scholarly journals An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

Energies ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 190 ◽  
Author(s):  
Hafiz Hussain ◽  
Nadeem Javaid ◽  
Sohail Iqbal ◽  
Qadeer Hasan ◽  
Khursheed Aurangzeb ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Management System ◽  
Demand Side Management ◽  
Demand Side ◽  
Home Energy Management

scholarly journals Demand Side Management Techniques for Home Energy Management Systems for Smart Cities

2021 ◽  
Vol 13 (21) ◽  
pp. 11740
Author(s):  
Muhammad Majid Hussain ◽  
Rizwan Akram ◽  
Zulfiqar Ali Memon ◽  
Mian Hammad Nazir ◽  
Waqas Javed ◽  
...  
Keyword(s):  
Energy Management ◽  
Smart Grids ◽  
Management System ◽  
Smart Cities ◽  
Demand Side Management ◽  
Management Systems ◽  
Demand Side ◽  
Pv System ◽  
Energy Management Systems ◽  
Home Energy Management

In this paper, three distinct distributed energy resources (DERs) modules have been built based on demand side management (DSM), and their use in power management of dwelling in future smart cities has been investigated. The investigated modules for DERs system are: incorporation of load shedding, reduction of grid penetration with renewable energy systems (RES), and implementation of home energy management systems (HEMS). The suggested approaches offer new potential for improving demand side efficiency and helping to minimize energy demand during peak hours. The main aim of this work was to investigate and explore how a specific DSM strategy for DER may assist in reducing energy usage while increasing efficiency by utilizing new developing technology. The Electrical Power System Analysis (ETAP) software was used to model and assess the integration of distributed generation, such as RES, in order to use local power storage. An energy management system has been used to evaluate a PV system with an individual household load, which proved beneficial when evaluating its potential to generate about 20–25% of the total domestic load. In this study, we have investigated how smart home appliances’ energy consumption may be minimized and explained why a management system is required to optimally utilize a PV system. Furthermore, the effect of integration of wind turbines to power networks to reduce the load on the main power grid has also been studied. The study revealed that smart grids improve energy efficiency, security, and management whilst creating environmental awareness for consumers with regards to power usage.

scholarly journals A Smart Home Energy Management System Using Two-Stage Non-Intrusive Appliance Load Monitoring over Fog-Cloud Analytics Based on Tridium’s Niagara Framework for Residential Demand-Side Management

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2883
Author(s):  
Yung-Yao Chen ◽  
Ming-Hung Chen ◽  
Che-Ming Chang ◽  
Fu-Sheng Chang ◽  
Yu-Hsiu Lin
Keyword(s):  
Cloud Computing ◽  
Energy Management ◽  
Management System ◽  
Demand Side Management ◽  
Energy Management System ◽  
Demand Side ◽  
Two Stage ◽  
Home Energy Management ◽  
Load Monitoring ◽  
Home Energy Management System

Electricity is a vital resource for various human activities, supporting customers’ lifestyles in today’s modern technologically driven society. Effective demand-side management (DSM) can alleviate ever-increasing electricity demands that arise from customers in downstream sectors of a smart grid. Compared with the traditional means of energy management systems, non-intrusive appliance load monitoring (NIALM) monitors relevant electrical appliances in a non-intrusive manner. Fog (edge) computing addresses the need to capture, process and analyze data generated and gathered by Internet of Things (IoT) end devices, and is an advanced IoT paradigm for applications in which resources, such as computing capability, of a central data center acted as cloud computing are placed at the edge of the network. The literature leaves NIALM developed over fog-cloud computing and conducted as part of a home energy management system (HEMS). In this study, a Smart HEMS prototype based on Tridium’s Niagara Framework® has been established over fog (edge)-cloud computing, where NIALM as an IoT application in energy management has also been investigated in the framework. The SHEMS prototype established over fog-cloud computing in this study utilizes an artificial neural network-based NIALM approach to non-intrusively monitor relevant electrical appliances without an intrusive deployment of plug-load power meters (smart plugs), where a two-stage NIALM approach is completed. The core entity of the SHEMS prototype is based on a compact, cognitive, embedded IoT controller that connects IoT end devices, such as sensors and meters, and serves as a gateway in a smart house/smart building for residential DSM. As demonstrated and reported in this study, the established SHEMS prototype using the investigated two-stage NIALM approach is feasible and usable.

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