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    A Two-stage Operating Strategy of Microgrids With Consideration of Uncertainty For Participating in Power Market

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    CIRED 2018 Ljubljana WS - 0263 - 20897.pdf (426.5Kb)
    Paper number
    0263
    Conference name
    CIRED 2018 Ljubljana Workshop
    Conference date
    7 - 8 June 2018
    Conference location
    Ljubljana, Slovenia
    Peer-reviewed
    Yes
    Metadata
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    Authors
    GAN, Lin, China Southern Power Grid, Guangzhou Power Supply CO., Ltd, China
    Mo, Wenxiong, China Southern Power Grid, Guangzhou Power Supply CO., Ltd, China
    Zhang, Zichong, China Southern Power Grid, Guangzhou Power Supply CO., Ltd, China
    WU, GuoPei, China Southern Power Grid, Guangzhou Power Supply CO., Ltd, China
    LUO, LinHuan, China Southern Power Grid, Guangzhou Power Supply CO., Ltd, China
    Zhang, Hang, China Southern Power Grid, Guangzhou Power Supply CO., Ltd, China
    Chen, Dapeng, South China University of Technology, China
    He, Hao, China Southern Power Grid, Guangzhou Power Supply CO., Ltd, China
    Abstract
    In this paper, a two-stage strategy is proposed for themicrogrid to optimize the energy bids for the day-ahead(DA) and real-time (RT) balancing market, respectively.The uncertainty of the energy prices in DA and RTmarket, the output power of renewable energy resourcesand the load demand are considered and modeled inthis paper. In the first stage, the microgridsimultaneously optimizes the energy bids in both the DAand RT market. After the DA market clearing, thecleared energy quantity and energy price are known.The microgrid re-optimizes the bids for RT marketduring the DA rebidding period. Comprehensive casestudies based on the codes and data of PJM powermarket show that the proposed strategy can minimizethe total cost of the microgrid.NOMENCLATUREp The probability of scenario p The probability of scenario ,,, ptiC The operating cost of unit i in scenariop during period t,,, ptiP The output power of unit i in scenario during period t,,tisBinary variable. 1 if unit i is scheduled onin scenario p  during period t and 0otherwise.upptiC ,,,The startup cost of unit i in scenario pduring period tbesptC ,,The charging/discharging cost of thebattery energy storage in scenario p during period tbesptP ,,The charging/discharging power of thebattery energy storage in scenario p during period tLptC ,,The cost of load curtailment in scenariop during period tlcptP ,,The load curtailed in scenario p duringperiod tdaptP , The bid power in the DA energy market inscenario prtptP , The bid power in the RT energy market inscenario pt Time intervaldaptp , The energy price in the DA market duringperiod t in scenario prtptp , The energy price in the RT market duringperiod t in scenario ploadptP ,,The forecast load demand in scenario pduring period twptP ,,The forecast output power of wind turbinein scenario p during period tpptP ,,The forecast output power of photovoltaicarrays in scenario p during period tmaxmin / ii PPThe minimum/maximum output power ofof unit idiui rr /The ramping up and ramping down limitof unit i during period tmaxmax / dcch rrThe maximum/minimum charging/discharging power of the battery energystoragebesptE ,,The energy content of the battery energystorage in scenario p during period tbesbes EE minmax / The maximum/minimum energy contentof the battery energy storagedcch  / The charging/discharging efficiency of thebattery energy storagemaxL The maximum load curtailmentmaxgridP The maximum exchanging power betweenmicrogrid and the upstream grid1.
    Publisher
    AIM
    Date
    2018-06-07
    Published in
    • CIRED 2018 Ljubljana Workshop on Microgrids and Local Energy Communities
    Permanent link to this record
    https://www.cired-repository.org/handle/20.500.12455/1261
    http://dx.doi.org/10.34890/439
    ISSN
    2032-9628
    ISBN
    978-2-9602415-1-8

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