scholarly journals An Optimal Energy-Saving Home Energy Management Supporting User Comfort and Electricity Selling With Different Prices

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 9235-9249
Author(s):  
Huy Truong Dinh ◽  
Daehee Kim
Keyword(s):  
Energy Saving ◽  
Energy Management ◽  
Optimal Energy ◽  
Home Energy Management ◽  
User Comfort

scholarly journals An Optimal Energy-Saving Strategy for Home Energy Management Systems with Bounded Customer Rationality

2019 ◽  
Vol 11 (4) ◽  
pp. 88 ◽  
Author(s):  
Guoying Lin ◽  
Yuyao Yang ◽  
Feng Pan ◽  
Sijian Zhang ◽  
Fen Wang ◽  
...  
Keyword(s):  
Energy Saving ◽  
Energy Management ◽  
Utility Functions ◽  
Management Systems ◽  
Real Field ◽  
Temperature Sensitive ◽  
Energy Management Systems ◽  
Optimal Energy ◽  
Home Energy Management

With the development of techniques, such as the Internet of Things (IoT) and edge computing, home energy management systems (HEMS) have been widely implemented to improve the electric energy efficiency of customers. In order to automatically optimize electric appliances’ operation schedules, this paper considers how to quantitatively evaluate a customer’s comfort satisfaction in energy-saving programs, and how to formulate the optimal energy-saving model based on this satisfaction evaluation. First, the paper categorizes the utility functions of current electric appliances into two types; time-sensitive utilities and temperature-sensitive utilities, which cover nearly all kinds of electric appliances in HEMS. Furthermore, considering the bounded rationality of customers, a novel concept called the energy-saving cost is defined by incorporating prospect theory in behavioral economics into general utility functions. The proposed energy-saving cost depicts the comfort loss risk for customers when their HEMS schedules the operation status of appliances, which is able to be set by residents as a coefficient in the automatic energy-saving program. An optimization model is formulated based on minimizing energy consumption. Because the energy-saving cost has already been evaluated in the context of the satisfaction of customers, the formulation of the optimization program is very simple and has high computational efficiency. The case study included in this paper is first performed on a general simulation system. Then, a case study is set up based on real field tests from a pilot project in Guangdong province, China, in which air-conditioners, lighting, and some other popular electric appliances were included. The total energy-saving rate reached 65.5% after the proposed energy-saving program was deployed in our project. The benchmark test shows our optimal strategy is able to considerably save electrical energy for residents while ensuring customers’ comfort satisfaction is maintained.

scholarly journals QoE-Aware Smart Home Energy Management Considering Renewables and Electric Vehicles

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2304 ◽  
Author(s):  
Mingfu Li ◽  
Guan-Yi Li ◽  
Hou-Ren Chen ◽  
Cheng-Wei Jiang
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Smart Home ◽  
Control Algorithm ◽  
Renewable Energy Sources ◽  
Peak Load ◽  
Electricity Bill ◽  
Home Energy Management ◽  
Smart Appliance ◽  
User Comfort

To reduce the peak load and electricity bill while preserving the user comfort, a quality of experience (QoE)-aware smart appliance control algorithm for the smart home energy management system (sHEMS) with renewable energy sources (RES) and electric vehicles (EV) was proposed. The proposed algorithm decreases the peak load and electricity bill by deferring starting times of delay-tolerant appliances from peak to off-peak hours, controlling the temperature setting of heating, ventilation, and air conditioning (HVAC), and properly scheduling the discharging and charging periods of an EV. In this paper, the user comfort is evaluated by means of QoE functions. To preserve the user’s QoE, the delay of the starting time of a home appliance and the temperature setting of HVAC are constrained by a QoE threshold. Additionally, to solve the trade-off problem between the peak load/electricity bill reduction and user’s QoE, a fuzzy logic controller for dynamically adjusting the QoE threshold to optimize the user’s QoE was also designed. Simulation results demonstrate that the proposed smart appliance control algorithm with a fuzzy-controlled QoE threshold significantly reduces the peak load and electricity bill while optimally preserving the user’s QoE. Compared with the baseline case, the proposed scheme reduces the electricity bill by 65% under the scenario with RES and EV. Additionally, compared with the method of optimal scheduling of appliances in the literature, the proposed scheme achieves much better peak load reduction performance and user’s QoE.

Naïve Bayes classifier enabled home energy management scheme for cost-effective end-user comfort

2021 ◽  
Vol 40 (1) ◽  
pp. 403-413
Author(s):  
M. Firdouse Ali Khan ◽  
Ganesh Kumar Chellamani ◽  
Premanand Venkatesh Chandramani
Keyword(s):  
Energy Management ◽  
Time Window ◽  
Cost Effective ◽  
Pattern Generation ◽  
Home Appliances ◽  
Management Scheme ◽  
Home Energy Management ◽  
Maximum Comfort ◽  
The Cost ◽  
User Comfort

Under demand response enabled demand-side management, the home energy management (HEM) schemes schedule appliances for balancing both energy and demand within a residence. This scheme enables the user to achieve either a minimum electricity bill (EB) or maximum comfort. There is always the added burden on a HEM scheme to obtain the least possible EB with comfort. However, if a time window that contains comfortable time slots of the day for an appliance operation, is identified, and if the cost-effective schedule-pattern gets generated from these windows autonomously, then the burden can be reduced. Therefore, this paper proposes a two-level method that can assist the HEM scheme by generating a cost-effective schedule-pattern for scheduling home appliances. The first level uses a classifier to identify the comfortable time window from past ON and OFF events. The second level uses pattern generation algorithms to generate a cost-effective schedule-pattern from the identified window. The generated cost-effective schedule-pattern is applied to a HEM scheme as input to demonstrate the proposed two-level approach. The simulation results exhibit that the proposed approach helps the HEM scheme to schedule home appliances cost-effectively with a satisfactory user-comfort between 90% and 100%.

scholarly journals IoT Operating System Based Fuzzy Inference System for Home Energy Management System in Smart Buildings

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2802 ◽  
Author(s):  
Qurat-ul Ain ◽  
Sohail Iqbal ◽  
Safdar Khan ◽  
Asad Malik ◽  
Iftikhar Ahmad ◽  
...  
Keyword(s):  
Operating System ◽  
Energy Consumption ◽  
Energy Management ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Residential Buildings ◽  
Inference System ◽  
Intelligent Sensors ◽  
Home Energy Management ◽  
User Comfort

Energy consumption in the residential sector is 25% of all the sectors. The advent of smart appliances and intelligent sensors have increased the realization of home energy management systems. Acquiring balance between energy consumption and user comfort is in the spotlight when the performance of the smart home is evaluated. Appliances of heating, ventilation and air conditioning constitute up to 64% of energy consumption in residential buildings. A number of research works have shown that fuzzy logic system integrated with other techniques is used with the main objective of energy consumption minimization. However, user comfort is often sacrificed in these techniques. In this paper, we have proposed a Fuzzy Inference System (FIS) that uses humidity as an additional input parameter in order to maintain the thermostat set-points according to user comfort. Additionally, we have used indoor room temperature variation as a feedback to proposed FIS in order to get the better energy consumption. As the number of rules increase, the task of defining them in FIS becomes time consuming and eventually increases the chance of manual errors. We have also proposed the automatic rule base generation using the combinatorial method. The proposed techniques are evaluated using Mamdani FIS and Sugeno FIS. The proposed method provides a flexible and energy efficient decision-making system that maintains the user thermal comfort with the help of intelligent sensors. The proposed FIS system requires less memory and low processing power along with the use of sensors, making it possible to be used in the IoT operating system e.g., RIOT. Simulation results validate that the proposed technique reduces energy consumption by 28%.

Development of the Home Energy Management System Learning Materials Using LEGO MINDSTORMS

2012 ◽  
Vol 590 ◽  
pp. 499-502
Author(s):  
Yoshito Nakajima ◽  
Takahiro Kaburagi ◽  
Takayuki Misu ◽  
Keishin Koh ◽  
Norikane Kanai
Keyword(s):  
High School Students ◽  
Energy Saving ◽  
Energy Management ◽  
Management System ◽  
Robot Control ◽  
Energy Management System ◽  
Learning Materials ◽  
Home Energy Management ◽  
Lego Mindstorms ◽  
Home Energy Management System

Technique and also education for energy saving is attracted attention in Japan. The suggestion about the energy management system utilized embedded technology using microcomputer control and a network system has been proposed. Home energy management system can be produced in replacing with ideas of robot control system. In this paper, we report the project to producing of model of Home Energy Management System utilizing a robot control technology with the LEGO MINDSTORMS Experimentally in PBL and it is developed the teaching and learning materials for high school students who could understand a flow of the energy management and energy saving.

scholarly journals User’s Perspective on Home Energy Management Systems

Environments ◽  
2018 ◽  
Vol 5 (12) ◽  
pp. 126 ◽  
Author(s):  
Ad Straub ◽  
Ellard Volmer
Keyword(s):  
Energy Saving ◽  
Energy Management ◽  
Energy Use ◽  
Electricity Consumption ◽  
Principal Component ◽  
Added Value ◽  
Q Method ◽  
Single Family ◽  
Home Energy Management ◽  
Saving Effect

A Home Energy Management System (HEMS) has no direct and immediate energy-saving effect. It gives insight into the resident’s behaviour regarding energy use. When this is linked to the appropriate feedback, the resident is in a position to change his or her behaviour. This should result in reduced gas and/or electricity consumption. The aim of our study is to contribute to the effective use of HEMSs by identifying types of homeowners in relation to the use of a HEMS. The research methods used were a literature review and the Q-method. A survey using the Q-method was conducted among 39 owners of single-family homes in various Rotterdam neighbourhoods. In order to find shared views among respondents, a principal component analysis (PCA) was performed. Five different types of homeowners could be distinguished: the optimists, the privacy-conscious, the technicians, the sceptics, and the indifferent. Their opinions vary as regards the added value of a HEMS, what characteristics a HEMS should have, how much confidence they have in the energy-saving effect of such systems, and their views on the privacy and safety associated with using a HEMS. The target group classification can be used as input for a way in which local stakeholders, e.g., a municipality, can offer HEMSs that are in line with the wishes of the homeowner.

Optimal Smart Home Energy Management Considering Energy Saving and a Comfortable Lifestyle

2015 ◽  
Vol 6 (1) ◽  
pp. 324-332 ◽  
Author(s):  
Amjad Anvari-Moghaddam ◽  
Hassan Monsef ◽  
Ashkan Rahimi-Kian
Keyword(s):  
Energy Saving ◽  
Energy Management ◽  
Smart Home ◽  
Home Energy Management

Development of Interface for Assisting Energy-Saving Utilizing Information From Network Home Appliances

2019 ◽  
pp. 138-147
Author(s):  
Takumi Shida ◽  
Hiroshi Sugimura ◽  
Moe Hamamoto ◽  
Masao Isshiki
Keyword(s):  
Power Consumption ◽  
Energy Saving ◽  
Energy Management ◽  
High Energy ◽  
Home Appliances ◽  
Home Energy Management ◽  
Level Of Consciousness ◽  
Operational Information ◽  
Home Energy Management System ◽  
Insufficient Knowledge

The authors propose an interface for home energy management system (HEMS). This interface is aimed at raising the energy-saving consciousness of users who have little knowledge of energy saving. A possible reason for the low level of consciousness of such users is that HEMS does not provide information which helps users in energy-saving planning. To help users who have insufficient knowledge of energy saving, the interface visualizes power consumption and operational information obtained from network home appliances. In order to show which appliances have potential for significant energy-saving effects, the interface uses icons that visually represent high-power appliances whose power consumption exceeds 400 W, along with their operation periods. By viewing the screen, users can easily recognize how to operate appliances for energy-saving planning as well as which appliances have high energy-saving effects. The authors have developed a tool with a built-in interface and have evaluated it by questionnaire.

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