Journal of System Simulation
Abstract
Abstract: Aiming at the uncertainty and randomness of photovoltaic power generation affected by weather factors, a mathematical model of day ahead thermal-photovoltaic economic dispatch considering seasonal weather factors is established. The mathematical model takes the operation cost of thermal power units, the cost of photovoltaic power generation, the cost of spinning reserve and the forecast error cost of photovoltaic power generation affected by weather factors as the economic objective function, and the sulfur dioxide emission of thermal power units as the environmental objective function. In order to improve the accuracy of photovoltaic output prediction, the long short term memory neural network with seasonal weather factors is used to predict the photovoltaic power generation. The model is solved by Cplex, and the effectiveness and feasibility of the proposed model are proved by case simulation.
Recommended Citation
Liu, Xinghua; Geng, Chen; Xie, Shenghan; Tian, Jiaqiang; and Cao, Hui
(2022)
"Day Ahead Thermal-photovoltaic Economic Dispatch Considering Uncertainty of Photovoltaic Power Generation,"
Journal of System Simulation: Vol. 34:
Iss.
8, Article 20.
DOI: 10.16182/j.issn1004731x.joss.21-0336
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss8/20
First Page
1874
Revised Date
2021-05-27
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-0336
Last Page
1884
CLC
TM7
Recommended Citation
Xinghua Liu, Chen Geng, Shenghan Xie, Jiaqiang Tian, Hui Cao. Day Ahead Thermal-photovoltaic Economic Dispatch Considering Uncertainty of Photovoltaic Power Generation[J]. Journal of System Simulation, 2022, 34(8): 1874-1884.
DOI
10.16182/j.issn1004731x.joss.21-0336
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