Local Versus National: Designing Supply Systems For Individual Net Zero Energy Buildings With Flexible Electricity Prices
Free (open access)
763 - 774
C. Milan, M. P. Nielsen & C. Bojesen
The building sector has obtained increased awareness throughout the last decades due to its notable contribution to global greenhouse gas (GHG) emissions. One approach to decrease these emissions is the concept of net zero energy buildings (Net ZEB), which produce as much energy out of renewable sources as they consume through public grid connections on an annual balance. A global design solution for these buildings does not exist, since the energy resource availability is different everywhere. In earlier publications a methodology was presented which allows for the cost optimal design of individual energy supply systems based on on-site weather and building conditions, as well as considering the expected energy consumption profile. However, local planning processes are problematic if they do not take regional or national impacts into account. Given the grid connection, the local building solution also has an impact on a national scale by exchanging electricity. Therefore it is important to implement respective grid loads into the planning process in order to avoid technology choices, which might counteract grid stability or cost inefficiencies at other sites. The aim of this paper is to adapt the earlier proposed methodology by integrating flexible national electricity prices and thus taking account for the aforementioned effects. The methodology is applied in a case study for a single family house under Danish conditions. The results show that the system configuration might not necessarily be changed but an adaptation in the mode of operation is important and could even lead to cost reductions when allowing for flexible tariffs. Keywords: net zero energy buildings, zero energy buildings, cost optimization, renewable energies, supply system design, MILP, linear programming.
net zero energy buildings, zero energy buildings, cost optimization, renewable energies, supply system design, MILP, linear programming.