Recombining Trees for Multistage Stochastic Programs

Küchler, Christian

doi:10.1007/978-3-8348-9399-4_3

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This requires some approximations in the state variables, yet it has been shown that similar approaches provide consistent approximations to the full stochastic model (cf. Vigerske 2007 andEpe et al 2010). In order to adequately describe the stochastics of wind and solar photovoltaic, a combination of three infeed scenarios in the range of low to high feed-in is used.…”

Section: Discussionmentioning

confidence: 99%

Impact of Coordinated Capacity Mechanisms on the European Power Market

Bucksteeg¹,

Spiecker²

2019

The Energy Journal

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. AbstractThere is an ongoing debate on the introduction of capacity markets in most European countries while a few of them have already established capacity markets. Since the implementation of independent national capacity markets is not in line with the target of a pan-European internal electricity market we investigate the impacts of uncoordinated capacity markets compared with coordinated capacity markets. A probabilistic approach for the determination of capacity requirements is proposed and a European electricity market model (E2M2s) is applied for evaluation. The model simultaneously optimizes investments and dispatch of power plants.Besides the impact on generation investments, market prices and system costs we analyse effects on production and security of supply. While coordinated capacity markets reveal high potentials for cross border synergies and cost savings, uncoordinated and unilateral implementations can lead to inefficiencies, in particular free riding effects and endanger security of supply due to adverse allocation of generation capacity.

show abstract

Section: Discussionmentioning

confidence: 99%

Impact of Coordinated Capacity Mechanisms on the European Power Market

Bucksteeg¹,

Spiecker²

2019

The Energy Journal

View full text Add to dashboard Cite

show abstract

“…Here, it is essential to remember the crucial assumption: the inflow uncertainty must be stagewise independent, that is, ξHrt and ξRrt are independent of the history ξHr,t-1 and ξRr,t-1 of the process. Under this assumption, the scenario tree collapses to a so-called recombining scenario tree [31], which means that in all nodes related to month t, the same realizations ξHrt and ξRrt may occur. As a result, for each month t, there is only one FCF that does not depend on the random data.…”

Section: Solving the Ltgs Problem In Sddpmentioning

confidence: 99%

Inflow Aggregation and Run-of-the-River Inflow Energy for Reducing Dimensionality in the Long-Term Generation Scheduling Problem

Fredo

Finardi

Larroyd³

et al. 2021

IEEE Access

View full text Add to dashboard Cite

The long-term generation scheduling (LTGS) problem aims to build an operating policy over a multi-year planning horizon, correlating thermal generation and deficit costs with water storage. The LTGS is modeled as a linear multistage stochastic program, whose state-of-art solution is the stochastic dual dynamic programming (SDDP). One critical challenge is to represent the time-dependency of river inflows accurately. Despite recent advances, modeling simplifications are needed to allow the LTGS computational tractability via SDDP since it is necessary to increase the state space to include the time-dependent variables properly. Thus, most works simplify the hydro production function (HPF) to represent the inflows in detail to overcome this negative aspect. However, the literature lacks this trade-off, i.e., finding a balance between stochastic inflow modeling and HPF representation. Thus, this paper proposes an alternative approach to analyzing this trade-off, using the inflow aggregation and run-of-the-river energy inflow instead of individual inflow in SDDP. The proposed approach drastically reduces the number of state variables in SDDP, allowing a detailed HPF representation in the LTGS. We employ a one-sided confidence interval for expected cost estimation to show that our approach provides better performance than the individualized inflows. The analysis is performed in several large-scale computational instances using a power system with 53 geographically widespread hydro plants. The numerical results demonstrate that inflow aggregation provides, on average, a 4 % reduction on the operating cost, whereas for the run-of-the-river inflow energy, the reduction is, on average, 2 %. INDEX TERMS Inflow modeling, hydro production function, the long-term generation scheduling problem, stochastic dual dynamic programming, run-of-the-river inflow energy.

show abstract

Recombining Trees for Multistage Stochastic Programs

Cited by 2 publications

References 0 publications

Impact of Coordinated Capacity Mechanisms on the European Power Market

Impact of Coordinated Capacity Mechanisms on the European Power Market

Inflow Aggregation and Run-of-the-River Inflow Energy for Reducing Dimensionality in the Long-Term Generation Scheduling Problem

Contact Info

Product

Resources

About