• Journal of Power Electronics
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• v.11 no.4
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• pp.479-489
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• 2011

The bidirectional dc-dc converter, being the interface between Energy Storage Element (ESE) and DC bus, is an essential component of the power management system for vehicle applications including electric vehicle (EV), hybrid electric vehicle (HEV), and fuel cell vehicle (FCV). In this paper, a novel multiphase bidirectional dc-dc converter interfacing with battery to supply and absorb the electric energy in the FCV system was studied with the help of real time digital simulator (RTDS). The mathematical models of fuel cell, battery and dc-dc converter were derived. A power management strategy was developed and first simulated in RTDS. A Power Hardware-In-the-Loop (PHIL) simulation using RTDS is then presented. The main challenge of this PHIL is the requirement for a highly dynamic bidirectional Simulation-Stimulation (Sim-Stim) interface. This paper describes three different interface algorithms. The closed-loop stability of the resulting PHIL system is analyzed in terms of time delay and sampling rate. A prototype bidirectional Sim-Stim interface is designed to implement the PHIL simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.3
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• pp.335-340
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• 2011

Building energy saving is one of the most important issues in these days. Control algorithm for energy saving should be designed properly to reduce power consumption in building. Recently, building energy system consists of hybrid energy system coupling with RE (Renewable Energy) source. In this paper, an optimum control algorithm for building energy saving is applied to BEMS (Building Energy Management System) by using an outdoor air temperature prediction strategy. BEMS coupling with renewable energy can control HVAC (Heating, Ventilating and Air-Conditioning) system effectively. In order to verify the effectiveness of building energy saving, BEMS was tested for several months at a laboratorial chamber with an air conditioner, fan and heater. To this end BEMS embedded control algorithm has been tested successfully.

• Design & Manufacturing
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• v.15 no.3
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• pp.50-55
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• 2021

Solar power generation, which is one of the methods of using solar energy, has a high possibility of practical implementation compared to other renewable energy power generation, and it has the characteristic that it can generate as much power as needed in necessary places. In addition, maintenance is easy, unmanned operation is possible, and power management can be performed more efficiently if operated in a hybrid method with existing electric energy. Therefore, in this study, numerical analysis using a computer program was performed to analyze the efficient operation and performance improvement of solar energy of the rotating condensing type solar LED street lamp. As a result, the two-axis tracking type could obtain 15.23 % more electricity per year than the fixed type, and additional auxiliary power generation was required for the fixed type by 19 % per year than the tracking type. As a result of computational fluid dynamics(CFD) simulation for PV module surface temperature prediction, the The surface temperature of the Photovoltaics(PV) module incident surface was predicted to be about 10℃ higher than that of the fixed type.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.231-235
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• 2015

Bimodal Tram developed by KRRI is driven by a series Hybrid propulsion system which has both the CNG engine, generator and LPB(Lithium Polymer Battery) pack. It has three driving modes; Hybrid mode, Engine mode and Battery mode. Even in case of Battery mode, LPB pack to get enough power to drive the vehicle only by itself onsists of 168 LPB cells(80Ah per lcell), 650V. It is important thing to manage LPB pack in a right way, which will extend the lifetime of LPB cells and operate in the hybrid mode effectively. This paper has shown the development of battery management system(12 BMS, 1 BMS per 14cells) to manage LPB pack which is connected with CAN(Controller Area Network) each other and measure the voltage, current, temperature and also control the cooling fan inside of LPB pack. Using the measured data, BMS can show the SOC(State of Charge), SOH(State of Health) and other status of LPB pack including of the cell balancing.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.46-51
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• 2012

Fuel Cell Hybrid Vehicles (FCHVs) have become a major topic of interest in the automotive industry owing to recent energy supply and environmental problems. Several types of power management strategies have been developed to improve the fuel economy of FCHVs including optimal control strategy based on optimal control theory, rule-based strategy, and equivalent consumption minimization strategy (ECMS). The ECMS is applied in this study. This strategy is based on the heuristic concept that the usage of the electric energy can be exchanged to equivalent fuel consumption. This strategy is known as one of the promising solutions for real-time control of hybrid vehicles. The ECMS for an FCHV is introduced in this paper as well as the equivalent fuel consumption parameter. The relationship between the battery final state of charge (SOC) and the fuel consumption while changing the equivalent fuel consumption parameter is obtained for three different driving cycles. The function of the equivalent fuel consumption parameter is also discussed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.6
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• pp.631-638
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• 2022

Microgrid, which enables the production and consumption of electricity to be done independently on a small scale, has been studied on one of the solutions of reinforcement for flexibility of electronic system. This study examined the application effect of new microgrid by applying hybrid battery in electric power storage device. We designed the system to highlight the advantage of each battery and complement the disadvantage by using hybrid system with Lithium-ion battery and interval Redox flow battery. It runs with lithium-ion battery during the initial startup while the Redox flow battery operates for a long time at the end of excessive period, and it enables a discharge of Lithium-ion and Redox flow battery at the same time when the load has a large output. We chose Maldives as a subject of this study for organizing and optimizing independent microgrid. Maldives is the country to accomplish 100% domestic electricity in South Asia, but the whole electric power is supplied through diesel generation imported fossil fuel. We organized and optimized microgrid for energy independence on Malahini island to solve Maldives energy cost problem and global energy environment matters. We analyzed the daily power supply and accumulated the power supply from September 18, 2018~February 11, 2019. The accumulated power supply was about 120.4 MWh and the daily power supply was about 800~1000 kWh. Based on the collected information, we divided the cases into three models which are only diesel generator, solar generator as well as diesel generator, and solar+ESS+diesel generator. We analyzed the amount of oil consumption compared to the cost of construction and power output. The result showed that solar+ESS+diesel generator was most economically feasible. As well, we obtained that our considering hybrid battery system reduced the fuel consumption for diesel power generation about 10~15%.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.715-724
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• 2023

Solar energy forecasting is essential for (1) power system planning, management, and operation, requiring accurate predictions. It is crucial for (2) ensuring a continuous and sustainable power supply to customers and (3) optimizing the operation and control of renewable energy systems and the electricity market. Recently, research has been focusing on developing solar energy forecasting models that can provide daily plans for power usage and production and be verified in the electricity market. In these prediction models, various data, including solar energy generation and climate data, are chosen to be utilized in the forecasting process. The most commonly used climate data (such as temperature, relative humidity, precipitation, solar radiation, and wind speed) significantly influence the fluctuations in solar energy generation based on weather conditions. Therefore, this paper proposes a hybrid forecasting model by combining the strengths of the Prophet model and the GRU model, which exhibits excellent predictive performance. The forecasting periods for solar energy generation are tested in short-term (2 days, 7 days) and medium-term (15 days, 30 days) scenarios. The experimental results demonstrate that the proposed approach outperforms the conventional Prophet model by more than twice in terms of Root Mean Square Error (RMSE) and surpasses the modified GRU model by more than 1.5 times, showcasing superior performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1455-1463
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• 2017

Global economy has recorded low growth, low consumption, high unemployment rate, high risk, short boom and long recession. As a result, maritime economy declines and the reduction of maintenance costs is inevitable. Thus, Studies such as green ship, eco ship, and smart ship are being actively conducted to save energy of ship. Power management system that use batteries in green ship is an important research area. In this paper, we analyze the heavy load control of a power management system of a general ship using only a generator, and study a heavy load control algorithm for a battery connected power management system. To study this, a structure of battery connected power management system is proposed and a battery connected power simulator was constructed based on the proposed system. Through the simulator, the operation of the battery according to the heavy load control is defined and confirmed in the battery connected power management system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3391-3398
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• 2015

Recently, the large scaled lead-acid battery is widely introduced to efficient operation of the photovoltaic system in many islands. but the demand of lithium-ion battery is getting increased by the operation of wind power and replacement of the lead-acid battery. And also, under the renewable portfolio standard(RPS) and energy efficiency resource standard(EERS) policy of Korea government, the introduction of energy storage system(ESS) has been actively increased. Therefore, this paper presents the operation algorithm of hybrid battery management system(BMS) using the lead-acid and lithium-ion batteries, in order to maximize advantage of each battery. In other words, this paper proposed the algorithm of state of charge(SOC) and hybrid operation algorithm to calculate the optimal composition rate considering the fixed cost and operation cost of each battery. From the simulation results, it is confirmed that the proposed algorithms are an effective tool to evaluate SOC and to optimally operate hybrid ESS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5904-5927
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• 2019

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.