• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.195-197
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• 2001

The Distribution Network costs are currently part of the total cost of KEPCO covered through aggregated final consumer tariffs. There is no unbundling of Power Sale and Distribution Network activities. This situation will change with the introduction of competition in supply. The Distribution Network Service Providers will have to provide access and set explicitly Distribution Service Charges in order to enable the Power Sales Businesses to convey electricity to their consumers using the Distribution Network for these purposes. The Distribution Service Charges will be made up of Distribution Connection Charge and Distribution Use of Network Charge. The Distribution Losses will be considered through Distribution Loss Factors and included in the electricity purchased by the Power Sales Businesses.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.194-198
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• 2023

The current electricity networks will undergo profound changes in the years to come to be able to meet the growing demand for electricity, while minimizing the costs of consumers and producers, etc. The electricity network of tomorrow or even the intelligent « Smart Grids » network will be the convergence of two networks: the electricity network and the telecommunications network. In this context falls our work which aims to study the impact of the integration of energy decentralization into the electricity network. In this sense, we have implemented a new smart grid model where several coexisting suppliers can exchange information with consumers in real time. In addition, a new approach to energy distribution optimization has been developed. The simulation results prove the effectiveness of this approach in improving energy exchange and minimizing consumer purchase costs and line losses.

• The Journal of Information Systems
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• v.28 no.1
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• pp.133-153
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• 2019

Purpose The purpose of this study is to design a regional electricity planning model rather than the existing single region ones and verify its usefulness. The regional electricity planning model is to determine both electricity distribution among regions and power plant planning at the same time satisfying regional demands and distribution networks. Design/methodology/approach This study made a regional electricity planning model by integrating power plant planning and electricity distribution among regions. The regional electricity planning model is formulated into a linear programming problem, and coded and run using the OSeMOSYS, one of open source energy systems. Findings According to the empirical analysis result, this study confirmed that the regional electricity planning model proposed in this study deducts the unfairness among regions in view of electricity and green house gas. In addition, the model is expected to be used in evaluating and developing the national policies concerning fine dust and/or green house gas.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.171-173
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• 2005

To date, the IEA DSM Programme has not undertaken any work on the potential for DSM to cost-effectively relieve electricity network constraints Such constraints are becoming a significant problem in countries where electricity demand is increasing and network infrastructure ('poles and wires') is ageing. As loads grow and infrastructure reaches the end of its economic life, the potential cost of augmenting electricity networks is increasing exponentially. In many situations, network-driven DSM can delay the need for network augmentation. In some limited situations, mainly at the distribution level, network-driven DSM may be able to cost-effectively eliminate the requirement to build a 'poles and wires' solution. In this paper, the concept of network-driven DSM program is surveyed.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.518-536
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• 2021

Studies and applications related to unidirectional flow are gaining attention from researchers across disciplines in the recent years. Flow can be viewed as a concept, where the material, fluid, people, air, and electricity are moving from one node to another over a transportation network, water network, or through electricity distribution systems. Unlike other networks such as computer networks, most of the flow networks are visible and have strong material existence and are responsible for the flow of materials with definite shape and volume. The flow of electricity is also unidirectional, and also share similar features as of flow of materials such as liquids and air. Generally, in a flow network, every node in the network participates and contributes to the efficiency of the network. In this survey paper, we would like to evaluate and analyze the depth and application of the acyclic nature of unidirectional flow in several domains such as industry, biology, medicine, and electricity. This survey also provides, how the unidirectional flow and flow networks play an important role in multiple disciplines. The study includes all the major developments in the past years describing the key attributes of unidirectional flow networks, including their applications, scope, and routing methods.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.185-188
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• 2001

This paper represents planning rules which specify the technical and design criteria and procedures that apply to the transmission asset owner(TAO) and the distribution network service providers(DNSP) in the planning and development of the electricity network.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.10
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• pp.500-506
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• 2005

With the advent of electric power systems moving to a deregulated retail electricity market environment, calculating distribution service tariffs has become a challenging theme for distribution industries and tariff regulators. As distribution business remains as a monopoly, it is necessary to be regulated. And as multiple distribution companies compete with each other, it would be efficient to adopt competition to the determination of distribution service tariffs. This paper proposes a method to calculate distribution service tariffs using yardstick regulation, which can lead to competition among multiple distribution companies. The proposed method takes into account not only recovering revenue requirements but also the advantages of the yardstick regulation based on long-term marginal costs of distribution network expansion algorithms. A computer simulation is carried out to illustrate effectiveness of the proposed method and it is estimated that the algorithm can be applied to compute the distribution service tariffs under retail electricity markets.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.10
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• pp.49-57
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• 2010

In order to provide electricity to users economically and safely, distribution automation systems (DASs) monitor and operate components of distribution systems remotely through communication networks. The fiber optic communication network has been mainly installed for the DAS of Korea Electric Power Corporation (KEPCO) because of its huge bandwidth and dielectric noise immunity. However, the fiber optic communication network has some shortcomings that its installation cost and communication fee are expensive. This paper proposes a complex network where WLANs are combined with conventional fiber optic communication networks in order to expand DAS easily and inexpensively. A fixed wireless bridge communication unit (FWB-CU) for the proposed complex network is implemented using IEEE 802.11a WLAN technology. The proposed complex network is built actually to verify its feasibility experimentally as a DAS communication network.