Modeling and Optimization of Energy services in Net Zero Energy House

• Main Author: Dao Thi Thu, Hang
• Other Authors: Jalas, Mikko, Dr., Aalto University, Department of Design, Finland, Kemian tekniikan korkeakoulu, School of Chemical Technology, Biotuotteiden ja biotekniikan laitos, Department of Bioproducts and Biosystems, Santos Silva, Carlos Augusto, Prof., Instituto Superio Tecnico, University of Lisbon, Portugal, Paltakari, Jouni, Prof., Aalto University, Department of Bioproducts and Biosystems, Finland, Aalto-yliopisto, Aalto University
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Aalto University 2017
• Subjects: Energy; Net Zero Energy House; energy services; residential energy services; residential energy consumption; life-cycle cost optimal; multiple objectives optimization; genetic algorithm; renewable energy; residential energy system; Arctic
• Online Access: https://aaltodoc.aalto.fi/handle/123456789/28745

The building sector consumes about 40% of primary energy in Europe, of which, residential building accounts for 26% - as the largest single energy consumption. As a result, the building sector plays a decisive role to reduce Europe's energy consumption. This led to the release of European Energy Performance Building Directive in 2010 known as EPBD recast 2010 which introduced the objective that all new buildings - and existing large buildings, by retrofitting – be Net Zero Energy Building (NZEB) from 2020 onwards. As a result, this PhD thesis intends to contribute to the design of better policies that foster the implementation of NZEB concept or Net Zero Energy House (NZEH), as a subset, with a particular emphasis on residential building in Europe. In this context, Portugal and Finland are chosen as the cases of the two climatically distinct European countries (Mediterranean vs. Boreal/Sub-Arctic) that also possess a large socio-economic gap. The thesis proposes that in order to develop policies that lead to the successful NZEH implementation in Europe, a clearly defined energy-service framework with numerical reference values for the residential energy services demand is required. As a result, the thesis proposes an energy service modeling framework for residential energy services: space heating and cooling, water heating, lighting, cooking, kitchen appliances and other media appliances. Additionally, a multi-objective optimization method that uses genetic algorithms is carried out, which can help to determine the optimal choice of energy systems to supply the demand energy services. The optimization objectives combine: minimize the energy system cost and minimize the energy demand. Furthermore, implications for future technology development and policy recommendations are defined with the emphasis on the end-use and demand side of residential energy services. With respect to Portugal, the results are water heat pump is best suited for water heating, whereas biomass boiler is preferable for both water and space ...