• Title/Summary/Keyword: Proportion of optimal storage-capacity

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Study on the optimal storage-capacity based on the commodity volume in apartments - Focused on $85m^2$ apartment - (물품부피에 근거한 적정수납용적에 관한 연구 - 30평형대 아파트를 중심으로 -)

  • Lee, Youn-Jae;Kim, Joon-Ji;Lee, Hyun-Soo
    • Korean Institute of Interior Design Journal
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    • v.15 no.6 s.59
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    • pp.139-149
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    • 2006
  • Because of economic growth and the social trend to respect individuality, people's average commodity volume tends to increase. It makes people perceive the importance of storage space. The storage planning without consideration of commodity volume in the apartment can not satisfy the needs of residents. This study is developed focused on the $85m^2$ apartment which is the most representative and general type. The objectives of the study are to investigate the storage-capacity of $85m^2$ apartment offered by 4 construction companies to know the present storage condition, to investigate the average volumes and type of commodities in 30 families located in Seoul and Kyungkido to produce the necessary storage-capacity, and lastly to produce optimal storage-capacity and proportion of optimal storage-capacity considering the volume of the furniture owned by each resident. The results of the study are 1) the storage capacity for commodity volume in $85m^2$ apartment is $19.41m^3$. 2) the optimal storage-capacity which only counts the storage volume of built-in furniture is $17.14m^3$ 3) the proportion of optimal storage-capacity is 9.5% of the house-capacity.

A Study on the Optimal Operation According to Appropriate PCS and Battery Capacity Estimation of PV-BESS System (PV-BESS 시스템의 적정 PCS, 배터리용량 산정에 따른 최적 운영에 관한 연구)

  • Choi, Yun Suk;Na, Seung You
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.9
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    • pp.1174-1180
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    • 2018
  • In December 2017, the government announced plans to increase the current proportion of renewable energy from 7% to 20% by 2030 through a plan called the Renewable Energy 3020 Implementation Plan. Therefore, the demand for installation of photovoltaic(PV), wind turbine(WT) and battery energy storage system(BESS) is expected to increase. In particular, the system combined with energy storage system(ESS) is expected to take up a large portion since PV and WT can receive high renewable energy certificates(REC) weights when combined with ESS. In this study, we calculate the optimal capacity of the power conditioning system(PCS) and the BESS by comparing the economical efficiency and maximize the efficiency of the PV-BESS system in which the PV and the BESS are connected. By analyzing the system marginal price(SMP) and REC, it maximize profits through application of REC weight 5.0 and optimal charge-discharge scheduling according to the SMP changes.

Determining the Optimal Capacities of Distributed Generators Installed in A Stand-alone Microgrid Power System (독립형 마이크로그리드 내 분산전원별 최적용량 결정 방법)

  • Ko, Eun-Young;Baek, Ja-Hyun;Kang, Tae-Hyuk;Han, Dong-Hwa;Cho, Soo-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.2
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    • pp.239-246
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    • 2016
  • In recent years, the power demand has been increasing steadily and the occurrence of maximum power demand has been moving from the summer season to the winter season in Korea. And since the control of electric power supply and demand is more important under those situations, a micro-grid system began to emerge as a keyword for the sTable operation of electric power system. A micro-gird power system is composed of various kinds of distributed generators(DG) such as small diesel generator, wind turbine, photo-voltaic generator and energy storage system(ESS). This paper introduces a method to determine the optimal capacities of the distributed generators which are installed in a stand-alone type of microgrid power system based on the fundamental proportion of diesel generator. At first, the fundamental proportion of diesel generator will be determined by changing from 0 to 50 percent. And then we will optimize the capacities of renewable energy resources and ESS according to load patterns. Lastly, after recalculating the capacity of ESS with consideration for SOC constraints, the optimal capacities of distributed generators will be decided.