Hi again everyone!
I can’t believe that today’s blog is already about week 5 and week 6 of my internship, which means it has been more than half of my internship period!
The last two weeks were less hectic compared to the previous weeks. In these two weeks, I mostly spent my time doing simulation, data analysis, and data organization. After my seniors debugged the ECM 72 for hot water service, my simulation result for the energy and electricity saving improved a lot, which directly decreased the payback years. However, before continuing with the packaged ECM simulation, I returned to finish simulating the individual ECM first. I realized that by doing this, I could thoroughly assess the potential and drawbacks of each ECM. Out of the nearly 30 ECM list that my senior previously gave, I managed to simulate all 19 ECMs that were compatible with residential projects. The rest 10 ECMs either did not produce any data because the projects did not use the technology, such as ECM 75 (replace RTUs with units that use evaporative cooling) or ECM 74 (replace CAV with VAV for packaged single-zone heat pump system), or there were several same technologies with only different efficiencies, such as ECM 19, 20, and 21 were all applying wall insulation but with different insulation R-value.
As a result, I managed to discover the potential of ECM 51 that worked to upgrade the whole system HVAC to a single-zone heat pump (11.0 EER, 3.3 COP). When combined with the ECM 72 (hot water service), it decreased the natural gas consumption by up to 90%, which supported the clean energy conversion target. Thus, for the most updated result, the combination of ECM 3 (upgrade to LED), 72 (hot water service), 51 (upgrade to single zone-heat pump), 23 (upgrade to windows with U-factor 0.25 & SHGC 0.18), 86 (add window film), and 88 (enable natural ventilation with windows) increased energy saving and reduced GHG emission by 40%-45%, decreased natural gas consumption by approximately 90%, and resulted in $3 energy cost saving per meter-squared.
However, the problem with the aforementioned ECM package was the extremely high payback year with an estimation of 90 years. This payback cost problem persisted since the beginning of the project. For each ECM, the payback year ranged from less than a year to more than 100 years. This was usually due to 2 possibilities: the expensive initial investment cost and/or the feature was ineffective, which was measured from the low energy saving cost per meter squared. For instance, the payback year for ECM 16 (reroof and roof with insulation R24.83) was approximately 100 years, which was due to the expensive initial investment cost that reached up to $50,000 and up to $2.5 energy-cost saving per meter squared.
Contrastingly, an example of low payback year is ECM 36 (adding ceiling fan) with only $200-$800 investment cost and $0-$2.5 energy cost-saving per meter squared, which resulted in only 1-5 years of payback year.
Thus, for this week and last week, aside from finishing the individual ECM simulation, I simulated several packages to optimize the retrofitting cost as well as re-analyzed all the previous simulation data to include the investment cost and energy saving cost per meter squared. At this point, I almost reached the target of clean energy conversion by reducing natural gas consumption by 90%. Even though there was still an increase in electricity consumption by up to 20%, it could still be helped using the PV potential generation simulation. Therefore, my target for the next few weeks is to start on my PV potential simulation as well as investigating different ECM packages to limit the payback year to below 50 years.