 Day-ahead stochastic coordinated scheduling for thermal-hydro-wind-photovoltaic systemsYue Yin, Tianqi Liu and Chuan He Energy, 2019, vol. 187, issue C Abstract: With the rapid development of electric power industry, the problem of dispatching renewable energy resources attracts worldwide attention. This paper presents a stochastic scheduling model to study the day-ahead coordination of a multi-source power system. The proposed stochastic scheduling model aims to find a base-case solution with relatively stable operation cost in the presence of uncertain renewable generation. Wind and photovoltaic generation uncertainties are modeled as scenarios using the Monte Carlo simulation method. Considering that wind and photovoltaic generations present complementary characteristics, scenarios are generated with correlations between wind and photovoltaic generations by Copula theory. To better reflect the characteristics of historical wind data, the fluctuation of wind power is also considered when scenarios are generated. The fast scenario reduction method is applied as a tradeoff between accuracy and computational speed. Numerical simulations indicate the effectiveness of the proposed approach in the coordinated scheduling of Thermal-Hydro-Wind- Photovoltaic systems. Keywords: Day-ahead scheduling; Renewable energy; Monte Carlo simulation; Scenarios; Copula theory (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:187:y:2019:i:c:s0360544219316287 DOI: 10.1016/j.energy.2019.115944 Access Statistics for this article Energy is currently edited by Henrik Lund and Mark J. Kaiser More articles in Energy from Elsevier |
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