Dynamic Environmental Economic Dispatch Considering the Uncertainty and Correlation of Photovoltaic–Wind Joint Power

The traditional power grid planning lacks consideration of the uncertainty and correlation between wind and solar joint output in the same region, which poses challenges to the stable operation of the power system. Therefore, it is greatly important to consider the environmental and economic dispatch in light of the uncertainties and correlations associated with wind and solar energy. To tackle these issues, this paper introduces a dynamic environmental economic dispatch model that accounts for the uncertainties and correlations between wind and photovoltaic power based on their output characteristics. Initially, a probability model for photovoltaic–wind joint power is established using the Copula function. Subsequently, the Latin hypercube sampling method is employed alongside an improved K-means clustering technique to derive typical output scenarios. An adaptive multi-objective fireworks algorithm, featuring a differential selection strategy, is then utilized to enhance the environmental economic dispatch model. Finally, the IEEE 39 node system is used as an example to demonstrate the solution of the dynamic environmental and economic scheduling model. Simulation results reveal that the method for generating typical output scenarios presented in this paper effectively captures the uncertainties and correlations of photovoltaic–wind joint power. Furthermore, when compared to other optimization algorithms, the improved adaptive multi-objective fireworks algorithm proves to be more efficient in addressing the dynamic environmental economic dispatch challenges within the power system.

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Publication Details

Journal
Energies
Published
2024-12-11
DOI
https://doi.org/10.3390/en17246247
Citations
3
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.63

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article

Dynamic Environmental Economic Dispatch Considering the Uncertainty and Correlation of Photovoltaic–Wind Joint Power

Di Zheng, Yi Hong Ru, Ying Wang, Wenqian Fang et al.
3 citations
Energies
Integrated Energy Systems Optimization
0.63
article

Dynamic Environmental Economic Dispatch Considering the Uncertainty and Correlation of Photovoltaic–Wind Joint Power

Di Zheng, Yi Hong Ru, Ying Wang, Wenqian Fang, Mao Weijun
article en
3 citations

Abstract

The traditional power grid planning lacks consideration of the uncertainty and correlation between wind and solar joint output in the same region, which poses challenges to the stable operation of the power system. Therefore, it is greatly important to consider the environmental and economic dispatch in light of the uncertainties and correlations associated with wind and solar energy. To tackle these issues, this paper introduces a dynamic environmental economic dispatch model that accounts for the uncertainties and correlations between wind and photovoltaic power based on their output characteristics. Initially, a probability model for photovoltaic–wind joint power is established using the Copula function. Subsequently, the Latin hypercube sampling method is employed alongside an improved K-means clustering technique to derive typical output scenarios. An adaptive multi-objective fireworks algorithm, featuring a differential selection strategy, is then utilized to enhance the environmental economic dispatch model. Finally, the IEEE 39 node system is used as an example to demonstrate the solution of the dynamic environmental and economic scheduling model. Simulation results reveal that the method for generating typical output scenarios presented in this paper effectively captures the uncertainties and correlations of photovoltaic–wind joint power. Furthermore, when compared to other optimization algorithms, the improved adaptive multi-objective fireworks algorithm proves to be more efficient in addressing the dynamic environmental economic dispatch challenges within the power system.

EnergiesVol. 17(24)
China Jiliang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Affordable and clean energy
Openalex Percentile: Top 30%
Integrated Energy Systems Optimization
0.63
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