optimal operation method coping with uncertainty in multi-area small power systems
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2017
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Abstract
Japan contains a vast number of isolated islands. Majority of these islands are poweredby diesel generators (DGs), which are operationally not economical. Therefore, the introduction of renewableenergy systems (RESs) into these area is very much vital. However, the variability of RESs asa result of weather condition as well as load demand , battery energy storage system (BESS) is broughtinto play. Demand response (DR) programs have also been so attractive in the energy management systemsfor the past decades. Among them, the real-time pricing (RTP) has been one of the most effectivedemand response program being utilized. This program encourages the customer to increase or reducethe load consumption by varying the electricity price. Also, due to the increase in power transactionmarket, Japan electric power exchange (JEPX) has established spot (day-ahead), intraday hour-ahead,and forward market programs. This paper utilizes day-ahead and hour-ahead markets, since these marketscan make it possible to deal with uncertainty related to generated power fluctuations. Therefore,this paper presents the optimal operation method coping with the uncertainties of RESs in multi-areasmall power systems. The proposed method enables flexibility to correspond to the forecasting error byproviding two kinds of power markets among multi-area small power systems and trading the shortageand surplus powers. Furthermore, it accomplishes a stable power supply and demand by RTP. Thus, theproposed method was able to reduce operational cost for multi-area small power systems. The processof creating operational plan for RTP, power trading at the markets and the unit commitment of DGs arealso presented in this paper. Simulation results corroborate the merit of the proposed program.
| Reference Key |
tobaru2017aimsoptimal
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| Authors | ;Shota Tobaru;Ryuto Shigenobu;Foday Conteh;Naomitsu Urasaki;Abdul Motin Howlader;Tomonobu Senjyu;Toshihisa Funabashi |
| Journal | Biology |
| Year | 2017 |
| DOI |
10.3934/energy.2017.4.718
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| URL | |
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