This paper proposes a computationally-effective method for optimal operation of multiple distributed generations (DGs) in DC distribution systems to improve their efficiency. There have been many researches to select the optimal sizes of multiple DGs. However, these optimal sizes are valid only in the particular operating point. For optimal operations of power systems, the DG sizes must be determined all the time according to the various load conditions. The proposed method can maintain the distribution system operating in its optimal condition with only single optimization process, without regard to load variations. Therefore, it can moderate the serious problems, derived from inaccurate load forecasting. To verify the performance of the proposed method, the DC system is first implemented with the real distribution system of Do-gok area in Seoul, Korea. Then, the real hourly-load data, acquired from SCADA system in Korea, are used to simulate the practical load variations.
|Title of host publication||Conference Record - 2016 IEEE/IAS 52nd Industrial and Commercial Power Systems Technical Conference, I and CPS 2016|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 2016 Jun 10|
|Event||52nd IEEE/IAS Industrial and Commercial Power Systems Technical Conference, I and CPS 2016 - Detroit, United States|
Duration: 2016 May 1 → 2016 May 5
|Name||Conference Record - Industrial and Commercial Power Systems Technical Conference|
|Other||52nd IEEE/IAS Industrial and Commercial Power Systems Technical Conference, I and CPS 2016|
|Period||16/5/1 → 16/5/5|
Bibliographical noteFunding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2011-0028065) and in part by Power Generation & Electricity Delivery Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted fmancial resource from Ministry of Trade, Industry & Energy, Korea (20141020402340).
© 2016 IEEE.
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