Development of comprehensive M&V software for improved whole facility energy saving with risk assessment / Nor Shahida Razali

In Malaysia, buildings consumed 14.3% of total energy demand, 48% of electricity use and correspondingly are also responsible for carbon emission. Since, Energy Conservative Measure (ECM) have been adopted as a key element in reducing energy use and carbon emission. However, the Measurement and V...

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Bibliographic Details
Main Author: Razali, Nor Shahida
Format: Thesis
Language:English
Published: 2018
Online Access:https://ir.uitm.edu.my/id/eprint/86294/1/86294.pdf
https://ir.uitm.edu.my/id/eprint/86294/
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Summary:In Malaysia, buildings consumed 14.3% of total energy demand, 48% of electricity use and correspondingly are also responsible for carbon emission. Since, Energy Conservative Measure (ECM) have been adopted as a key element in reducing energy use and carbon emission. However, the Measurement and Verification (M&V) of the savings from the ECMs are still new practice particularly in Malaysia. Besides, it did not consider risk assessment in its evaluation. Imprecise savings determination due to incomplete M&V evaluation and uncertain factors may lead practitioners in making inappropriate investment risk decisions. Furthermore, there is lack of commercial M&V software equipped with risk assessment available to assist practitioners in performing M&V activities. This research presents two comprehensive and user-friendly M&V software, i.e. Module 1 and Module 2. Module 1 is established to perform the M&V activities aligned with International Performance Measurement and Verification Protocol (IPMVP). Module 2 is developed to provide comprehensive framework by computing and evaluating the impact of ECMs on the building in terms of energy saving, cost saving, payback period and financial indicator, i.e. NPV and IRR. Module 2 used Monte Carlo Simulation (MCS) as computation engine. Within the developed software, regression technique is adopted in its methodology. From the developed M&V software, regression technique revealed that more than one parameter are actually affecting energy use in building. It can be validates based on highest value of 0.87 for R2 and lowest value of 0.0161 for CV-RMSE. Further analysis showed that energy savings for each case are deemed to be statistically valid since it is larger than twice standard error of the baseline value. From the findings, Module 2 only have a small percentage error compared to Module 1. The percentage error in energy savings for case1, case 2 and case 3 is 0.052%, 0.183% and 0.388% respectively. At the 95% confidence level, Module 2 provides a wider investment possibility and a narrower precision interval, hence better accuracy. It is considered that the developed M&V software can provide a comprehensive M&V activity equipped with broaden savings and investment risk framework to the practitioners.