Byeongkwan Kang

A smart energy distribution and management system for renewable energy distribution and context-aware services based on user patterns and load forecasting

Emerging green IT and smart grid technologies have changed electric power infrastructure more efficiently. These technologies enable a power system operator and a consumer to improve energy efficiency and reduce greenhouse gas emissions by optimizing energy distribution and management. There are many studies of these topics with the trend of green IT and smart grid technology. However, existing systems are still not effectively implemented in home and building because of their architectural limitations. Therefore, in this paper, we propose a smart energy distribution and management system (SEDMS) that operates through interaction between a smart energy distribution system and a smart monitoring and control system. Proposed system monitors information about power consumption, a user¿s situation and surroundings as well as controls appliances using dynamic patterns. Because SEDMS is connected with the existing power grid and with the newrenewable energy system, we consider integration of new renewable energy system through electric power control. We implemented proposed system in test-bed and carry out some experiments. The results show that a reduction of the service response time and the power consumption are approximately 45.6% and 9-17% respectively.

Design and implementation of intelligent energy distribution management with photovoltaic system

As increasing power consumption is becoming a huge problem, renewable energy has been highlighted recently. Many companies and research centers study this new sustainable energy, and various products have appeared to the public. However, this kind of researches concentrates on the elemental technologies, and now a management system is needed to manage these technologies to maximize energy efficiency. In this paper, we propose the system of Intelligent Energy Distribution Management (iEDM) to monitor fast-changing environmental variables and manage solar power flexibly. Compared with normal utility interactive systems, the iEDM improves the energy efficiency up to 5.6 percent.

IoT-based monitoring system using tri-level context making model for smart home services

In future smart home based on Internet of Things (IoT), data acquisition and information analysis through various sensors will play a crucial role, and it will be a core technology to develop IoT-based smart home services. This paper proposes an IoT-based monitoring system using a tri-level context making model for context-aware services in smart homes.

Design and implementation of an intelligent energy saving system based on standby power reduction for a future zero-energy home environment

Energy saving has attracted great attention as a global issue because of recent environmental problems. As a part of energy saving efforts, governments are operating policies that encourage the distribution of energy saving systems. Also, individual households are voluntarily installing energy saving systems to reduce electric power consumption. However, due to fixed system architecture, the existing systems have a disadvantage, lacking in scalability and usability. In addition, the existing systems bring up immense inconvenience as it returns to standby mode after automatic standby power cut-off. Therefore, we propose an intelligent energy saving system to solve these problems. The proposed system controls the power based on the hierarchical relationship among home appliances, along with the relationship between user activity and home appliances for standby power reduction. We designed and implemented the proposed system, deployed it in the test bed, and measured the total power consumption to verify the system performance. The proposed system reduces total power consumption up to 10.5%.

Degradation diagnosis system of photovoltaic panels with mobile application

Recently, the number of buildings and houses in which photovoltaic (PV) systems are installed has increased. However, an issue with the efficiency of the PV system and the degradation phenomenon has been revealed. Consumers who benefit from the PV system experience difficulties monitoring and controlling it because a PV diagnosis system is heavy and expensive to install at home. Furthermore, the existing diagnosis system is not coordinated with a home energy management system. In addition, the accurate performance evaluation of the PV system is required for energy management. Therefore, a new degradation diagnosis system for PV panels for household consumers is proposed in this paper. Additionally, a mobile-type home gateway that has various management applications is proposed. It is demonstrated that, with this mobile-type home gateway applied to the proposed system, consumers can monitor the degradation of the PV system, analyze the efficiency of the PV panels, and save energy at home by using a mobile-type home gateway.

An IoT-based home energy management system over dynamic home area networks

A smart grid (SG) has attracted great attention due to recent environmental problems. SG technologies enable users, such as energy system operators and consumers, to reduce energy consumption and the emission of greenhouse gases, by changing energy infrastructure more efficiently. As a part of the SG, home energy management system (HEMS) has become increasingly important, because energy consumption of a residential sector accounts for a significant amount of total energy consumption. However, a conventional HEMS has some architectural limitations on scalability, reusability, and interoperability. Furthermore, the cost of implementation of a HEMS is very expensive, which leads to the disturbance of the spread of a HEMS. Therefore, this paper proposes an Internet of Things- (IoT-) based HEMS with lightweight photovoltaic (PV) system over dynamic home area networks (DHANs), which enables the construction of a HEMS to be more scalable, reusable, and interoperable. We suggest the techniques for reducing the cost of the HEMS with various perspectives on system, network, and middleware architecture. We designed and implemented the proposed HEMS and conducted a experiment to verify the performance of the proposed system.

Implementation of an Adaptive Intelligent Home Energy Management System Using a Wireless Ad-Hoc and Sensor Network in Pervasive Environments

Wireless ad hoc and sensor networks have been becoming increasingly essential in recent years because of their ability to monitor and manage real-time situational information for various novel services. Therefore, we propose an adaptive intelligent home energy management system (AiHEMS) using a wireless ad-hoc and sensor network, which consists of a monitoring sensor and a management gateway. The AiHEMS adopts an information convergence mechanism, so that when the system generates patterns it interconnects with the AiHEMS in other domains and then utilizes information from other domains for pattern generation. We also propose adaptive light-weight middleware architecture which is modified based on a systems role, a situation, and a policy, which leads to reduction in sensors system resource. To verify the efficiency of our system, we built a test bed using two offices and conducted experiments based on light and air-conditioner control for saving power. The results show that the power saving using dynamic patterns without information convergence and with information convergence are approximately 18% and 26% respectively compared to fixed value based control.

Intelligent office energy management system by analysis in Hyper-connected-IoT environments

As the importance of efficient energy management continues to increase, energy management systems (EMS) are also being actively researched and propagated. The most familiar and widely used system is the scheduling-based EMS. However, this system disallows maximized efficiency of energy management in environments where various users and devices coexist. In this paper, suggested energy management method through User-Device intimacy that based on the materialization of Hyper-connected-IoT environments (a concept that links Data, IoT, and space). Ultimately, more energy can be saved than from existing scheduling-based EMS.

Design and implementation of intelligent energy storage service model for peak load shaving

In this paper, we propose a new intelligent energy storage service model that utilizes the information of distributed energy storage and maintains a constant reserve margin by storing remaining power. We developed an Intelligent Energy Storage Manager (IESM) and verified its performance using the information of energy storage. Furthermore, we simulated the proposed intelligent energy storage service under two different conditions. In the simulation results, the average reserve margins were 18.3% and 17.7% respectively.

DESIGN OF ENERGY-EFFICIENT DATA COMMUNICATION BETWEEN A SMART METER AND HOME APPLIANCES

In this paper, we investigate communication between a smart meter and home appliances. Recently, researches on the smart grid are making progress actively. Furthermore, lots of information is being exchanged between consumers and energy service providers. However, even though the most important component in this smart grid system is the smart meter, the smart meter can’t communicate with an individual appliance in a household yet. Moreover, it is predicted that the more home appliances there are in the household, the bigger load and delay grow in the future. Therefore this paper aims for reducing amount of data transmission between the smart meter and the home appliances by delaying communication period if the previous information sent by the home appliances remains unchanged.