• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1489-1494
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• 2014

A hardware-in-the-loop simulation (HILS) method for a wind farm controller using a real time digital simulator (RTDS) is presented, and performance of the wind farm controller is analyzed. A 100 MW wind farm which includes 5 MW wind power generation systems (WPGS) is modeled and analyzed in RSCAD/RTDS. The wind farm controller is implemented by using a computer, which is connected to the RTDS through transmission control protocol/internet protocol (TCP/IP). The HILS results show the active power and power factor of the wind farm, which are controlled by the wind farm controller. The proposed HILS method in this paper can be effectively utilized to validate and test a wind farm controller under the environment in practice without a real wind farm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.404-410
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• 2016

This paper proposed a program of an energy storage system(ESS) for peak shaving of high-speed railway substations The peak shaving saves cost of equipment and demand cost of the substation. To reduce the peak load, it is very important to know when the peak load appears. The past data based load profile forecasting method is easy and applicable to customers which have relatively fixed load profiles. And an optimal scheduling method of the ESS is helpful in reducing the electricity tariff and shaving the peak load efficiently. Based on these techniques, MS. NET based peak shaving program is developed. In case study, a specific daily load profile of the local substation was applied and simulated to verify performance of the proposed program.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.27-34
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• 2014

The paper proposed a sizing method of an energy storage system(ESS) for peak shaving of high-speed railway substations based on load profile patterns of substations. A lithium based battery ESS was selected since it can produce high-power at high speed that peak shaving requires, and also takes up a relatively smaller space for installation. Adequate size of the ESS, minimum capacity which can technically meet a peak shaving target, was determined by collectively considering load patterns of a target substation, characteristics of the ESS to be installed, and optimal scheduling of the ESS. In case study, a local substation was considered to demonstrate the proposed sizing method. Also economic analysis with the determined size of ESS was performed to calculate electricity cost savings of the peak shaving ESS, and to offer pay-back period and return on investment.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.824-833
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• 2012

In this paper, a coordinated state-of-charge (SOC) control strategy for the energy storage system (ESS) operating under microgrid islanded mode to stabilize the frequency and voltage was proposed. The proposed SOC control loop is made up of PI controller, which uses a SOC state of the energy storage system as an input and an auxiliary reference value of secondary control as an output. The SOC controller changes the auxiliary reference value of secondary control to charge or discharge the ESS. To verify the proposed control strategy, PSCAD/EMTDC simulation study was performed. The simulation results show that the SOC of the ESS can be regulated at the desired operating range without degrading the stabilizing control performance by proposed coordinated SOC control method.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.59-71
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• 2019

This research is aimed to identify the building factors and deriving the importance of each factor for establishing the smart distribution center in the fourth industrial revolution era. The research methodology used CFPR(Consistent Fuzzy Preference Relations) to effectively extract expert knowledge. Research has shown as principle factors that "Service" is the first factor to be considered as 0.271, followed by "Infra(Warehouse)"(0.254), "Information System"(0.247), and "Equipment"(0.228). And as detailed factors, "Reliability" showed the highest importance as 0.091, followed "Visibility of Information System"(0.076), "Space Advancement"(0.075), "Location"(0.074) and "Satisfaction of service"(0.073). This study has implications in that it has presented an establishment direction for the smart distribution center.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1510-1532
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• 2017

In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1390-1396
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• 2013

The paper estimated the reasonable market price of lead-acid battery energy storage system (BESS) intended for demand management of electricity customers. As time-of-use (TOU) tariffs have extended to a larger number of customers and gaps in the peak and off-peak rates have gradually risen, deployment of BESS has been highly needed. However, immature engineering techniques, lack of field experiences and high initial investment cost have been barriers to opening up ESS markets. This paper assessed electricity cost that BESS operation could save for customers and, based on the possible cost savings, estimated reasonable prices at which BESSs could become a more prospective option for demand management of customers. Battery scheduling was optimized to maximize the electricity cost savings that BESS would possibly achieve under TOU tariffs conditions. Basic economic factors such as payback period and return on investment were calculated to determine reasonable market prices. Actual load data of 12 industrial customers were used for case studies.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.547-554
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• 2016

Analyze the customer daily load patterns, be used to determine the optimal charging and discharging schedule which can minimize the electrical charges through the battery energy storage system(BESS) installed in consumers is an object of this paper. BESS, which analyzes the load characteristics of customer and reduce the peak load, is essential for optimal charging and discharging scheduling to save electricity charges. This thesis proposes optimal charging and discharging scheduling method, using particle swarm optimization (PSO) and penalty function method, of BESS for reducing energy charge. Since PSO is a global optimization algorithm, best charging and discharging scheduling can be found effectively. In addition, penalty function method was combined with PSO in order to handle many constraint conditions. After analysing the load patterns of target BESS, PSO based on penalty function method was applied to get optimal charging and discharging schedule.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.21-28
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• 2013

The paper proposes an optimal sizing method of a customer's battery energy storage system (BESS) which aims at managing the electricity demand of the customer to minimize electricity cost under the time of use(TOU) pricing. Peak load limit of the customer and charging and discharging schedules of the BESS are optimized on annual basis to minimize annual electricity cost, which consists of peak load related basic cost and actual usage cost. The optimal scheduling is used to assess the maximum cost savings for all sets of candidate capacities of BESS. An optimal size of BESS is determined from the cost saving curves via capacity of BESS. Case study uses real data from an apartment-type factory customer and shows how the proposed method can be employed to optimally design the size of BESS for customer demand management.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.