Two-stage stochastic programming model for optimal scheduling of the wind-thermal-hydropower-pumped storage system considering the flexibility assessment
Mohammadreza Daneshvar,
Behnam Mohammadi-Ivatloo,
Kazem Zare and
Somayeh Asadi
Energy, 2020, vol. 193, issue C
Abstract:
This paper presents a two-stage stochastic programming model for optimal scheduling of the wind-thermal-hydropower-pumped storage system considering the competitive interactions between the electrical generation units. The first stage is focused on the day-ahead scheduling of the thermal power plants while the balancing market dispatch is considered in the second stage using the stochastic producers and quick dispatch units. To capture the uncertainties associated with electricity demand and wind speed, Latin hyperbolic sampling and fast forward selection methods are applied for scenario generation and reduction processes, respectively. The flexibility of the studied system is analyzed considering the variations of the key parameters of thermal units and the transmission line’s capacity. For this work, the modified IEEE 14-bus standard test system integrated with the components of the studied system is selected as the case study. After solving the problem, the maximum potential of clean energy production units is used in comparison with fossil fuel-based units through the optimal scheduling of the wind-thermal-hydropower-pumped storage system. Given the numerical results, reducing the flexibility of the system by reducing the ramp up/down parameters, increasing the minimum up/down parameters, and reducing the transmission line capacity has been led to increase of 6.47%, 7.3%, and 9.77% in the total energy cost, respectively.
Keywords: Two-stage stochastic programming; Wind-thermal-hydropower-pumped storage system; Uncertainty modeling; Clean energy production; Flexibility assessment (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544219323527
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:193:y:2020:i:c:s0360544219323527
DOI: 10.1016/j.energy.2019.116657
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().