Simulation of nearly zero energy building microgrid using RES2GEO model : master's thesis

Procjenjuje se da su zgrade u EU odgovorne za 40% potrošene sveukupne energije i 36% emisija CO2 što ih čini velikim potrošačima energije i zagađivačima okoliša, te su iz tog razloga postavljeni novi kriteriji za njihovu izgradnju. Radi se o takozvanim zgradama nulte energetske potrošnje (engl. Nearly zero energy building – NZEB) koje se temelje na potrošnji izuzetno niskih količina energije i pridobivanju energije primarno iz obnovljivih izvora. Svrha ovog rada je provesti tehnoekonomsku analizu energetske opskrbe definiranog stambenog kompleksa. Za izračun energetskih tokova stambenog kompleksa i energetske bilance plitkog geotermalnog ležišta, kao i za određivanje referentnog scenarija korišten je model RES2GEO. Radi se o internom modelu napisanom u programu Python v3.8. Izmjenom parametara referentnog scenarija generirano je mnoštvo razmatranih scenarija, te je za svaki scenarij provedena tehnoekonomska analiza korištenjem programa Python v3.8. i MS Excel. U ovom radu je prikazana analiza scenarija koji najviše utječu na promjenu energetske opskrbe stambenog kompleksa u tehničkom i ekonomskom pogledu, te grafički prikaz analize osjetljivosti u kojoj se može vidjeti utjecaj različitih parametara na isplativost razmatranih scenarija.It is estimated that buildings in EU are responsible for 40% of total energy consumption and 36% of CO2 emissions, making them major energy consumers and polluters. Therefore new criteria has been set for their construction. These are so-called Nearly Zero Energy Buildings (NZEB), which are based on the consumption of extremely low amounts of energy and obtaining energy primarily from renewable energy sources. The purpose of this thesis is to conduct a techno-economic analysis of the energy supply of a defined housing complex. RES2GEO model was used to calculate the energy flows of the housing complex and the energy balance of the shallow geothermal reservoir, as well as to determine the reference scenario. This is an in-house model written in Python v3.8. By changing the parameters of the reference scenario, a multitude of considered scenarios were generated, and for each scenario, a technoeconomic analysis was performed using Python v3.8 and MS Excel. This thesis presents an analysis of scenarios that have the greates effect on the change of energy supply of the housing complex in technical and economic terms and provides a graphical representation of sensitivity analysis where the impact of different parameters on cost-effectiveness of the considered scenarios is clearly visible