Load Disaggregation & Smart Meter Analytics
Research on hourly smart meter data, separating space-heating and non-space-heating electricity demand, and interpreting energy demand patterns in public buildings.
Research
My doctoral research focuses on how public buildings can be analyzed as flexible energy resources, especially where smart meter data, electric heating, weather sensitivity, and demand response are important.
Research on hourly smart meter data, separating space-heating and non-space-heating electricity demand, and interpreting energy demand patterns in public buildings.
Work on weather-normalized analysis, multivariate weather features, heating demand estimation, outdoor temperature sensitivity, and robust building energy analysis methods.
Analysis of flexible electricity demand from electric heating loads in public buildings, with attention to temporal flexibility, demand response potential, and practical limits in observed data.
Research interests include buildings as virtual power plants, flexibility exchange between buildings, energy communities, renewable energy integration, and coordinated energy management.
Research directions
These directions describe active doctoral work, method development, and related research interests.
Doctoral research
Data-driven analysis of hourly smart meter data to separate space-heating and non-space-heating electricity demand in buildings, with emphasis on public buildings and interpretable energy-use patterns.
Research direction
Development of weather-augmented approaches for estimating heating-related electricity demand using outdoor temperature and additional weather variables to improve building energy analysis.
Ongoing research
Quantification of electric heating flexibility and demand response potential in public buildings, with attention to temporal flexibility, grid-aware operation, and practical limitations in observed data.
Future research direction
Research interest in buildings as flexible energy resources within energy communities, virtual power plants, renewable energy integration, and coordinated energy management.
Method development
Interest in reproducible Python and R workflows for smart meter analytics, building energy analysis, energy demand estimation, and transparent research communication.
Topics