• Journal of the Korean Professional Engineers Association
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• v.27 no.4
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• pp.46-55
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• 1994

Demand Side Management(DSM) is a system to reduce the investment cost for new power plant construction and expansion of supply facilities, power through the investment for the energy conservation and load management. In this study, the trend of the energy environment, the necessity and feasibility of DSM shall be investigated and analysed, so that this study will give a help to select and develope a proper DSM technologies for actual use.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2398-2421
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• 2020

In third world countries like Pakistan, the production of electricity has been quickly reduced in past years due to rely on the fossil fuel. According to a survey conducted in 2017, the overall electrical energy capacity was 22,797MW, since the electrical grids have gone too old, therefore the efficiency of grids, goes down to nearly 17000MW. Significant addition of fossil fuel, hydro and nuclear is 64.2%, 29% and 5.8% respectively in the total electricity production in Pakistan. In 2018, the demand crossed 20,223MW, compared to peak generation of 15,400 to 15,700MW as by the Ministry of Water and Power. Country faces a deficit of almost 4000MW to 5000MW for the duration of 2019 hot summer term. Focus on one aspect considering Demand Side Management (DSM) cannot oversea the reduction of gap between power demand and customer supply, which eventually leads to the issue of load shedding. Hence, a scheduling scheme is proposed in this paper called RPSMDSM that is based on selection of those appliances that need to be only Turned-On, on priority during peak hours consuming minimum energy. The Home Energy Management (HEM) system is integrated between consumer and utility and bidirectional flow is presented in the scheme. During peak hours of electricity, the RPSMDSM is capable to persuade less power consumption and accomplish productivity in load management. Simulations show that RPSMDSM scheme helps in scheduling the electricity loads from peak price to off-peak price hours. As a result, minimization in electricity cost as well as (Peak-to-Average Ratio) PAR are accomplished with sensible waiting time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1799-1807
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• 2016

In this paper, we propose the automatic demand response systems which reduce the electric power consumption for the period automatically distinct from the existing passive demand response that a subscriber directly controls the energy consumption. The proposed systems are based on SEP 2.0 and consist of the demand response management program, the demand response server, and the demand response client. The demand response program shows the current status of the electric power use to a subscriber and supports the function which the administrator enables to creates or cancels a demand response event. The demand response server transmits the demand response event received from the demand response management program to the demand response client through SEP 2.0 protocol, and it stores the metering data from the demand response client in a database. After extracting the data, such as the demand response the start time, the duration, the reduction level, the demand response client reduces the electric power consumption for the period.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.3
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• pp.187-197
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• 2004

This paper presents a window-based load management system (LMS) developed as a decision-making tool in the competitive electricity market The developed LMS can help the users to monitor system load patterns, analyze their past energy consumption and schedule for the future energy consumption. The LMS can also provide the effective information on real-time energy/cost monitoring, consumed energy/cost analysis, demand schedule and cost-savings. Therefore. this LMS can be used to plan the optimal demand schedule and consumption strategy.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.396-400
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• 2005

This paper proposes the cost analysis on the energy efficient equipment when this equipment is participated in the demand-side bidding. Conventional demand-side bidding is exercised through load re-distribution. However if this load reduction is exercised by the use of high efficient equipment, its effect will be assumed to be more economical. This paper analyses this cost-benefit effect of high efficient equipment in the demand-side bidding.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.264-269
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• 2006

Efficient load management on natural gas is strongly required to allow stable and reasonable energy use. The present study investigated domestic and international cases for demand management of natural gas. The directions of load management were discussed. The reasonable evaluation methods of demand management were analyzed and specific evaluation items were suggested.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.408-417
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• 2022

Although traditionally perceived as being a visualization and asset management resource, the relatively rapid rate of improvement of computing power, coupled with the proliferation of cloud and edge computing and the IoT has seen the expanded functionality of modern Digital Twins (DTs). These technologies, when applied to buildings, are now providing users with the ability to analyse and predict their energy consumption, implement building controls and identify faults quickly and efficiently, while preserving acceptable comfort and well-being levels. Furthermore, when these building DTs are linked together to form a community DT, entirely new and novel energy management techniques, such as demand side management, demand response, flexibility and local energy markets can be unlocked and analysed in detail, creating circularity in the economy and making ordinary building occupants active participants in the energy market. Through the EU Horizon 2020 funded TwinERGY project, three different levels of DT (consumer - building - community) are being created to support the creation of local energy markets while optimising building performance for real-time occupant preferences and requirements for their building and community. The aim of this research work is to demonstrate the development of this new, interrelated, multi-level DT that can be used as a decision-making tool, helping to determine optimal scenarios simultaneously at consumer, building and community level, while enhancing and successfully supporting the community's management plan implementation.

• 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.