A new three-triangle based method to linearly concave hydropower output in long-term reservoir operation
Hao Zheng,
Suzhen Feng,
Cheng Chen and
Jinwen Wang
Energy, 2022, vol. 250, issue C
Abstract:
The nonlinearity and non-convexity of the hydropower output function (HOF) make it very challenging to search for the optimal solution to the hydropower scheduling problem, which however can be more easily solved with consistency by mathematical programming if the HOF can be properly linearized with high accuracy. This paper presents a new three-triangle based method to linearly concave the HOF without introducing any integer variables, and mathematically proves its equivalence in fitting accuracy to the all-triangle based method in which any active plane needs to be compared with all the other active planes to ensure it is active within its triangular grid, making the number of constraints be increased dramatically. The two methods are applied in approximating the HOFs of 4 hydropower reservoirs located in the Lancang River. The case studies show that the present linearization method can achieve a root-mean-square error (RMSE) at 2.05% on average of the installed power capacity, the same as the all-grid concaving method, but takes only less than 0.097s in solving the problem, 80 times faster than the all-grid concaving method. The present method should be very promising in solving the real-world hydropower scheduling problems, especially when the linearization needs to be done frequently during the solution procedure.
Keywords: OR in Energy; Long-term reservoir operation; Piecewise linearization; Hydropower output function; Linear programming (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544222006879
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:250:y:2022:i:c:s0360544222006879
DOI: 10.1016/j.energy.2022.123784
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 ().