Load Monitoring for Benefit Assessment

In this study, we monitored power consumption to analyze the impact of energy usage on people's well-being. Data analytics is playing a key role in grid operation and the benefits derived from it. We use change point detection techniques to identify instances where power consumption time-series significantly change. Wavelets and adaptive chisquare and Ljung-Box tests are computed to detect these changes using real-world data. It has been shown that there is a strong positive correlation between quality of life and electricity consumption in impoverished countries. Once different levels of consumption are identified due to the use of different appliances, citizens well-being derived from these levels are linked to the relevant elements described in the Gallup-Healthways Report. Furthermore, it is important to come up with methodologies that rely on affordable meters, and thus allow users to manage their power consumption in a distributed manner and maximize their well-being.