OPTIMIZATION OF POLYGENERATION SYSTEMS SERVING A CLUSTER OF BUILDINGS

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The optimization of combined energy systems for the production and distribution of warm and cold fluids to civil users is very complex; two possible configurations, i.e. the small single units for individual buildings and the large plants integrated with district heating networks, can be essentially considered, especially in cold climates. Dealing with such a complex problem, involving a very large number of variables, requires efficient algorithms and resolution techniques.The present chapter illustrates a Mixed Integer Linear Program (MILP)1 approach to the optimization of synthesis, design and operation for CHCP-based μ-grids including thermal energy storages.A novel approach is presented, oriented to design and optimize district energy systems, assuming to have detailed data available as concerns the energy consumption profiles and the location of buildings; the method evaluates a number of feasible layouts for the heat distribution network and relies upon pre-defined cost models for plant components in order to identify the most profitable plant design and operation.The method is implemented into a compiled tool and is validated with reference to a case study, represented by a cluster of buildings interconnected via a heat network and situated over a small area (maximum distance in the order of 1.5 km). A relevant profit potential resulted for the examining buildings, and the results appear consistent with respect to those achievable through alternative heuristic or ―manual methods.
Original languageEnglish
Title of host publicationLinear Programming - New Frontiers in Theory and Applications
Pages327-350
Number of pages24
Publication statusPublished - 2012

All Science Journal Classification (ASJC) codes

  • Mathematics(all)

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    Piacentino, A., Gallea, R., Cardona, F., & Barbaro, C. (2012). OPTIMIZATION OF POLYGENERATION SYSTEMS SERVING A CLUSTER OF BUILDINGS. In Linear Programming - New Frontiers in Theory and Applications (pp. 327-350)