Milad Afzalan

Milad Afzalan
Virginia Polytechnic Institute and State University | VT · Department of Civil and Environmental Engineering

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17
Publications
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188
Citations

Publications

Publications (17)
Article
Full-text available
With the widespread adoption of smart meters in buildings, an unprecedented amount of high-resolution energy data is released, which provides opportunities to understand building consumption patterns. Accordingly, research efforts have employed data analytics and machine learning methods for the segmentation of customers based on their load profile...
Article
Full-text available
With the increased adoption of distributed energy resources (DERs) and renewables, such as solar panels at the building level, consumers turn into prosumers with generation capability to supply their on-site demand. The temporal complementarity between supply and demand at the building level provides opportunities for energy exchange between prosum...
Article
Full-text available
Load shapes obtained from smart meter data are commonly utilized to understand daily energy use patterns for adaptive operations in applications such as Demand Response (DR). However, they do not provide information on the underlying causes of specific energy use patterns – i.e., inference on appliances’ time-of-use (ToU) as actionable information....
Conference Paper
Regular monitoring of railway systems is imperative for improving safety and ride quality. To this end, data collection is carried out regularly in the rail industry to document performance and maintenance. The use of machine learning methods in the past recent years has provided opportunities for improved data processing and defect detection and m...
Article
Demand response (DR) is considered an effective approach in mitigating the ever-growing concerns for supplying the electricity peak demand. Recent attempts have shown that the contribution from the aggregate impact of flexible individual residential loads can add flexibility to the power grid as ancillary services. However, current DR schemes do no...
Conference Paper
With the widespread adoption of smart metering infrastructures, household energy consumption segmentation is receiving increasing attention. The objective is to transform the large volume of household daily load shapes into representative patterns through clustering methods, with the aim of program targeting and customer engagement. In the literatu...
Article
Power utilities leverage Demand Response (DR) events to effectively reduce the peak load at critical times with excessive power demand. DR programs are generally categorized as manual or automated from the automation perspective. The opportunities for automated DR in the residential sector have emerged with the integration of smart and connected lo...
Conference Paper
The adoption of smart meters in residential households provides electricity consumption data with high temporal resolution. Considering the wealth of the generated information, data analytics methods can be employed to segment the households based on the timing and magnitude of consumption. Specifically, the resultant load shapes reveal the lifesty...
Article
The emergent context-aware applications in ubiquitous computing demands for obtaining accurate location information of humans or objects in real-time. Indoor location-based services can be delivered through implementing different types of technology, among which is a recent approach that utilizes LED lighting as a medium for Visible Light Communica...
Conference Paper
Condition monitoring of rail infrastructure is an important task to ensure the safety and ride quality. The increasing travel demands of the rail network due to higher miles traveled requires regular monitoring of the infrastructure and efficient processing of the data for timely decision-making. Despite the regular data collection on different par...
Article
Monitoring the temporal changes in the operational states of appliances is a key step in inferring the dynamics of operations in smart homes. This information could be leveraged in a variety of energy management applications including energy breakdown of individual loads, inferring the occupancy patterns, and associating the energy use to occupants...
Article
Spectral clustering algorithms typically require a priori selection of input parameters such as the number of clusters, a scaling parameter for the affinity measure, or ranges of these values for parameter tuning. Despite efforts for automating the process of spectral clustering, the task of grouping data in multi-scale and higher dimensional space...
Preprint
Spectral clustering algorithms typically require a priori selection of input parameters such as the number of clusters, a scaling parameter for the affinity measure, or ranges of these values for parameter tuning. Despite efforts for automating the process of spectral clustering, the task of grouping data in multi-scale and higher dimensional space...
Conference Paper
Power utilities rely on Demand Response (DR) programs in order to shave the peak load at critical times, when there is an excessive demand. In the context of automation, DR programs are categorized as manual or automated. With the emergence of home energy management (HEM) systems that monitor and operate the household appliances, the opportunities...
Conference Paper
Electricity disaggregation, the task of inferring appliances' energy consumption in a building from a few sensing points, has received attention in the energy community. In this paper, we introduce EMBED, a publically available dataset for Energy Monitoring through Building Electricity Disaggregation. EMBED is the most comprehensive fully labeled d...
Conference Paper
Providing users’ location information in indoor environments has great importance for the management of the built environment in energy conservation efforts, facilitating navigation in large and complex places, providing context-aware information, and addressing safety concerns in emergency situations. Various technologies have been proposed to add...
Conference Paper
Full-text available
Following the Northridge earthquake in 1994, widespread damage including brittle cracking was observed in steel structural components; and by that time, the attention of researchers has been shifted towards development of improved connection details to make them less prone to brittle fracture. However, studies have shown that these post-Northridge...

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