Development of a Simple Model to Estimate Heating Demand at a District Level

Resumen

The energy rehabilitation of buildings has great potential to significantly reduce energy consumption in the building sector. In this sense, the Energy Performance of Buildings Directive 2010/31/EU, recently updated in Directive 2018/844/EU, represented a turning point in the promotion of energy efficiency in buildings in the EU, introducing legal requirements for both new and existing buildings. This directive introduced important concepts such as the optimal cost of investments and the nearly zero energy building (nZEB). For this purpose, it becomes necessary to develop extensive design processes with an optimization perspective that covers all possible aspects in matters of building design (envelope, shading, components of cooling and heating systems, regulation criteria, among others), starting from the most initial design phases, to comply with the prescriptions of the Directive, ensuring the thermal comfort of the occupants. In addition, the need of speeding up the emissions reduction rate associated with buildings has led to transcending the individual limit of each building, applying the nZEB principle at the neighborhood or district scale, from both an architectural and urban planning perspective. This has given rise to the concept of Net-Zero Energy Districts. Software tools for the energy simulation of buildings allow estimating the thermal demand of different alternatives and obtaining optimal designs. However, they require many evaluations at a high computational cost, making the analysis practically impossible when the object of study is entire neighborhoods. Therefore, there is a need for simple methods for estimating energy demands that offer sufficiently accurate results. One of the main steady-state methods for calculating energy demand is the degree-days method. However, this model has limitations that must be known to consider its scope and applicability. Among the main uncertainties of this method is the selection of the base temperature, which in practice will be affected by the level of efficiency of the evaluated building. Although there have been approaches for calculating a variable base temperature, the tendency is to use a generic base temperature, without considering the specific characteristics of the analyzed building. This has a significant impact on the demands estimated using this method, which tend to be significantly overestimated. In this sense, the present work aims to develop a simple model for calculating district heating demand. To this end, the most relevant design and operational aspects for residential buildings were taken into consideration, leading to the selection of 7 independent parameters. A total of 5,000 simulations have been carried out, based on a multi-family building located in the neighborhood of Otxarkoaga (Bilbao). Using linear regression techniques, a relationship between these independent variables and the base temperature has been determined. The heating demand can be consequently determined by applying the degree days formula. The results show the potential of this prediction method as an effective alternative tool to support decision-making on energy rehabilitation solutions through an initial estimation of heating demand with good precision.