc.subject.other |
District heating and cooling |
en |
dc.subject.other |
Investment analysis |
en |
dc.subject.other |
Logistics |
en |
dc.subject.other |
Modelling |
en |
dc.subject.other |
Supply chain |
en |
dc.subject.other |
Tri-generation |
en |
dc.subject.other |
Investments |
en |
dc.subject.other |
bioenergy |
en |
dc.subject.other |
biomass |
en |
dc.subject.other |
decision support system |
en |
dc.subject.other |
financial system |
en |
dc.subject.other |
holistic approach |
en |
dc.subject.other |
investment |
en |
dc.subject.other |
optimization |
en |
dc.title |
An optimization model for multi-biomass tri-generation energy supply |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1016/j.biombioe.2008.05.008 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1016/j.biombioe.2008.05.008 |
en |
heal.language |
English |
en |
heal.publicationDate |
2009 |
en |
heal.abstract |
In this paper, a decision support system (DSS) for multi-biomass energy conversion applications is presented. The system in question aims at supporting an investor by thoroughly assessing an investment in locally existing multi-biomass exploitation for tri-generation applications (electricity, heating and cooling), in a given area. The approach followed combines use of holistic modelling of the system, including the multi-biomass supply chain, the energy conversion facility and the district heating and cooling network, with optimization of the major investment-related variables to maximize the financial yield of the investment. The consideration of multi-biomass supply chain presents significant potential for cost reduction, by allowing spreading of capital costs and reducing warehousing requirements, especially when seasonal biomass types are concerned. The investment variables concern the location of the bioenergy exploitation facility and its sizing, as well as the types of biomass to be procured, the respective quantities and the maximum collection distance for each type. A hybrid optimization method is employed to overcome the inherent limitations of every single method. The system is demand-driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of an investor to assess and optimize in financial terms an investment aiming at covering real energy demand. optimization is performed taking into account various technical, regulatory, social and logical constraints. The model characteristics and advantages are highlighted through a case study applied to a municipality of Thessaly, Greece. (C) 2008 Elsevier Ltd. All rights reserved. |
en |
heal.publisher |
PERGAMON-ELSEVIER SCIENCE LTD |
en |
heal.journalName |
Biomass and Bioenergy |
en |
dc.identifier.doi |
10.1016/j.biombioe.2008.05.008 |
en |
dc.identifier.isi |
ISI:000263995200008 |
en |
dc.identifier.volume |
33 |
en |
dc.identifier.issue |
2 |
en |
dc.identifier.spage |
223 |
en |
dc.identifier.epage |
233 |
en |