Bi-layer optimization scheduling of energy system transmission and distribution based on IGDT with electric vehicle access
The increase in the penetration of new energy and electric vehicles in the power grid has led to a se-rious lack of flexibility of the power system in local time periods.Aiming at the existing problems of dealing with power system flexibility and supply uncertainty that are too conservative or too risky,a two-layer optimal scheduling model based on information gap decision theory(IGDT)is proposed.An energy scheduling system(ESS)including transmission and distribution is established,and a two-layer optimal scheduling strategy for EV charging and discharging is proposed on this basis.The upper layer coordinates the optimization of EVs,gensets,wind and photovoltaic power generation to minimize the cost of power supply.Meanwhile,for the sto-chastic problem of renewable energy generation,IGDT is introduced for simulation and analysis.In the lower layer optimization of the distribution network,EVs are assigned to charging nodes by introducing node loss sensitivity(NLS)and node electricity price(NEP)to minimize the grid loss cost and charging cost.Finally,the effectiveness and superiority of the proposed strategy is verified by simulation and analyses through the ESS models and IEEE 33-node standard grid.
electric vehiclesbi-layer optimizationnode electricity priceIGDT
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