Combining a dynamic simulation tool and a multi-criteria decision aiding algorithm for improving existing District Heating

Autor: Patrick Meyer, Bruno Lacarrière, Vincent Dessarthe, Mohamed Tahar Mabrouk, Pierrick Haurant
Přispěvatelé: Optimisation - Système - Energie (GEPEA-OSE), Laboratoire de génie des procédés - environnement - agroalimentaire (GEPEA), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Ecole Polytechnique de l'Université de Nantes (EPUN), Université de Nantes (UN)-Université de Nantes (UN)-Institut Universitaire de Technologie - Nantes (IUT Nantes), Université de Nantes (UN)-Institut Universitaire de Technologie Saint-Nazaire (IUT Saint-Nazaire), Université de Nantes (UN)-Institut Universitaire de Technologie - La Roche-sur-Yon (IUT La Roche-sur-Yon), Université de Nantes (UN)-Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Université Bretagne Loire (UBL)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Université Bretagne Loire (UBL), Département Systèmes Energétiques et Environnement (IMT Atlantique - DSEE), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI)
Rok vydání: 2018
Předmět:
Zdroj: Energy Procedia
Energy Procedia, Elsevier, 2018, 149, pp.266-275. ⟨10.1016/j.egypro.2018.08.191⟩
ISSN: 1876-6102
DOI: 10.1016/j.egypro.2018.08.191
Popis: International audience; District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand-outdoor temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. Abstract The work aims to evaluate the recovering potential of excess heat in the return pipe of a district heating (DH) for heating some substations. The proposed method combines a DH simulation tool and a multi-criteria decision aiding algorithm. It is based on the analysis of the measured return temperatures at each sub-station in order to identify those with high potential of efficiency gains by using the return flow (with support of the supply pipe when needed). Combinations of substations from this set of eligible ones define potential scenarios of connection to the return pipe. The impacts of each scenario on the DH operational performance and the energy savings are evaluated with a detailed hydro-thermal model. The technical parameters and the energy efficiency are not the only points of view in the selection process "of best compromise" scenarios for the improvement of the DH, so that we propose a complex decision aiding process, involving multiple criteria, dealing with different points of view (economic, energy, technical…) and different decision makers. The evaluations of the scenarios on the criteria are summed up in a so-called performance table and aggregated by an outranking model (MR-Sort) to identify relevant scenarios. This methodology is illustrated by the example of a part of the DH in Nantes (France). Interpretation of data from substations of a specific branch showed the potential of connecting some of them to the return pipe. Six scenarios were generated and evaluated with four criteria. Then, the Multi-criteria Decision Aiding method associated to two actors who have different priorities lead to not obvious results at a first glance. Abstract The work aims to evaluate the recovering potential of excess heat in the return pipe of a district heating (DH) for heating some substations. The proposed method combines a DH simulation tool and a multi-criteria decision aiding algorithm. It is based on the analysis of the measured return temperatures at each sub-station in order to identify those with high potential of efficiency gains by using the return flow (with support of the supply pipe when needed). Combinations of substations from this set of eligible ones define potential scenarios of connection to the return pipe. The impacts of each scenario on the DH operational performance and the energy savings are evaluated with a detailed hydro-thermal model. The technical parameters and the energy efficiency are not the only points of view in the selection process "of best compromise" scenarios for the improvement of the DH, so that we propose a complex decision aiding process, involving multiple criteria, dealing with different points of view (economic, energy, technical…) and different decision makers. The evaluations of the scenarios on the criteria are summed up in a so-called performance table and aggregated by an outranking model (MR-Sort) to identify relevant scenarios. This methodology is illustrated by the example of a part of the DH in Nantes (France). Interpretation of data from substations of a specific branch showed the potential of connecting some of them to the return pipe. Six scenarios were generated and evaluated with four criteria. Then, the Multi-criteria Decision Aiding method associated to two actors who have different priorities lead to not obvious results at a first glance.
Databáze: OpenAIRE
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