A5082756125- Smart Grid Energy Management
- Indoor and Outdoor Localization Technologies
- Energy, Environment, and Transportation Policies
- Speech and Audio Processing
- Energy Load and Power Forecasting
- Human Mobility and Location-Based Analysis
- Remote Sensing and LiDAR Applications
- Energy Efficiency and Management
- Building Energy and Comfort Optimization
- Robotics and Sensor-Based Localization
Oak Ridge National Laboratory
2023-2024
The University of Texas at Austin
2023-2024
National Transportation Research Center
2023
Machine learning (ML) solutions to indoor localization problems have become popular in recent years due high positioning accuracy and low cost of implementation. This paper proposes a novel local nonparametric approach for solving localizations from high-dimensional Received Signal Strength Indicator (RSSI) values. Our consists sequence classification algorithms that sequentially narrows down the possible space location into smaller neighborhoods. The idea this sequential method is similar...
Increasing fuel prices and capacity investment deferral place an increasing demand for peak reduction from distribution level systems. Residential commercial devices, such as HVAC systems water heaters, are increasingly involved in load control programs, their use may generate synchronization rebound effects, artificial peaks caused by device optimization. While there have been concerns over synchronization, few studies quantify the extent of this effect with numerical values. In study, we...
Building electrification is putting pressure on distribution grid worldwide. Peak reduction an important concern that can help reduce the growing stress and allow to defer investments in new capacity. Water heaters represent a convenient way of reducing peak because they are less dependent weather, their storage volume allows for asynchronous water heating hot use. Previous empirical studies investigated ability through adjustment temperature setpoint. However, not all equipment vendors...
Machine learning (ML) solutions to indoor localization problems have become popular in recent years due high positioning accuracy and low cost of implementation. This paper proposes a novel local nonparametric approach for solving localizations from high-dimensional Received Signal Strength Indicator (RSSI) values. Our consists sequence classification algorithms that sequentially narrows down the possible space location into smaller neighborhoods. The idea this sequential method is similar...
Demand response is a growing concept in light of the internet things and an increasing need for grid flexibility. Water heaters are one preferred devices providing demand services peak management due to their capability store energy. The efficient use water requires consideration associated load effects such as synchronization device schedules rebound effect. These present significant challenge. Despite importance mentioned heater queuing scheduling, there has been no effort quantify...