With the rapid and large-scale development of renewable energy, the lack of\nnew energy power transportation or consumption, and the shortage of grid\npeak-shifting ability have become increasingly serious. Aiming to the severe\nwind power curtailment issue, the characteristics of interactive load are studied\nupon the traditional day-ahead dispatch model to mitigate the influence\nof wind power fluctuation. A multi-objective optimal dispatch model with the\nminimum operating cost and power losses is built. Optimal power flow distribution\nis available when both generation and demand side participate in the\nresource allocation. The quantum particle swarm optimization (QPSO) algorithm\nis applied to convert multi-objective optimization problem into single\nobjective optimization problem. The simulation results of IEEE 30-bus system\nverify that the proposed method can effectively reduce the operating cost and\ngrid loss simultaneously enhancing the consumption of wind power.
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