Smart Home Energy Management System

2022 ◽  
pp. 1132-1147
Author(s):  
Tesfahun Molla
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Peak Load ◽  
Area Network ◽  
Home Gateway ◽  
Energy Management Systems ◽  
Power Scheduling ◽  
Home Energy Management ◽  
Home Area ◽  
Home Energy Management System

With the development of smart grid technology, residents can schedule their power consumption pattern in their home to minimize electricity expense, reducing peak-to-average ratio (PAR) and peak load demand. The two-way flow of information between electric utilities and consumers in smart grid opened new areas of applications. In this chapter, the general architectures of the home energy management systems (HEMS) are introduced in a home area network (HAN) based on the smart grid scenario. Efficient scheduling methods for home power usage are discussed. The energy management controller (EMC) receives the demand response (DR) information indicating the Time-of use electricity price (TOUP) through the home gateway (HG). With the DR signal, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG.

Smart Home Energy Management System

2020 ◽  
pp. 191-206
Author(s):  
Tesfahun Molla
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Peak Load ◽  
Area Network ◽  
Home Gateway ◽  
Energy Management Systems ◽  
Power Scheduling ◽  
Home Energy Management ◽  
Home Area ◽  
Home Energy Management System

With the development of smart grid technology, residents can schedule their power consumption pattern in their home to minimize electricity expense, reducing peak-to-average ratio (PAR) and peak load demand. The two-way flow of information between electric utilities and consumers in smart grid opened new areas of applications. In this chapter, the general architectures of the home energy management systems (HEMS) are introduced in a home area network (HAN) based on the smart grid scenario. Efficient scheduling methods for home power usage are discussed. The energy management controller (EMC) receives the demand response (DR) information indicating the Time-of use electricity price (TOUP) through the home gateway (HG). With the DR signal, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG.

scholarly journals COMMUNITY BASED HOME ENERGY MANAGEMENT SYSTEM

2017 ◽  
Vol 18 (1) ◽  
pp. 43-55
Author(s):  
Muhammad Adnan Aziz ◽  
Ijaz Mansoor Qureshi ◽  
Tanweer Ahmed Cheema ◽  
Engr. Akram Rashid
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Cost Reduction ◽  
Community Based ◽  
Energy Management Systems ◽  
Power Scheduling ◽  
Home Energy Management ◽  
Reduction Stability ◽  
Home Energy Management System ◽  
Low Charge

In a Smart Grid (SG) scenario, domestic consumers can gain cost reduction benefit by scheduling their Appliance Activation Time (AAT) towards the slots of low charge. Minimization in cost is essential in Home Energy Management Systems (HEMS) to induce consumers acceptance for power scheduling to accommodate for a Demand Response (DR) at peak hours. Despite the fact that many algorithms address the power scheduling for HEMS, community based optimization has not been the focus. This paper presents an algorithm that targets the minimization of energy costs of whole community while keeping a low Peak to Average Ratio (PAR) and smooth Power Usage Pattern (PUP). Objective of cost reduction is accomplished by finding most favorable AAT by Particle Swarm Optimization (PSO) in conjunction with Inclined Block Rate (IBR) approach and Circular Price Shift (CPS). Simulated numerical results demonstrate the effectiveness of CPS to assist the merger of PSO & IBR to enhance the reduction/stability of PAR and cost reduction.

scholarly journals Demand response program for smart grid through real time pricing and home energy management system

2021 ◽  
Vol 11 (5) ◽  
pp. 4558
Author(s):  
Shibily Joseph ◽  
E. A. Jasmin
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Energy Management ◽  
Demand Response ◽  
Management System ◽  
Peak Load ◽  
Energy Management System ◽  
Home Energy Management ◽  
Real Time Pricing ◽  
Home Energy Management System

Aim of demand response (DR) programs are to change the usage pattern of electricity in such a way that, beneficial to the consumers as well as to the distributors by applying some methods or technology. This way additional cost to erect new energy sources can be postponed in power grid. Best method to implement demand response (DR) program is by influencing consumer through the implementation of real time pricing scheme. To harness the benefit of DR, automated home energy management system is essential. This paper presents a comprehensive demand response system with real time pricing. The real time price is determined after considering price elasticity of various classes of consumers and their load profiles. A real time clustering algorithm suitable for big data of smart grid is devised for the segmentation of consumers. This paper is novel in its design for real time pricing and modelling and automatic scheduling of appliances for home energy management. Simulation results showed that this new real time pricing method is suitable for DR programs to reduce the peak load of the system as well as reducing the energy expenditure of houses, while ensuring profit for the retailer.

scholarly journals A Case Study of Socially-Accepted Potentials for the Use of End User Flexibility by Home Energy Management Systems

2020 ◽  
Vol 13 (1) ◽  
pp. 132
Author(s):  
Christian Pfeiffer ◽  
Markus Puchegger ◽  
Claudia Maier ◽  
Ina V. Tomaschitz ◽  
Thomas P. Kremsner ◽  
...  
Keyword(s):  
Energy Management ◽  
Management System ◽  
Management Systems ◽  
System Support ◽  
Energy Management System ◽  
Energy Management Systems ◽  
Sample Area ◽  
Home Energy Management ◽  
Support Optimization ◽  
Home Energy Management System

Due to the increase of volatile renewable energy resources, additional flexibility will be necessary in the electricity system in the future to ensure a technically and economically efficient network operation. Although home energy management systems hold potential for a supply of flexibility to the grid, private end users often neglect or even ignore recommendations regarding beneficial behavior. In this work, the social acceptance and requirements of a participatively developed home energy management system with focus on (i) system support optimization, (ii) self-consumption and self-sufficiency optimization, and (iii) additional comfort functions are determined. Subsequently, the socially-accepted flexibility potential of the home energy management system is estimated. Using methods of online household survey, cluster analysis, and energy-economic optimization, the socially-accepted techno-economic potential of households in a three-community cluster sample area is computed. Results show about a third of the participants accept the developed system. This yields a shiftable load of nearly 1.8 MW within the small sample area. Furthermore, the system yields the considerably larger monetary surplus on the supplier-side due to its focus on system support optimization. New electricity market opportunities are necessary to adequately reward a systemically useful load behavior of households.

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