相关论文: Energy Disaggregation for SMEs using Recurrence Qu…

We consider a resource allocation problem involving a large number of agents with individual constraints subject to privacy, and a central operator whose objective is to optimizing a global, possibly non-convex, cost while satisfying the…

In this article we present an unsupervised low-frequency method aimed at detecting and disaggregating the power used by Cumulative Water Heaters (CWH) in residential homes. Our model circumvents the inherent difficulty of unsupervised…

The rapid deployment of renewable generations such as photovoltaic (PV) generations brings great challenges to the resiliency of existing power systems. Because PV generations are volatile and typically invisible to the power system…

As we transition to renewable energy sources, addressing their inflexibility during peak demand becomes crucial. It is therefore important to reduce the peak load placed on our energy system. For households, this entails spreading…

Non-Intrusive Load Monitoring (NILM) aims to estimate appliance-level consumption from aggregate electrical signals recorded at a single measurement point. In recent years, the field has increasingly adopted deep learning approaches;…

Non-intrusive load monitoring (NILM) is an important topic in smart-grid and smart-home. Many energy disaggregation algorithms have been proposed to detect various individual appliances from one aggregated signal observation. However, few…

This paper investigates the energy management problem for multiple self-interested users, each with renewable energy generation as well as both the fixed and controllable loads, that all share a common energy storage system (ESS). The…

Energy disaggregation or nonintrusive load monitoring (NILM), is a single-input blind source discrimination problem, aims to interpret the mains user electricity consumption into appliance level measurement. This article presents a new…

High-resolution energy consumption and emissions datasets are essential for localized policy-making, resource optimization, and climate action planning. They enable municipalities to monitor mitigation strategies and foster engagement among…

Many countries are rolling out smart electricity meters. These measure a home's total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with…

This paper provides a formalization of the energy disaggregation problem for particle swarm optimization and shows the successful application of particle swarm optimization for disaggregation in a multi-tenant commercial building. The…

The data collected by smart meters contain a lot of useful information. One potential use of the data is to track the energy consumptions and operating statuses of major home appliances.The results will enable homeowners to make sound…

Non-intrusive load monitoring (NILM) identifies the status and power consumption of various household appliances by disaggregating the total power usage signal of an entire house. Efficient and accurate load monitoring facilitates user…

Producing reliable estimates of health and demographic indicators at fine areal scales is crucial for examining heterogeneity and supporting localized health policy. However, many surveys release outcomes only at coarser administrative…

Memory disaggregation is being considered as a strong alternative to traditional architecture to deal with the memory under-utilization in data centers. Disaggregated memory can adapt to dynamically changing memory requirements for the data…

Future wireless systems are expected to deliver significantly higher quality-of-service (QoS) albeit with fewer energy resources for diverse, already existing and also novel wireless applications. The optimal resource allocation for a…

As sensor networks for health monitoring become more prevalent, so will the need to control their usage and consumption of energy. This paper presents a method which leverages the algorithm's performance and energy consumption. By utilising…

With rapid advancements in the Internet of Things (IoT) paradigm, electrical devices in the near future is expected to have IoT capabilities. This enables fine-grained tracking of individual energy consumption data of such devices, offering…

Recurrence Quantification Analysis (RQA) can help to detect significant events and phase transitions of a dynamical system, but choosing a suitable set of parameters is crucial for the success. From recurrence plots different RQA variables…

Measuring energy consumption is a challenging task faced by developers when building mobile apps. This paper presents EMaaS: a system that provides reliable energy measurements for mobile applications, without requiring a complex setup. It…