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    Risk averse scheduling by a PEV aggregator under uncertainty

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    Publication type
    Journal article with impact factor
    Author
    Momber, Ilan
    Siddiqui, Afzal
    Gómez, Tómas
    Söder, Lennart
    Publication Year
    2015
    Journal
    IEEE Transactions on Power Systems
    Publication Volume
    30
    Publication Issue
    2
    Publication Begin page
    882
    Publication End page
    891
    
    Metadata
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    Abstract
    Research on electric power systems has considered the impact of foreseeable plug-in electric vehicle (PEV) penetration on its regulation, planning, and operation. Indeed, detailed treatment of PEV charging is necessary for efficient allocation of resources. It is envisaged that a coordinator of charging schedules, i.e., a PEV aggregator, could exercise some form of load control according to electricity market prices and network charges. In this context, it is important to consider the effects of uncertainty of key input parameters to optimization algorithms for PEV charging schedules. However, the modeling of the PEV aggregator's exposure to profit volatility has received less attention in detail. Hence, this paper develops a methodology to maximize PEV aggregator profits taking decisions in day-ahead and balancing markets while considering risk aversion. Under uncertain market prices and fleet mobility, the proposed two-stage linear stochastic program finds optimal PEV charging schedules at the vehicle level. A case study highlights the effects of including the conditional value-at-risk (CVaR) term in the objective function and calculates two metrics referred to as the expected value of aggregation and flexibility.
    Keyword
    Vehicles, Uncertainty, Stochastic Processes, System-on-chip, Electricity Supply Industry, Power Systems, Availability
    Knowledge Domain/Industry
    Entrepreneurship
    DOI
    10.1109/TPWRS.2014.2330375
    URI
    http://hdl.handle.net/20.500.12127/5092
    ae974a485f413a2113503eed53cd6c53
    10.1109/TPWRS.2014.2330375
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