• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.272-276
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• 2010

Renewable energy sources are considered to be environment-friendly alternatives those are increasingly introduced in the power systems. Microgrid is one of the systems in which renewable sources have a main role as a energy suppliers. Decision of constitution rates of renewable energy sources is very important for the economical and stable operation of microgird systems. In this paper, we present a method to assess an optimal constitution rate of renewable sources especially of windturbine and photovoltaic systems.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.2
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• pp.87-95
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• 2011

A Renewable Portfolio Standard(RPS) is a regulation that requires the increased generation of energy from renewable energy sources such as solar, wind, fuel cell, small hydro, biomass and geothermal. By environmental, technical and these regulatory reasons, the amount of renewable energy sources will be increased in a network. However, it is hard to assess risk of a transmission network with large scale renewable energy sources because the output characteristics of renewable energies are intermittent. This paper evaluates effects of a transmission system with supplemental large scale renewable energies into the existing system. To evaluate these effects, a methodology for risk level of components in a network is proposed considering steady state and contingency N-1 in this paper. We consider line current and bus voltage in each state of a network.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.269-296
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• 2006

With the concern of the potential problems which can be observed in terms of the power supply of renewable energies, we need to analyze the impact of additional power generation capacities of renewable energy sources on peak load. Each renewable energy sources are dependent upon wind speed, solar radiation, head differences caused by lunar calendar. Considering that these exogenous renewable energy sources follow their own stochastic distributions, we analyze the probability distribution of the impact of each renewable energy power supply on peak load. As a conclusion, we note that traditional tools used for the analysis of power supply such as capacity factors are no longer appropriate for the analysis of renewable energy sources in that perspective.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1666-1672
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• 2015

Small islands are quite adequate places where microgrid system with renewable sources can replace diesel engines as operation costs of diesel engine in most small islands are very high. To get the large amount of renewable energy, the microgrid system has very large capacity of renewable sources. The system with large capacity of renewable sources can meet the case when supplied energy is greater than the load and the fluctuation of source output is very large. The battery energy storage system can be a solution to stabilize the system with large capacity of renewable sources. In this case, BESS can be utilized as a master source for the synchronous operation of all sources including diesel engine, wind turbine and PV. The diesel generators can be used as a backup in case the BESS SOC goes below a certain level. In this paper, we suggest a novel unit commitment of diesel generators and operation schedule of pump for water supply service with the information of wind forecast, PV forecast, and load forecast. The proposed methods has been implemented and tested at the test bed in Gasa-Island.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

• Current Research on Agriculture and Life Sciences
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• v.32 no.4
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• pp.215-223
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• 2014

This study examines the contribution level of greenhouse gas(GHG) emission reduction and installation costs of renewable energy facilities. The GHG emission forecasts and industrial structures in the 16 regions of Korea are then analyzed to identify the proper supply of renewable energy sources for each region. The results show that water power is the most effective and efficient renewable energy source to reduce GHG emissions, followed by sunlight, wind power, geothermal heat, and solar heat, respectively. The 16 regions are then categorized into 4 groups based on their GHG emission forecast and industrial structure: high emission and manufacturing group, low emission and manufacturing group, low emission and service group, and high emission and service group. The proper supply of renewable energy sources for each group is then determined based on the contribution level and cost efficiency of GHG emission reduction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2177-2193
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• 2018

This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1486-1495
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• 2019

Dealing with the DC link fault poses a technical problem for an HVDC based on a modular multilevel converter. The fault suppressing mechanisms of several sub-module topologies with DC fault current blocking capacity are examined in this paper. An improved half-bridge sub-module topology with double direction control switch is also designed to address the additional power consumption problem, and a sub-module topology called hybrid double direction blocking sub module (HDDBSM) is proposed. The DC fault suppression characteristics and sub-module capacitor voltage balance problem is also analyzed, and a self-startup method is designed according to the number of capacitors. The simulation model in PSCAD/EMTDC is built to verify the self-startup process and the DC link fault suppression features.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.31-41
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• 2022

As the environmental impacts of fossil fuel energy sources increase, the South Korean government has tried to change non-environmental-friendly enery sources to environmental-friendly energy sources in order to mitigate environmental effects, which lead to global warming and air pollution. With both a limited budget and limited time, it is essential to accurately evaluate the economic and environmental effects of renewable energy projects for the efficient and effective operation of renewable energy plants. Although the traditional economic evaluation methods are not ideal for evaluating the economic impacts of renewable energy projects, they can still be used for this purpose. Renewable energy projects involve many risks due to various uncertainties. For this reason, this study utilizes a real option method, the Geske compound model, to evaluate the renewable energy projects on Jeju Island in terms of economic and environmental values. This study has developed an economic evaluation model based on the Geske compound model to investigate the influences of flexibility and uncertainty factors on the evaluation process. This study further conducts a sensitivity analysis to examine how two uncertainty factors (namely, investment cost and wind energy production) influence the economic and environmental value of renewable energy projects.