相关论文: Appliance Operation Modes Identification Using Cyc…
Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their…
Analyzing smart meter data to understand energy consumption patterns helps utilities and energy providers perform customized demand response operations. Existing energy consumption segmentation techniques use assumptions that could result…
A significant portion of electricity consumed worldwide is used to power thermostatically controlled loads (TCLs) such as air conditioners, refrigerators, and water heaters. Because the short-term timing of operation of such systems is…
Non-intrusive load monitoring (NILM) has been extensively researched over the last decade. The objective of NILM is to identify the power consumption of individual appliances and to detect when particular devices are on or off from…
Non-Intrusive Load Monitoring (NILM) is an energy efficiency technique to track electricity consumption of an individual appliance in a household by one aggregated single, such as building level meter readings. The goal of NILM is to…
A smart home energy management system (HEMS) can contribute towards reducing the energy costs of customers; however, HEMS suffers from uncertainty in both energy generation and consumption patterns. In this paper, we propose a sequence to…
Increasing global energy demand and renewable integration complexity have placed buildings at the center of sustainable energy management. We present a three-step reinforcement learning(RL)-based Building Energy Management System (BEMS)…
This study explores the interaction between aggregators and building occupants in activating flexibility through Demand Response (DR) programs, with a focus on reinforcing the resilience of the energy system considering the uncertainties…
Cache-assisted ultra-dense mobile edge computing (MEC) networks are a promising solution for meeting the increasing demands of numerous Internet-of-Things mobile devices (IMDs). To address the complex interferences caused by small base…
The evolution of the power grid towards the so-called Smart Grid, where information technologies help improve the efficiency of electricity production, distribution and consumption, allows to use the fine-grained control brought by the…
Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data…
The understanding of the buildings operation has become a challenging task due to the large amount of data recorded in energy efficient buildings. Still, today the experts use visual tools for analyzing the data. In order to make the task…
Under Smart Grid environment, the consumers may respond to incentive--based smart energy tariffs for a particular consumption pattern. Demand Response (DR) is a portfolio of signaling schemes from the utility to the consumers for load…
Process mining provides various algorithms to analyze process executions based on event data. Process discovery, the most prominent category of process mining techniques, aims to discover process models from event logs, however, it leads to…
Increased deployment of residential smart meters has made it possible to record energy consumption data on short intervals. These data, if used efficiently, carry valuable information for managing power demand and increasing energy…
Energy disaggregation determines the energy consumption of individual appliances from the total demand signal, which is recorded using a single monitoring device. There are varied approaches to this problem, which are applied to different…
Detecting anomalies in Internet of Things (IoT) networks is a critical security challenge, often hampered by highly imbalanced and diverse network traffic datasets. Standard classifiers struggle to perform well across all traffic types.…
Activity recognition, as an important component of behavioral monitoring and intervention, has attracted enormous attention, especially in Mobile Cloud Computing (MCC) and Remote Health Monitoring (RHM) paradigms. While recently resource…
One of the most promising approaches for complex technical systems analysis employs ensemble methods of classification. Ensemble methods enable to build a reliable decision rules for feature space classification in the presence of many…
Timely processing has been increasingly required on smart IoT devices, which leads to directly implementing information processing tasks on an IoT device for bandwidth savings and privacy assurance. Particularly, monitoring and tracking the…