Real-Time Recognition Non-Intrusive Electrical Appliance Monitoring Algorithm for a Residential Building Energy Management System

The concern of energy price hikes and the impact of climate change because of energy generation and usage forms the basis for residential building energy conservation. Existing energy meters do not provide much information about the energy usage of the individual appliance apart from its power rating. The detection of the appliance energy usage will not only help in energy conservation, but also facilitate the demand response (DR) market participation as well as being one way of building energy conservation. However, energy usage by individual appliance is quite difficult to estimate. This paper proposes a novel approach: an unsupervised disaggregation method, which is a variant of the hidden Markov model (HMM), to detect an appliance and its operation state based on practicable measurable parameters from the household energy meter. Performing experiments in a practical environment validates our proposed method. Our results show that our model can provide appliance detection and power usage information in a non-intrusive manner, which is ideal for enabling power conservation efforts and participation in the demand response market.1176Ysciescopu

A transition from manual to Intelligent Automated power system operation -A Indicative Review

This paper reviews the transition of the power system operation from the traditional manual mode of power system operations to the level where automation using Internet of Things (IOT) and intelligence using Artificial Intelligence (AI) is implemented. To make the review paper brief only indicative papers are chosen to cover multiple power system operation based implementation. Care is taken there is lesser repeatation of similar technology or application be reviewed. The indicative review is to take only a representative literature to bypass scrutinizing multiple literatures with similar objectives and methods. A brief review of the slow transition from the traditional to the intelligent automated way of carrying out power system operations like the energy audit, load forecasting, fault detection, power quality control, smart grid technology, islanding detection, energy management etc is discussed .The Mechanical Engineering Perspective on the basis of applications would be noticed in the paper although the energy management and power delivery concepts are electrical

Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions and Research Directions

Energy management systems are designed to monitor, optimize, and control the smart grid energy market. Demand-side management, considered as an essential part of the energy management system, can enable utility market operators to make better management decisions for energy trading between consumers and the operator. In this system, a priori knowledge about the energy load pattern can help reshape the load and cut the energy demand curve, thus allowing a better management and distribution of the energy in smart grid energy systems. Designing a computationally intelligent load forecasting (ILF) system is often a primary goal of energy demand management. This study explores the state of the art of computationally intelligent (i.e., machine learning) methods that are applied in load forecasting in terms of their classification and evaluation for sustainable operation of the overall energy management system. More than 50 research papers related to the subject identified in existing literature are classified into two categories: namely the single and the hybrid computational intelligence (CI)-based load forecasting technique. The advantages and disadvantages of each individual techniques also discussed to encapsulate them into the perspective into the energy management research. The identified methods have been further investigated by a qualitative analysis based on the accuracy of the prediction, which confirms the dominance of hybrid forecasting methods, which are often applied as metaheurstic algorithms considering the different optimization techniques over single model approaches. Based on extensive surveys, the review paper predicts a continuous future expansion of such literature on different CI approaches and their optimizations with both heuristic and metaheuristic methods used for energy load forecasting and their potential utilization in real-time smart energy management grids to address future challenges in energy demand managemen

Temporary Load Shedding - Optimization of power distribution system using load shedding Techniques

In today’s world, electrical energy is a necessity. The dependency on electricity is increasing day by day which caused the system to work under a stress state close to stability limits and disturbances. An efficient power system supplying electrical energy must be reliable, stable, secure, and reasonable to meet consumer needs. The power demand depends on several factors and weather is one of the main in them. The thesis is done with the cooperation of Arva As. for the Tromsøya region in northern Norway. In Northern Norway, during the winter season, the temperature falls to -20˚C which eventually causes the rise in demand for electricity to meet the heating needs. The heating of households plays a big role in increasing demand. To avoid contingency and keep the distribution grid stable during the winter season a temporary load shedding scheme has been proposed by using the load curves and grid model that was analyzed through power flow analysis. It includes procedures for detection of voltage stability on buses with voltage stability indexes and plans to temporarily shut the heating system and sources to avoid the stress on the grid in peak hours with available communication possibilities

Optimal Home Energy Management System for Committed Power Exchange Considering Renewable Generations

This thesis addresses the complexity of SH operation and local renewable resources optimum sizing. The effect of different criteria and components of SH on the size of renewable resources and cost of electricity is investigated. Operation of SH with the optimum size of renewable resources is evaluated to study SH annual cost. The effectiveness of SH with committed exchange power functionality is studied for minimizing cost while responding to DR programs

Digital Twin Concept, Method and Technical Framework for Smart Meters

Smart meters connect smart grid electricity suppliers and users. Smart meters have become a research hotspot as smart grid applications like demand response, power theft prevention, power quality monitoring, peak valley time of use prices, and peer-to-peer (P2P) energy trading have grown. But, as the carriers of these functions, smart meters have technical problems such as limited computing resources, difficulty in upgrading, and high costs, which to some extent restrict the further development of smart grid applications. To address these issues, this study offers a container-based digital twin (CDT) approach for smart meters, which not only increases the user-facing computing resources of smart meters but also simplifies and lowers the overall cost and technical complexity of meter changes. In order to further validate the effectiveness of this method in real-time applications on the smart grid user side, this article tested and analyzed the communication performance of the digital twin system in three areas: remote application services, peer-to-peer transactions, and real-time user request services. The experimental results show that the CDT method proposed in this paper meets the basic requirements of smart grid user-side applications for real-time communication. The container is deployed in the cloud, and the average time required to complete 100 P2P communications using our smart meter structure is less than 2.4 seconds, while the average time required for existing smart meter structures to complete the same number of P2P communications is 208 seconds. Finally, applications, the future development direction of the digital twin method, and technology architecture are projected