2014
DOI: 10.3390/en7128554
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Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

Abstract: In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings' energy supply characterized by high load variations on daily, weekly and annual bases, as well as the components applicable for flexible operation. The idea is that this approach should enable high accuracy and flexibility in mathematical modeling, while remaining efficient enough. The optimization problem is structurally decomposed into two new problems. … Show more

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Cited by 22 publications
(10 citation statements)
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“…net present value, internal rate of return, annual total costs), PEC, GHGE etc. For this purpose, we use the multiplatform object-oriented software tool for flexible ESSs mathematical modeling, called ESO-MS [19,27], developed by the first author of this paper. It is written in the C# programming language and able to operate on the.NET and Mono frameworks and communicate with various MILP solvers.…”
Section: Energy Systems Modelingmentioning
confidence: 99%
“…net present value, internal rate of return, annual total costs), PEC, GHGE etc. For this purpose, we use the multiplatform object-oriented software tool for flexible ESSs mathematical modeling, called ESO-MS [19,27], developed by the first author of this paper. It is written in the C# programming language and able to operate on the.NET and Mono frameworks and communicate with various MILP solvers.…”
Section: Energy Systems Modelingmentioning
confidence: 99%
“…Analysing tri‐generation or poly‐generation plants with mixed‐integer linear programming (MILP) as an optimisation model was carried out by the authors in . Canova et al proposed an MILP model for the optimal energy management of a tri‐generation system.…”
Section: Optimisation Studiesmentioning
confidence: 99%
“…MIP can lead to exponential run times with increasing complexity but enables a global optimum. Hybrid MH and MIP approaches have been also proposed and investigated in Evins and Orehounig (2014) and Stojiljković, Stojiljković, and Blagojević (2014) to enhance the solution finding.…”
Section: Introductionmentioning
confidence: 98%