Wind Power Scenario Generation Method and Application Based on Spatiotemporal Covariance Function

doi:10.16183/j.cnki.jsjtu.2022.180

Abstract

Abstract:

Wind power generation is different from traditional power generation in which wind power output is highly stochastic and spatio-temporally dependent. In the optimal scheduling problem of wind power grid-connected power system, ensuring the optimal execution of power scheduling in different wind power scenarios is the key of the decision-making problem. Therefore, high quality wind power scenario generation is of great importance. The spatiotemporal correlation of the output power of wind power plants are characterized based on Gaussian stochastic process and spatiotemporal covariance function, and the joint probability distribution is established by the Pair Copula model, and specific scenarios are implemented by the method of empirical probability inverse transformation. A variety of scene metrics of the generated scene are generated, which verifies the superiority of the generated scene. Finally, based on the modified IEEE 6-bus system, a mixed integer programming model for the unit output of the power system is established to solve the problems in different scenarios and verify the economic advantages of the scenario generation method in the dispatching problem of wind power grid connection.

Key words: wind power generation, scenario generation, spatiotemporal covariance function, Copula function, economic dispatch

CLC Number:

TM715

PENG Xinghao, LI Yanting. Wind Power Scenario Generation Method and Application Based on Spatiotemporal Covariance Function[J]. Journal of Shanghai Jiao Tong University, 2023, 57(12): 1531-1542.

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Copula类型	d₂
Frank	6.8323
Clayton	7.4544
Gumbel	10.2047

方法	S_E	S_V	P_c	b_AI	b_SI
M1	25.480	686.613	0.976	41.621	41.659
M2	27.091	722.756	0.983	50.279	50.303
M3	26.922	733.940	0.991	63.185	63.193
M4	28.302	751.359	0.975	63.971	62.979

方法	C_fuel	C_setup	C_RUD	C_WC	C_LS	C_AF	C_total
M1	103169	4275	5881	2046	3966	622	119959
M2	103150	4308	7526	2093	5688	1716	124459
M3	103160	4294	6523	2259	6629	888	123752
M4	103156	4309	8344	2837	6315	1845	126807