Equilibrium approach to the single solution of longer- and shorter-term hydro-thermal scheduling problems

Bernardinelli, Luisa; Martins, L. S. A.

doi:10.1109/iccep.2017.8004730

Cited by 4 publications

(5 citation statements)

References 21 publications

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“…3. If not, add a new feasibility cut of type (9) to C F at for EERs with infeasible trial solutions. To limit the computational expense involved with solving (6), it was found efficient checking hydropower feasibility only in the forward SDDP iteration.…”

Section: B Dynamic Feasibility Cutsmentioning

confidence: 99%

“…2. Dynamic Feasibility Cuts (DYN-FC) using the same SDDP formulation as in REF, but with dynamic construction and addition of feasibility cuts (9) in the forward SDDP iterations, as described in Section IV-B. 3.…”

Section: A System and Case Descriptionmentioning

confidence: 99%

“…3. Static Feasibility Cuts (STAT-FC) using the same SDDP formulation as in REF, but with pre-computed feasibility cuts (9) as described in Section IV-C. For case DYN-FC, 200 new feasibility cuts are built in each forward iteration for each stage. These cuts will accumulate with the forward iterations.…”

Section: A System and Case Descriptionmentioning

confidence: 99%

“…While LTS models emphasize on the representation of uncertainties over the planning horizon typically using a rather coarse description of the technical system, shorter-term models are oriented towards deterministic formulations and a detailed physical system description [6], [7]. System simplifications in LTS models could lead to time-inconsistent policies [8], revealing a need for embedding more details from the short-term scheduling into LTS models [9].…”

Section: Introductionmentioning

confidence: 99%

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Hydropower Aggregation by Spatial Decomposition—An SDDP Approach

Helseth

2023

IEEE Trans. Sustain. Energy

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The balance between detailed technical description, representation of uncertainty and computational complexity is central in long-term scheduling models applied to hydro-dominated power system. The aggregation of complex hydropower systems into equivalent energy representations (EER) is a commonly used technique to reduce dimensionality and computation time in scheduling models. This work presents a method for coordinating the EERs with their detailed hydropower system representation within a model based on stochastic dual dynamic programming (SDDP). SDDP is applied to an EER representation of the hydropower system, where feasibility cuts derived from optimization of the detailed hydropower are used to constrain the flexibility of the EERs. These cuts can be computed either before or during the execution of the SDDP algorithm and allow system details to be captured within the SDDP strategies without compromising the convergence rate and statespace dimensionality. Results in terms of computational performance and system operation are reported from a test system comprising realistic hydropower watercourses.

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Section: B Dynamic Feasibility Cutsmentioning

confidence: 99%

Section: A System and Case Descriptionmentioning

confidence: 99%

Section: A System and Case Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hydropower Aggregation by Spatial Decomposition—An SDDP Approach

Helseth

2023

IEEE Trans. Sustain. Energy

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“…By contrast, those corresponding to the cases where the water value is computed with Model 2 are by far the highest. The "extreme" behaviour of both the models is due to the modelling inconsistencies existing between the short-term scheduling and the medium-term one, as discussed in [39] and [40]. Model 1/Model 2 tends to underestimate/overestimate the plant's water value [25], and for this reason, the short-term scheduling model tends to keep a lower/higher reservoir volume than in the cases where the water value was computed with Model 3 and Model 4, which are consistent with the power plant's operation strategy.…”

Section: Number Of Integer Variablesmentioning

confidence: 99%

Medium-term scheduling of a hydropower plant participating as a price-maker in the automatic frequency restoration reserve market

Pérez‐Díaz

Guisández

Chazarra

et al. 2020

Electric Power Systems Research

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Hydropower Aggregation by Spatial Decomposition – An SDDP Approach

Helseth¹,

Mo²

2022

Preprint

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The balance between detailed technical description, representation of uncertainty and computational complexity is central in long-term scheduling models applied to hydro-dominated power system. The aggregation of complex hydropower systems into equivalent energy representations (EER) is a commonly used technique to reduce dimensionality and computation time in scheduling models. This work presents a method for coordinating the EERs with their detailed hydropower system representation within a model based on stochastic dual dynamic programming (SDDP). SDDP is applied to an EER representation of the hydropower system, where feasibility cuts derived from optimization of the detailed hydropower are used to constrain the flexibility of the EERs. These cuts can be computed either before or during the execution of the SDDP algorithm and allow system details to be captured within the SDDP strategies without compromising the convergence rate and state-space dimensionality. Results in terms of computational performance and system operation are reported from a test system comprising realistic hydropower watercourses.<br>

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Equilibrium approach to the single solution of longer- and shorter-term hydro-thermal scheduling problems

Cited by 4 publications

References 21 publications

Hydropower Aggregation by Spatial Decomposition—An SDDP Approach

Hydropower Aggregation by Spatial Decomposition—An SDDP Approach

Medium-term scheduling of a hydropower plant participating as a price-maker in the automatic frequency restoration reserve market

Hydropower Aggregation by Spatial Decomposition – An SDDP Approach

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