• Title/Summary/Keyword: energy monitoring and management

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An On-line System Architecture for Remote Energy Monitoring of CNC Machine Tools (CNC 기계의 원격 에너지 모니터링을 위한 온라인 시스템 구조)

  • Nam, Sung-Ho;Song, Ki-Hyeong;Baek, Jae-Yong;Lee, Dong-Yoon;Ryu, Kwang-Yeol
    • Journal of the Korean Society for Precision Engineering
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    • v.30 no.5
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    • pp.480-485
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    • 2013
  • Enhancing energy efficiency of machine tools causes substantial impacts on the manufacturing industries, to cope with the competitive introduction of the total energy management strategies. Real-time energy monitoring is essential to identify energy consumption patterns of the machine tools and correlate them with the energy management strategy. Integrated analysis of machine tool's operation status and the corresponding energy usage is most important to accurately evaluate the energy efficiency under the various machining process environments. This paper proposes a system architecture to realize the online energy monitoring system and the embedded energy monitoring approach interconnected with the CNC kernel. The shop-floor operation management system is presented to integrate the proposed online energy monitoring approach.

A Tutorial: Information and Communications-based Intelligent Building Energy Monitoring and Efficient Systems

  • Seo, Si-O;Baek, Seung-Yong;Keum, Doyeop;Ryu, Seungwan;Cho, Choong-Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.11
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    • pp.2676-2689
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    • 2013
  • Due to increased consumption of energy in the building environment, the building energy management systems (BEMS) solution has been developed to achieve energy saving and efficiency. However, because of the shortage of building energy management specialists and incompatibility among the energy management systems of different vendors, the BEMS solution can only be applied to limited buildings individually. To solve these problems, we propose a building cluster based remote energy monitoring and management (EMM) system and its functionalities and roles of each sub-system to simultaneously manage the energy problems of several buildings. We also introduce a novel energy demand forecasting algorithm by using past energy consumption data. Extensive performance evaluation study shows that the proposed regression based energy demand forecasting model is well fitted to the actual energy consumption model, and it also outperforms the artificial neural network (ANN) based forecasting model.

Real Time Monitoring of Energy Efficiency Operation Indicator on Merchant Ships

  • Barro, Ronald Dela Cruz;Kim, Jun-Seong;Lee, Don-Chool
    • Journal of Advanced Marine Engineering and Technology
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    • v.35 no.3
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    • pp.301-308
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    • 2011
  • International Maritime Organization (IMO) proposed the Energy Efficiency Operation Indicator (EEOI) in 2005 and the Energy Efficiency Design Index (EEDI) in 2008 so as to address emission concern and regulation. Likewise, Ship Energy Efficiency Management Plan (SEEMP) and Greenhouse Gas (GHG) monitoring and management are also becoming an issue lately. This paper introduces the energy efficiency design index (operation indicator) monitoring system (EDiMS) software can continuously monitor $CO_2$, $NO_x$, $SO_x$, and PM values emitted from ship. The accurate inventory of ships GHG can be obtained from base of emission result during the engine shop test trial and the actual monitoring of shaft power and ship speed. In addition, the ability to store all exhaust emission and engine operation data can be applied as the useful tool of the inventory work of air pollution and ship energy management plan for the mitigation or reduction of ship emissions.

Design and Implementation of Ship Energy Efficiency Monitoring System (선박 에너지 효율 모니터링 시스템 설계 및 구현)

  • Kim, Yong-dae;Yoon, Hyeon-kyu;Kang, Nam-seon
    • Journal of Advanced Navigation Technology
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    • v.20 no.5
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    • pp.408-416
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    • 2016
  • This study designed a ship energy efficiency monitoring system based on a ship application system that provides maritime services by utilizing data collected onboard, and a ship-land integration system for integrated management and exchange of maritime data. The ship energy efficiency monitoring system was developed as a Windows application program and designed to use file based EDI communications. Its main functions include route planning to minimize fuel consumption, monitoring of energy consumption and gas emissions, analysis of ship energy efficiency and other data analysis. The system has been successfully implemented in actual ships.

A Development of Intelligent Metering and Control System for Energy Management of Electric Cabinet Panel (분전반 전력관리용 지능형 계측 제어 시스템 개발)

  • Park, Byung-Chul;Park, Jae-Sung;Song, Sung-Kun;Shin, Joong-Rin
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.27 no.8
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    • pp.90-97
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    • 2013
  • In recent years, the many electric saving methods are studied because of difficulty of meeting the demand. The electric energy management such as monitoring of branch power consumption, demand control, metering, power quality monitoring, electric safety monitoring can make energy saving. The purpose of this paper is to develop a system which can provide the integrated management of various functions required for energy management by consumers. In this system all functions which were embodied into each devices are integrated into intelligent meter. The developed systems are tested and implemented by installing at consumer electric distribution panel.

A Research for Agentless Monitoring Application of Energy Consumption Analysis in a Data Center (데이터센터의 효율적인 에너지소비분석을 위한 에이전트리스 모니터링 애플리케이션에 관한 연구)

  • Lee, Yunho;Jung, Hyedong;Lim, Hojung;Kang, Jeonghoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.896-899
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    • 2016
  • Server management and power management are important to operate a data center stably and efficiently. By this paper, we introduce an web based application that is able to monitor and visualize energy consumption, help to energy consumption analysis of a data center due to provide server monitoring information such as temperatures for server, status of each device, power status using server management interfaces and power management modules in data center, also suggest the methods to implement them. This application takes advantage of IPMI which is server management standard interfaces and server management technology in manufacturer's individual way so it can do integrated monitoring for heterogeneous severs, and there is little monitoring load inside of server system because it doesn't need to install agent program for monitoring target system, and it can be used successfully to energy consumption analysis, server management in a data center due to realtime provided energy consumption and monitoring information.

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A Study on Energy Saving and Safety Improvement through IoT Sensor Monitoring in Smart Factory (스마트공장의 IoT 센서 모니터링을 통한 에너지절감 및 안전성 향상 연구)

  • Woohyoung Choi;Incheol Kang;Changsoo Kim
    • Journal of the Society of Disaster Information
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    • v.20 no.1
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    • pp.117-127
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    • 2024
  • Purpose: The purpose is to conduct basic research to save energy and improve the safety of manufacturing plant infrastructure by comprehensively monitoring energy management, temperature, humidity, dust and gas, air quality, and machine operation status in small and medium-sized manufacturing plants. Method: To this end, energy-related data and environmental information were collected in real time through digital power meters and IoT sensors, and research was conducted to disseminate and respond to situations for energy saving through monitoring and analysis based on the collected information. Result: We presented an application plan that takes into account energy management, cost reduction, and safety improvement, which are key indicators of ESG management activities. Conclusion: This study utilized various sensor devices and related devices in a smart factory as a practical case study in a company. Based on the information collected through research, a basic system for energy saving and safety improvement was presented.

Design of CIM(Common Information Model) Profile for Smart City Energy Monitoring (스마트시티 에너지 감시를 위한 CIM(Common Information Model) 프로파일 설계)

  • Youngil, Kim;Changhun, Chae;Yeri, Kim;Jihoon, Lee
    • KEPCO Journal on Electric Power and Energy
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    • v.8 no.2
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    • pp.127-135
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    • 2022
  • With the advent of high technologies such as the 4th Industrial Revolution and artificial intelligence and big data, efforts are being made to solve urban problems and improve the quality of life by applying new technologies in the smart city field. In addition, as carbon neutrality has emerged as an important issue due to global warming, smart city energy platform technologies such as urban energy management, efficiency improvement, and carbon reduction are in the spotlight. In order to effectively manage urban energy, energy resource information such as electricity, water, gas, hot water, heating, etc. must be collected from the management system of various energy utilities and managed on the central platform. The centrally integrated data is delivered to external city management systems that require city energy information through an energy platform. This study developed a CIM profile for smart city energy monitoring required to provide energy data to external systems. Electric data model were designed using the CIM class of IEC 61970, and water, gas, and heat data model were designed in compliance with the UML-based design ideas of IEC 61970.

An integrated monitoring system for life-cycle management of wind turbines

  • Smarsly, Kay;Hartmann, Dietrich;Law, Kincho H.
    • Smart Structures and Systems
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    • v.12 no.2
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    • pp.209-233
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    • 2013
  • With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

Development of Sensor Based Energy Management System (센서기반 에너지 모니터링 프로토타입 시스템)

  • Um, Dae-Jin;Choi, Jung-In;Lee, Ingyu
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.10
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    • pp.69-74
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    • 2014
  • With the increasing interest of energy efficiency, several buildings and factories begin to monitor energy usages with a built-in energy management system. However, the built-in energy monitoring system does not reflect the dynamics of buildings and factories energy usage. To overcome the latter, we deploy several sensors to monitor the dynamics of buildings energy usage patterns. In this paper, we are proposing a framework of a sensor based energy monitoring system. Based on our limited experiments, we can monitor power usages by a person, device and time period. As a result, we can plan a better energy usage and improve energy efficiency by the monitored energy usage profile data.