• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.284-291
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• 2018

As environmental pollution has become worse green technologies to replace or reduce consumption of fossil fuel get spotlight from government, industry and academia globally. It is reported that 40% of carbon dioxide emission is caused by electricity power generation. And 37% of end user electricity power is used by residential costumer in US. Smart Grid is considered as one of promising technology to alleviate severe environmental problem. In residential environment, Home Energy Management System (HEMS) can play a key role for green smart home. The HEMS can give several benefits like aslowering electric utility bill, improvement of efficiency of electric power consumption and integration of generator using renewable energy resources. However just limited functions of HEMS can be used for residential customer in real life because of lack of smart function in home appliances and optimal managing software for HEMS. This study provides comprehensive analysis for Home Energy Management System for residential customer. Simple HEMS system with real products on the market are explained and limitation of current HEMS are also discussed.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.221-226
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• 2020

Smart homes have become the state of the art in the reduction and monitoring of energy usage within a residential setting. Emerging threats such as climate change, global warming and volatility in energy prices have fuelled the interest in smart systems. Given that environmental sustainability has become a more significant factor for consumers, this research examines whether consumers' attitudes toward smart home services for efficient energy management differ according to their regulatory focus. Specifically, it is predicted that consumers will have more favorable attitudes toward smart home services for efficient energy management when they are promotion-focused (vs. prevention-focused). The results indicate that respondents with a promotion (vs. prevention) focus reported significantly more favorable attitudes toward smart home services for energy management (e.g., smart cooling/heating system, smart ventilation & air conditioning system, smart thermostats, smart plugs, and smart switches). We suggest that regulatory focus may be an effective marketing and segmentation tool in promoting smart home services for energy management and facilitating their receptiveness to the services.

• Journal of Computing Science and Engineering
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• v.7 no.3
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• pp.204-210
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• 2013

We present the motivation, design and implementation of a smart home system in Korea. Our system is open, extensible, integrated, intelligent, and usage-centric. We detail the challenges and key design requirements for the smart home system based on our past experiences, and show how convergence system design is a capable methodology for enabling an integrated and multi-faceted home management system that encompasses energy management, home appliance control, environment management, u-health, and living support functionalities under a single unified design. Using energy management as a specific case study, we demonstrate how convergence system design can encapsulate technology heterogeneity and hardware-software disparity without compromising simple yet powerful user interfaces.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.77-82
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• 2024

The Smart home energy consumption represents much of the total energy consumed in advanced countries. For this reason, the main objectif of this paper is to study the energy consumption profile by day for each home appliances: controllable appliances for example Washing machine, Tumble dryer and Air conditioning and uncontrollable appliances for example TV, PC, Lighting, Refrigerator and Electric heater. In this paper, we start with presentation of a smart home energy management systems. Next, we present the modeling and simulation of controllable appliances and uncontrollable appliances. Finally, concludes this paper with some prospects. The modeling and the simulation of a Smart home appliances is based on MATLAB/Simulink software.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2781-2798
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• 2019

Thanks to internet, as one of indispensable parts of our lives, many devices that we use in our daily lives like TV, air conditioner, refrigerator, washing machine, can be monitored and controlled remotely by becoming more intelligent via Internet of Things (IoT) technology. Smart Home applications as one of the elements of smart cities, are individually the most demanded application without question. In this study, Smart Energy Management (SEM) system, based on NodeMCU and Android, has been designed for SEM, which is a part of the smart home application. With this system, household energy consumption can be monitored in real time, as well as having the ability to record the data comprising of operation times and energy consumption information for each device. Additionally, it is ensured to meet the energy needs on a maximized level possible, during the hours when the energy costs are lower owing to the SEM system. The Android interface provides the users with the opportunity to monitor and change their electricity consumption habits in order to optimize the energy efficiency, along with the opportunity to draw up of a daily and weekly schedule.

• Asia pacific journal of information systems
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• v.27 no.2
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• pp.99-125
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• 2017

In this study, we propose an operations model to automate a home energy management system (HEMS) that utilizes an energy storage system (ESS) in consideration of consumer utility. Most previous studies focused on the system for the profits obtained from trading charged energy using large-scale ESS. By contrast, the present study focuses on constructing a home-level energy management system that considers consumer's utility over energy consumption. Depending on personal preference, some residential consumers may prefer consuming additional energy to earn increased profits through price arbitrage and vice versa. However, the current system could not yet reflect on this aspect. Thus, we develop an operations model for HEMS that could automatically control energy consumption while considering the level of consumer's preference and the economic benefits of using an ESS. The results of simulations using a dataset of the Korean market show that an operations policy of charging and discharging can be changed depending on consumer's utility. The impact of this policy is not ignorable. Moreover, the technical specifications of ESS, such as self-discharge rate and round-trip efficiency, can affect the operations policy and automation of HEMS.

• 한국IT서비스학회:학술대회논문집
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• 2010.05a
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• pp.151-154
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• 2010

In this paper, we propose an energy monitoring and management service based on wireless sensors and a home gateway for homes and buildings. Homes and buildings have a significant energy saving potential compared with other sectors. Sensing, monitoring, and managing of the information on the energy consumption are required for an efficient energy saving service. The proposed system is composed of two main components, wireless sensor and an intelligent home gateway. Wireless sensors have the ZigBee communication interface for communication, and the intelligent home gateway is an energy portal. We expect that energy saving could be achieved with this system. As a further work, we will analyze the practical impact of the proposed service.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.678-680
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• 2016

Due to changes in the energy environment, it's very popular to introduce the solar energy at home. More effective energy management is achieved together with an energy storage system(ESS). The electricity generated by solar can be used effectively to achieve the peak cut and price reduction. In this paper, we developed Smart Energy Profile(SEP) to make an ESS as a component of home energy management system(HEMS) cooperating with home network. First, we defined the functions equipped on the ESS and then developed a standard-based protocol to achieve compatibility between products. Our main contribution is to establish the foundation to introduce the HEMS at home.

• ETRI Journal
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• v.35 no.4
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• pp.677-686
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• 2013

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real-time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost-effective way possible. In our research, to avoid the high peak-to-average ratio (PAR) of power, we combine the real-time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.