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contributor authorJian Wang; Chuntian Cheng; Xinyu Wu; Jianjian Shen; Rui Cao
date accessioned2019-03-10T11:51:09Z
date available2019-03-10T11:51:09Z
date issued2019
identifier other%28ASCE%29WR.1943-5452.0001046.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4254379
description abstractHedging rules for hydropower operation provide optimal decisions to hedge against extreme system loss from an energy shortfall in the future at the price of a small current loss. Aiming at determining optimal end-of-year carryover storage decisions, this paper develops a hedging model for hydropower operation and proposes a corresponding numerical solving procedure to derive optimal hedging rules. The overall solving procedure involves generating possible future inflow sequences, optimizing the hedging model with nonlinear programming (NLP) technique, and plotting the hedging rule with the optimal results in condition–decision forms. Results from a case study demonstrate the correctness and feasibility of the proposed model and procedure. Performance comparison between the generated hedging rule and standard operating policy (SOP) reveals that (1) in a dry period, hedging rules could provide optimal end-of-year carryover storage, which helps achieve more benefit and suffer less system loss compared with SOP; (2) forecast uncertainty greatly affects the operation for it reduces the benefit and increases the system loss; and (3) when water is abundant, hedging becomes trivial and the generated operating rules provide similar benefit and system loss compared with SOP. The proposed procedure and the implications could be applied to determine more rational end-of-year carryover storage decisions for hydropower operation considering inflow uncertainty.
publisherAmerican Society of Civil Engineers
titleOptimal Hedging for Hydropower Operation and End-of-Year Carryover Storage Values
typeJournal Paper
journal volume145
journal issue4
journal titleJournal of Water Resources Planning and Management
identifier doi10.1061/(ASCE)WR.1943-5452.0001046
page04019003
treeJournal of Water Resources Planning and Management:;2019:;Volume ( 145 ):;issue: 004
contenttypeFulltext


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