• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.164-170
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• 2013

The commercial buildings are consuming about 30% of total energy used in Korea. And a large amount of energy consumption in commercial buildings is consumed by HVAC(Heating, Ventilation, Air Conditioning) system. Therefore, if we can reduce the energy consumption in HVAC or air-conditioning system in commercial buildings, the overall energy consumption in Korea can be reduced. Currently, an electricity charge called Time of Use (TOU) is applied to typical commercial buildings. This paper proposes the novel energy management method where the temperature setting of air-conditioning system are adjusted to minimize the use of electrical energy while indoor comfort level is retained. The simulation test for a typical commercial building shows that the proposed method gives over 10% savings in electricity bills and electricity consumption compared to the conventional air-conditioning method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.833-839
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• 2018

This paper presents an analysis and the methodology of optimal operation strategy of the ESS(Energy Storage System) for reduce electricity charges. Electricity charges consist of a basic charge based on the contract capacity and energy charge according to the power usage. In order to use electrical energy at minimal charge, these two factors are required to be reduced at the same time. QP(Quadratic Programming) is appropriate for minimization of the basic charge and LP(Linear Programmin) is adequate to minimize the energy charge. However, the integer variable have to be introduced for modelling of different charge and discharge efficiency of ESS PCS(Power Conversion System), where MILP(Mixed Integer Linear Programming) can be used. In this case, the extent to which the peak load savings is accomplished should be assumed before the energy charge is minimized. So, to minimize the electricity charge exactly, optimization is sequentially performed in this paper, so-called the Two Stage Hybird optimization, where the extent to which the peak load savings is firstly accomplished through optimization of basic charge and then the optimization of energy charge is performed with different charge and discharge efficiency of ESS PCS. Finally, the proposed method is analyzed quantitatively with other optimization methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1278-1285
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• 2018

For saving electricity bill, energy storage system(ESS) is being installed in factories, public building and commercial building with a Time-of-Use(TOU) tariff which consists of demand charge(KRW/kW) and energy charge(KRW/kWh). However, both of peak reduction and ESS special tariff are not considered in an analysis of initial cost payback period(ICPP) on ESS. Since it is difficult to reflect base rate by an amount of uncertain peak demand reduction during mid-peak and on-peak periods in the future days. Therefore, the ICPP on ESS can be increased. Based on this background, this paper presents the advanced analysis method for the ICPP on ESS. In the proposed algorithm, the representative days of monthly electricity consumption pattern for the amount of peak reduction can be found by the k­means clustering algorithm. Moreover, the total expected energy costs of representative days are minimized by optimal daily ESS operation considering both peak reduction and the special tariff through a mixed-integer linear programming(MILP). And then, the amount of peak reduction becomes a value that the sum of the expected energy costs for 12 months is maximum. The annual benefit cost is decided by the amount of annual peak reduction. Two simulation cases are considered in this study, which one only considers the special tariff and another considers both of the special tariff and amount of peak reduction. The ICPP in the proposed method is shortened by 18 months compared to the conventional method.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.146-148
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• 2001

This paper discusses the optimal sizes of BESS. The goal must be optimized electricity charge of the customers-side with choosing the time-of-use rates. Therefore the cost is minimized by BESS installed the customers-side. Feasible ROR that means the ratio of capital costs to economic effect owned the optimal BESS sizes is determined the suitable domestic condition based on the battery cost and power converter system cost. Payback period times can be presented by BESS through the ROR. Multi-Pass Dynamic Programming(MPDP) algorithm is applied to the customer for the optimal sizes determination in this paper. It is to solve the optimal solution under the constraints. To investigate the efficiencies of the constraints, it is applied the typical load curve to the high-voltage customer owned Time-Of-Use(TOU) whether BESS is installed or not. Well, The result is obtained that feasible BESS sizes can be achieved the suitable customers-side of meter through the ROR.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.315-317
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• 2001

This paper studies for the optimal operation of BESS. The goal must be optimized electricity charge of the customer sides owned time-of-use rates in this paper. Therefore, the least of cost is caused by BESS installation, Multi-Pass Dynamic Programming (MPDP) algorithm is applied to the customer for the optimal operation determination in this paper. It is to solve the optimal solution under the constraints. No matter how become one stage in general, problem is divided into several stage in series in this algorithm. Regardless of the decision step, MPDP is only accomplished based on the state of stage in the present. To investigate the efficiencies of the algorithm, it is applied the typical load curve to the cutomer owned Time-Of-Use(TOU). Result shows that the maximun economic benefits of the battery energy storage system can be achieved by the purposed algorithm.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.192-194
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• 2006

To elucidate possible challenges for outdoor practical use of dye-sensitized solar cells(DSC), compared with conventional Si solar cells. DSC modules still need the larger area than conventional Si solar modules to attain the same rated output because of lower photoelectron-chemical conversion efficiency. However, using batteries backup systems, the measured data shows that DSCs gathered over 12% more electricity than Si solar cells of the same rated output power in same outdoor condition. Moreover, battery charging time of DSC is about 1 hour faster than same rate of Si solar module. In this paper, 12 single DSC cells prepared for 4 serialized DSC cells was connected in 3 row parallel which have same output power rate of Si solar module. This DSC module was practiced generating characteristic experiment over outdoor daylight condition and applied with PV battery charger by using DC-DC converter. The main advantages of DSC module battery charger as compared with conventional Si solar module one are shorter charge time and lower cost.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.67-77
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• 2024

Increasing energy efficiency in factories is an activity aimed at optimizing resource allocation in manufacturing processes to establish production plans. However, this strategy may not apply effectively when night shifts are unavoidable. Additionally, continuous fluctuations in production requirements pose challenges for its implementation in the factory. Recently, with the rapid proliferation of electric vehicles (EVs), technology utilizing electric vehicle batteries as energy storage systems has gained attention. Technology using these batteries can be an alternative for factory energy management. In this paper, a factory energy management method using EV batteries is proposed. The proposed method is analyzed using PSCAD/EMTDC software, considering the state of charge of EV batteries and Time-of-Use (TOU) rates. The proposed method was compared with production scheduling established considering predicted power usage and TOU rates. As a result, production scheduling saved 4,152 KRW per day, while the proposed method saved 7,286 KRW in electricity costs. Through this paper, the possibility of utilizing EV batteries for factory energy management has been demonstrated.