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Source-load spatial-temporal mismatch and joint optimization of electrified transportation-distribution network

机译：Source-load spatial-temporal mismatch and joint optimization of electrified transportation-distribution network

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? 2022The development of dynamic wireless charging technology and photovoltaic distributed generation sources provides a solution to eliminating the mile anxiety of electric vehicles (EVs), however which strengthens the spatio-temporal coupling in electrified transportation-distribution network (ET-DN). In this paper, by combining the dynamic traffic assignment model of transportation networks (TNs) with the multi-period AC optimal power flow model of distribution networks (DNs), the dynamic coupling model for ET-DN is established to depict the spatio-temporal distribution of EV charging load and jam-congestion cost. We found that coordinating the EVs charging and active/reactive power resources helps to alleviate jam in TNs and congestion in DNs, while source-load spatio-temporal mismatching may lead to the deterioration of jam-congestion in ET-DN, even there are sufficient active/reactive power resources, which has an adverse impact on the system security and economy. To overcome the source-load spatio-temporal mismatching problem, a joint optimization scheme of ET-DN with dynamic distribution network reconfiguration is proposed to eliminate jam-congestion deterioration and improve the operation of ET-DN system.

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