scholarly journals Wireless Home Energy Management System with Smart Rule-Based Controller

2020 ◽  
Vol 10 (13) ◽  
pp. 4533
Author(s):  
Hussain Shareef ◽  
Eslam Al-Hassan ◽  
Reza Sirjani
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Residential Buildings ◽  
Public Utility ◽  
Renewable Energy Resources ◽  
Rule Based ◽  
Central Controller ◽  
Home Energy Management ◽  
Daily Energy ◽  
Utility Services

Despite the increasing utilization of renewable energy resources, such as solar and wind energy, most residential buildings still rely on conventional energy supply by public utility services. Such utility services often use time-of-use energy pricing, which compels residential consumers to reduce their energy usage. This paper presents a wireless home energy management (HEM) system that enables the automatic control of home appliances to reduce energy consumption to assist such energy users. The system consists of multiple smart sockets that measure the energy that is consumed by the connected appliances and are capable of implementing on/off commands. The system includes other support components for supplying data to a central controller, which utilizes a rule-based HEM algorithm. The control rules were designed, such that the lifestyle of the user would be preserved while the energy consumption and daily energy cost were reduced. The experimental results showed that the central controller could effectively receive data and control multiple devices. The system was also found to afford significant reductions of 23.5 kWh and $2.898 in the total daily energy consumption and bill of the considered household setup, respectively. The proposed HEM system promises to be particularly useful for households with a high daily energy consumption.

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%.

scholarly journals Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4539 ◽  
Author(s):  
Kumar ◽  
Brar ◽  
Singh ◽  
Nikolovski ◽  
Baghaee ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Management ◽  
Residential Buildings ◽  
Effective Means ◽  
Demand Side Management ◽  
Demand Side ◽  
Specific System ◽  
Energy Data ◽  
Energy Auditing

With the ever-growing power demand, the energy efficiency in commercial and residential buildings is a matter of great concern. Also, strategic energy auditing (SEA) and demand-side management (DSM) are cost-effective means to identify the requirements of power components and their operation in the energy management system. In a commercial or residential building, the major components are light sources and heating, ventilation, and air conditioning. The number of these components to be installed depends upon the technical and environmental standards. In this scenario, energy auditing (EA) allows identifying the methods, scope, and time for energy management, and it helps the costumers to manage their energy consumption wisely to reduce electricity bills. In the literature, most of the traditional strategies employed specific system techniques and algorithms, whereas, in recent years, load shifting-based DSM techniques were used under different operating scenarios. Considering these facts, the energy data in a year were collected under three different seasonal changes, i.e., severe cold, moderate, and severe heat for the variation in load demand under different environmental conditions. In this work, the energy data under three conditions were averaged, and the DSM schemes were developed for the operation of power components before energy auditing and after energy auditing. Moreover, the performance of the proposed DSM techniques was compared with the practical results in both scenarios, and, from the results, it was observed that the energy consumption reduced significantly in the proposed DSM approach.

scholarly journals A Survey of Communications and Networking Technologies for Energy Management in Buildings and Home Automation

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Aravind Kailas ◽  
Valentina Cecchi ◽  
Arindam Mukherjee
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Energy Management ◽  
Smart Grids ◽  
Energy Demand ◽  
Demand Curve ◽  
Future Research ◽  
Energy Awareness ◽  
Home Energy Management ◽  
Networking Technologies

With the exploding power consumption in private households and increasing environmental and regulatory restraints, the need to improve the overall efficiency of electrical networks has never been greater. That being said, the most efficient way to minimize the power consumption is by voluntary mitigation of home electric energy consumption, based on energy-awareness and automatic or manual reduction of standby power of idling home appliances. Deploying bi-directional smart meters and home energy management (HEM) agents that provision real-time usage monitoring and remote control, will enable HEM in “smart households.” Furthermore, the traditionally inelastic demand curve has began to change, and these emerging HEM technologies enable consumers (industrial to residential) to respond to the energy market behavior to reduce their consumption at peak prices, to supply reserves on a as-needed basis, and to reduce demand on the electric grid. Because the development of smart grid-related activities has resulted in an increased interest in demand response (DR) and demand side management (DSM) programs, this paper presents some popular DR and DSM initiatives that include planning, implementation and evaluation techniques for reducing energy consumption and peak electricity demand. The paper then focuses on reviewing and distinguishing the various state-of-the-art HEM control and networking technologies, and outlines directions for promoting the shift towards a society with low energy demand and low greenhouse gas emissions. The paper also surveys the existing software and hardware tools, platforms, and test beds for evaluating the performance of the information and communications technologies that are at the core of future smart grids. It is envisioned that this paper will inspire future research and design efforts in developing standardized and user-friendly smart energy monitoring systems that are suitable for wide scale deployment in homes.

scholarly journals Design of Ensemble Forecasting Models for Home Energy Management Systems

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7664
Author(s):  
Karol Bot ◽  
Samira Santos ◽  
Inoussa Laouali ◽  
Antonio Ruano ◽  
Maria da Graça Ruano
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Simple Procedure ◽  
Ensemble Forecasting ◽  
Management Systems ◽  
Energy Forecasting ◽  
Energy Management Systems ◽  
Ensemble Techniques ◽  
Home Energy Management ◽  
Home Energy Management System

The increasing levels of energy consumption worldwide is raising issues with respect to surpassing supply limits, causing severe effects on the environment, and the exhaustion of energy resources. Buildings are one of the most relevant sectors in terms of energy consumption; as such, efficient Home or Building Management Systems are an important topic of research. This study discusses the use of ensemble techniques in order to improve the performance of artificial neural networks models used for energy forecasting in residential houses. The case study is a residential house, located in Portugal, that is equipped with PV generation and battery storage and controlled by a Home Energy Management System (HEMS). It has been shown that the ensemble forecasting results are superior to single selected models, which were already excellent. A simple procedure was proposed for selecting the models to be used in the ensemble, together with a heuristic to determine the number of models.

scholarly journals Optimization of rule-based energy management strategies for hybrid vehicles using dynamic programming

2021 ◽  
Vol 184 (1) ◽  
pp. 3-10
Author(s):  
Di Zhu ◽  
Ewan Pritchard ◽  
Sumanth Dadam ◽  
Vivek Kumar ◽  
Yang Xu
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Measurement System ◽  
Hybrid Electric Vehicle ◽  
Management Strategies ◽  
Optimization Approach ◽  
Rule Based ◽  
Management Optimization ◽  
Vehicle Test ◽  
Vehicle Dynamic Model

Reducing energy consumption is a key focus for hybrid electric vehicle (HEV) development. The popular vehicle dynamic model used in many energy management optimization studies does not capture the vehicle dynamics that the in-vehicle measurement system does. However, feedback from the measurement system is what the vehicle controller actually uses to manage energy consumption. Therefore, the optimization solely using the model does not represent what the vehicle controller sees in the vehicle. This paper reports the utility factor-weighted energy consumption using a rule-based strategy under a real-world representative drive cycle. In addition, the vehicle test data was used to perform the optimization approach. By comparing results from both rule-based and optimization-based strategies, the areas for further improving rule-based strategy are discussed. Furthermore, recent development of OBD raises a concern about the increase of energy consumption. This paper investigates the energy consumption increase with extensive OBD usage.

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.

Robust anticipative energy management system: Application of a smart building platform

2016 ◽  
Vol 38 (2) ◽  
pp. 226-248 ◽  
Author(s):  
Minh-Hoang Le ◽  
Stephane Ploix
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Optimization Problem ◽  
Energy Allocation ◽  
Electricity Production ◽  
Variable Cost ◽  
Parametric Uncertainties ◽  
Management Problem ◽  
Weather Forecasts ◽  
Home Energy Management

Robust energy management in buildings is addressed in this paper. The energetic impact of buildings in the current energetic context is first presented. Then the studied optimization problem is defined as the optimal management of production and consumption activities in buildings. A scheduling problem is identified to adjust the energy consumption to both the energy cost and the user’s comfort. The available flexibility of the services provided by domestic appliances is used to compute optimal energy plans. These flexibilities are associated to time windows or heating storage abilities. A constraints formulation of the energy allocation problem is given. A derived mixed linear program is used to solve this problem. The energy consumption in houses is very dependent on uncertain data such as weather forecasts and inhabitants’ activities. Parametric uncertainties are introduced in the home energy management problem in order to provide robust energy allocation. Robust linear programming is implemented. A scenario-based approach is implemented to face this robust optimization problem. Practical application: Because of the increasing part of renewable energy in electricity production, which is difficult to control, consumers will have to become more involved in the grid management. This paper states the problem of energy management in buildings and describes the optimization problem defined to adjust the energy consumption of buildings to production constraints. This decision system is based on the weather forecasts and a variable cost of electricity. Parametric uncertainties on the data are taken into account in order to propose robust energy planning in which a performance is guaranteed over the expected data.

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