• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.20-24
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• 2008

A bid-based pool(BBP) model is representative of energy market structure in a number of restructured electricity markets. Supply function equilibrium(SFE) models of interaction better match what is explicitly required in the bid formats of typical BBP markets. Many of the results in the SFE literature involve restrictive parametrization of the bid cost functions. In the SFE models, two parameters, intercept and slope, are available for strategic bidding. This paper addresses the realistic competition format that players can choose both parameters arbitrarily. In a fixed demand function, equilibrium conditions for generation company's profit maximization have a degree of freedom, which induces multi-equilibrium. So it is hard to choose a convergent equilibrium. However, consideration of stochastic demand function makes the equilibrium conditions independent each other based on the amount of variance of stochastic demand function. This variance provides the bidding players with incentives to change the slope parameter from an equilibrium for a fixed demand function until the slope parameter equilibrium.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.125-136
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• 2005

As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high -tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which is extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Eased-Modeling and Tobin's censored regression model.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.307-311
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• 2014

Due to the increasing of power consumption, it is difficult to construct accurate prediction model for daily peak power demand. It is very important work to know power demand in next day for manager and control power system. In this research, we develop a daily peak power demand prediction method considering of characteristics of day of week. The proposed method is composed of liner model based on AR model and nonlinear model based on ELM to resolve the limitation of a single model. Using data sets between 2006 and 2010 in Korea, the proposed method has been intensively tested. As the prediction results, we confirm that the proposed method makes it possible to effective estimate daily peak power demand than conventional methods.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1128-1134
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• 2016

Demand response provides customer load reductions based on high market prices or system reliability conditions. One type of demand response, price-based program, induces customers to respond to changes in product rates. However, there are large-scale general and industrial customers that have difficulty changing their energy consumption patterns, even with rate changes, due to their electricity demands being commercial and industrial. This study proposes an in-house pricing model for large-scale general and industrial customers, particularly those with multiple business facilities, for self-regulating demand-side management and cost reduction. The in-house pricing model charges higher rates to customers with lower load factors by employing peak to off-peak ratios in order to reduce maximum demand at each facility. The proposed scheme has been applied to real world and its benefits are demonstrated through an example.

• Journal of Integrative Natural Science
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• v.12 no.1
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• pp.20-23
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• 2019

Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1225-1228
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• 2011

This paper presents an advanced energy saving algorithm in building. It is important to aggregate a various demand side resource which is controllable on demand response environment. Previous demand side algorithm for building is restricted on peak power. In this paper, we suggest duty cycle algorithm for AHU on demand response to reduce the quantity of building power consumption. The test results show that the proposed algorithm is very effective.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.904-914
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• 2017

For efficient energy usage, the concept of demand response has been emerged and thereby Open Automated D emand Response(OpenADR) protocol is developed as a standard protocol to provide automated demand response. There have been emerging trends on the demand response services using the Internet of Things(IoT) for smart h ome energy management. In this smart home energy IoT environment, a lightweight protocol is needed rather tha n the existing HTTP/ XML based OpenADR protocol for demand response services since many small devices wi ll be interconnected. In this paper, we propose a lightweight OpenADR protocol based on CoAP protocol for pro viding demand response service in Smart Energy IoT environment, implement the proposed CoAP-based protocol, and analyzed the performance compared to existing HTTP/ XML-based OpenADR 2.0b protocol.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.929-935
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• 2011

Customers hardly change to electric prices in old days because electricity is essential commodity, while demand changes with price after deregulation. It's explained by price-based demand response with demand-elasticity matrix. Also all of the customers have had identical demand-price elasticity matrix till now. But in a practical power system, various customers are present with taking a variety of demand-price elasticity. Therefore this paper proposes demand-price sensitivity to represent different demand-price elasticity. Also as proposing demand-reliability sensitivity, it is modeling various customers' characteristics to reliability. And then this paper calculates total expected interruption cost of customer from the customer interruption cost and the demand-reliability sensitivity. A total expected interruption cost of system is shown as opportunity cost of a generation cost.

• Journal of Satellite, Information and Communications
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• v.8 no.2
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• pp.56-61
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• 2013

With the rapidly increasing power demand in recent years, variety of methods have been proposed for efficient power consumption.. Among them, the most representative example is demand response system based smart grid. Demand response system is not passive, one-side power demand. This system can efficiently consume through communication between service provider and power consumer. Demand response system uses HTTP based TCP/IP. And currently, there are variety of communication application protocol. In this paper, we analyze procotol type and application for demand response system.