Methodologie d'evaluation de la demande de chaleur des groupes de batiments dans le cadre d'une etude de faisabilite du chauffage urbain

In the context of energy efficiency improvements to pulp and paper mills, process modifications allow to free low quality steam. This kind of low pressure and temperature steam is often found to be in excess in mills. New opportunities to use this energy could be created by gathering plants along with local communities and other enterprises into eco-industrial clusters. Following this proposition, district heating is an interesting technology that could be developed. It consists in supplying buildings with steam or hot water from one or more central heating plants through a series of canalization, generally underground. The supplied energy is used mostly for space heating but it can also be used with appliances specially designed for this purpose.;The objective of this work is to develop a methodology that can assess the feasibility of district heating quickly and using easily accessible data. It was mainly designed to determine the heat consumption, which is especially critical as to decide whether or not to implement this technology. The focus is primarily directed on residential buildings, but another methodology is also developed to take into account the commercial and institutional buildings demand.;An analysis of the sources of data revealed a certain redundancy among them. Therefore, four different computation procedures were developed to obtain the heat consumption of residential buildings: • C1, the first procedure, is the most time consuming one. It is also the one that uses the most specific information from the case: aerial photographs, census data (building year of construction and type (single family detached, single family attached, apartments or mobile homes)) and punctual on-site verification from the target area. National estimates of thermal requirements values are also used. • C2, the second procedure, is less specific than C1, but is much less time consuming to achieve. The local data sources used are: aerial photographs and census data from the case. While the national ones are: estimates of the building heating surfaces and thermal requirements. • C3 and C4, are the easiest procedures. Those two are very similar. The specific data used in these cases are census data from the locations under study. National data used for C3 are building surface estimates and thermal requirements values while C4 only uses thermal requirement values which are slightly different from those of C3. A further analysis revealed later that these two calculations yielded the same results. Therefore, since C3 is slightly more complicated to implement, it was removed from further analysis.;Using three procedures thus ensures the stability of the methodology when the three results are the same order of magnitude. An average of the three results gives a good estimation of the consumption.;Under certain conditions, this type of heating is cheaper and more environmentally friendly for several reasons including the facts that one central boiler plant is more efficient and has lower pollutant emissions due to better combustion control. Moreover, it can be adapted to multiple fuels that are locally available such as biomass around some pulp and paper mills. However, to insure that the savings occur, the heat demand must be sufficiently high and concentrated. Therefore, detailed feasibility studies shall be conducted to justify significant investments. Such studies require a lot of time not to mention that they necessitate a lot of data which can be difficult to obtain.;The methodology was then applied to four study cases. One of them has already been the subject of a detailed district heating assessment feasibility study. It is used to validate the results obtained with the new methodology. The three other cases are rather used to test different conditions (number, density, type and year of construction of buildings). The validation results showed that the methodology can determine the heat consumption to about 20% of the baseline value. It also determines the total heating surface to about 5%. The three other study cases, A, B and C, have confirmed that possibility of applying the methodology in various conditions. Case A showed lower gaps between the four procedures when the rate of single family houses is lower. Since this rate is high in the validation case, better results can be expected for cases where the number of single family houses is low, such as in case A. In case B, the global results showed a particularly low gap between the four procedures with a maximum of 5%. However, an analysis of individual dissemination areas showed higher positive and negative gaps, which, when they are summed, compensate for the individual errors. The bigger errors in this case are explained by the fact that the apartments in this city are larger than the national average. Case C presented an additional challenge since no aerial photo was available. It has nevertheless been possible to realize two calculation procedures, C3 and C4, which provided a broad approximation of the consumption.;For the commercial sector, a similar methodology to that of the residential sector is developed. However, the lack of global data has prescribed the individual processing of every building. This approach is also justified by the fact that commercial and institutional buildings are less numerous and have higher consumption. Due to the extended duration of this type of approach, only the validation and case Aare realized. The first one confirmed the better results than the ones from the residential sector with a gap of 7% compared to the consumption baseline. The results from case A showed the areas where the heat consumption is higher. Furthermore, it showed that the commercial and institutional demand accounts for 10% to 40% of the total heat demand.;The integration of the results obtained into a district heating feasibility study is then discussed. A joint analysis of the residential and the commercial and institutional sectors showed the importance of considering each building's heat consumption for the planning of a district heating network. The profitability of the study cases is considered in relation to the thermal thresholds suggested in the literature.