ISSN 1674-0629
CN 44-1643/TK
CN 44-1643/TK
Day-Ahead Optimal Dispatch of Wind Power Distribution Network with P2H and EVs in Consideration of Source-Load Coordination
Xiao TAN , Dong HUA
›› 2023, Vol. 17 ›› Issue (4) : 144 -155.
Day-Ahead Optimal Dispatch of Wind Power Distribution Network with P2H and EVs in Consideration of Source-Load Coordination
Due to the inherent intermittence of the high proportion of renewable energy, the problem of consumption has become increasingly prominent. Electric to hydrogen and electric vehicles are important technologies for achieving energy conservation and emission reduction, and participate in grid optimization and dispatch as flexible resources, which are beneficial for the consumption of renewable energy. In this paper, a day-ahead optimal dispatch model of wind power distribution network with P2H and EVs in consideration of source-load coordination is proposed. Firstly, a model based on the energy storage and adjustable characteristics of electric to hydrogen and electric vehicles is established to realize the improvement of load characteristics. Secondly, combining the demand for wind power consumption and peak shaving and valley filling in the system, a dynamic time-sharing cost model based on power value and power change rate is proposed, and a flexible resource control strategy of source-load coordination is formed. Finally, a day-ahead dispatch model of distribution network with wind power is established, which aims at economic optimization. The simulation experiment in the modified IEEE 33-bus distribution network system shows that the proposed dispatch method can effectively reduce the total system scheduling cost and load peak-valley difference, and address wind power consumption.
source-load coordination / P2H / EV / optimal dispatch / dynamic time-sharing cost model / demand side flexible resources / wind power consumption
the Key Project of National Natural Science Foundation of China(51937005)
the Key-Area Research and Development Program of Guangdong Province(2019B111109002)
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