The main goal of this paper is to comprehensively model demand dispatch (DD) operation concept on prosumer plug in electric vehicles (PEVs) in the framework of a microgrid in a smart distribution grid. Method: Here, PEVs role as demand side assets that make commitments as dispatchable time-flexible prosumers with microgrid operator (MGO). Therefore, they directly help MGO in efficient operation of the microgrid. Modeling and formulation of the proposed one level MG-PEVs-DD optimization problem, considering convenience of PEV drivers, MG operation reliability and loss of load, are investigated in this paper. In order to investigate the effect of various levels of DD commitment on MG operation cost and quantify worthiness brought by DD, a DD participation index (DDP) is defined. Moreover, extensive simulations are carried out on different days of the year to verify weather conditions, which influence MG generation and operation cost. The LP optimization operation problem for 24 hours of the day is solved by classic optimization in MATLAB. Results: The effectiveness of the proposed model is demonstrated on a realtest MG system under different scenarios of conventional operation and other scenarios of applying DD. Simulation results reveal that the proposed MGPEVs-DD model yields much more decrement in microgrid operation cost in comparison with conventional operation methods. Results show that increasing DDP index of PEVs, significantly decreases the cost of microgrid operation. Moreover, PEV driver\\\'s convenience has been suitably considered by the MGO through the suggested method. MG total operation cost for the cloudy coldest day of the year, is approximately twice higher than the sunny hottest day due to considerable decrement of output solar power generation in cloudy days. Discussion: Consumer-side asset optimization by utilizing dispatchable assets, like PEVs or dispatchable loads would considerably help in handling the uncertainty in MG operation through demand dispatch operation concept with lower operation cost.

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