scholarly journals Optimization of Demand-Response-Based Intelligent Home Energy Management System with Binary Backtracking Search Algorithm

Information ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 395
Author(s):  
Suhaib N. Abdul Latif ◽  
Jinjing Shi ◽  
Hasnain Ali Salman ◽  
Yongze Tang
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Demand Response ◽  
Search Algorithm ◽  
Optimal Schedule ◽  
Backtracking Search ◽  
Backtracking Search Algorithm ◽  
Intelligent Home ◽  
Home Energy Management ◽  
Demand Limit

In many nations, limited power from providers and an increase in demand for electricity have created new opportunities that can be used by home energy management systems (HEMSs) systems to enforce proper use of energy. This paper presents a virtual intelligent home with demand response (DR) model home appliances that have an inverter air conditioner, water pump, washing machine, and inverter refrigerator. A binary backtracking search algorithm (BBSA) is proposed to introduce the optimal schedule controller. With the proposed BBSA schedule controller, the highest energy consumption during DR can be reduced by 33.84% during the weekends and by 30.4% daily during the weekdays. The results indicate the effectiveness of the proposed HEMS. Additionally, the model can control the appliances and maintain total residential energy consumption below the defined demand limit.

scholarly journals Human Comfort-Based-Home Energy Management for Demand Response Participation

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2463 ◽  
Author(s):  
Herie Park
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Demand Response ◽  
Residential Building ◽  
Limited Participation ◽  
Human Comfort ◽  
Control Approach ◽  
Home Energy Management ◽  
Lighting Systems ◽  
Home Energy Management System

The residential building sector is encouraged to participate in demand response (DR) programs owing to its flexible and effective energy resources during peak hours with the help of a home energy management system (HEMS). Although the HEMS contributes to reducing energy consumption of the building and the participation of occupants in energy saving programs, unwanted interruptions and strict guidance from the system cause inconvenience to the occupants further leading to their limited participation in the DR programs. This paper presents a human comfort-based control approach for home energy management to promote the DR participation of households. Heating and lighting systems were chosen to be controlled by human comfort factors such as thermal comfort and visual comfort. Case studies were conducted to validate the proposed approach. The results showed that the proposed approach could effectively reduce the energy consumption during the DR period and improve the occupants’ comfort.

Design of Intelligent Home Energy Management for Demand Response Applications

2013 ◽  
Vol 827 ◽  
pp. 78-83
Author(s):  
Tao Li ◽  
Kun Peng Xu ◽  
Xue Qing Qi
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Energy Management ◽  
Demand Response ◽  
High Power ◽  
Household Appliances ◽  
Intelligent Home ◽  
Home Energy Management ◽  
High Power Consumption ◽  
Insight Into

A Home Energy Management (HEM) system is an integral part of a smart grid that can potentially enable demand response applications for residential customers. It provides a homeowner the ability to automatically perform smart load controls based on utility signals, customers preference and load priority. This paper presents an intelligent HEM for managing high power consumption household appliances for demand response (DR) analysis. The proposed HEM manages household loads according to their preset priority and guarantees the total household power consumption below certain levels.Given the lack of understanding about DR potentials in this market, this work serves as an essential stepping-stone toward providing an insight into how much DR can be performed for residential customers.

scholarly journals FEMAN: Fuzzy-Based Energy Management System for Green Houses Using Hybrid Grid Solar Power

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Abdellah Chehri ◽  
Hussein T. Mouftah
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Energy Demand ◽  
Global Awareness ◽  
Robust Controller ◽  
Intelligent Home ◽  
Home Energy Management ◽  
The Future ◽  
Hybrid Grid ◽  
The Impact

The United Nations has designated the year 2012 as the international year of sustainable energy. Today, we are seeing a rise in global awareness of energy consumption and environmental problems. Many nations have launched different programs to reduce the energy consumption in residential and commercial buildings to seek lower-carbon energy solutions. We are talking about the future green and smart houses. The subject of smart/green houses is not one of “why,” but rather “how,” specifically: “how making the future house more energy efficient.” The use of the renewable energy, the technology and the services could help us to answer this question. Intelligent home energy management is an approach to build centralized systems that deliver application functionality as services to end-consumer applications. The objective of this work is to develop a smart and robust controller for house energy consumption with maximizing the use of solar energy and reducing the impact on the power grid while satisfying the energy demand of house appliances. We proposed a fuzzy-based energy management controller in order to reduce the consumed energy of the building while respecting a fixed comfort.

Rule Base Home Energy Management System Considering Residential Demand Response Application

2015 ◽  
Vol 785 ◽  
pp. 526-531 ◽  
Author(s):  
Maytham S. Ahmed ◽  
Hussein Shareef ◽  
Azah Mohamad ◽  
Jamal Abd Ali ◽  
Ammar Hussein Mutlag
Keyword(s):  
Power Consumption ◽  
Energy Management ◽  
Demand Response ◽  
Comfort Level ◽  
Total Power ◽  
Rule Base ◽  
Customer Preference ◽  
Total Power Consumption ◽  
Home Energy Management ◽  
Demand Limit

The increasing number of consumer and household appliances causes the rise in home energy use. Therefore, home energy management (HEM) technology is essential to manage and reduce electricity consumption. The objective of this paper is to present an intelligent algorithm for HEM using rule base technique to manage the power consumption with demand response (DR) feature. The scheduling algorithm considers household loads according to the comfort level, customer preference setting and priority of appliance that can be managed at a given time. The algorithm guarantees the total power consumption to be below the electrical demand limit. To exhibit the performance of the proposed HEM, a number of simulations are carried out including DR signal from the network operator. The results show that the algorithm can effectively respond to DR signal, comfort level, customer preference setting and priority of appliance. Furthermore, the algorithm is simple to implement and has flexibility to control the appliances.

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