Multistage stochastic unit commitment using stochastic dual dynamic integer programming
Unit commitment (UC) is a key operational problem in power systems for the optimal
schedule of daily generation commitment. Incorporating uncertainty in this already difficult …
schedule of daily generation commitment. Incorporating uncertainty in this already difficult …
Security-constrained unit commitment for electricity market: Modeling, solution methods, and future challenges
This paper summarizes the technical activities of the IEEE Task Force on Solving Large
Scale Optimization Problems in Electricity Market and Power System Applications. This Task …
Scale Optimization Problems in Electricity Market and Power System Applications. This Task …
Multistage stochastic power generation scheduling co-optimizing energy and ancillary services
With the increasing penetration of intermittent renewable energy and fluctuating electricity
loads, power system operators are facing significant challenges in maintaining system load …
loads, power system operators are facing significant challenges in maintaining system load …
Leaving well-worn paths: Reversal of the investment-uncertainty relationship and flexible biogas plant operation
We propose a dynamic investment model to study investment behavior for power grid-
stabilizing, flexibility-providing energy projects. Our model adds to the literature in several …
stabilizing, flexibility-providing energy projects. Our model adds to the literature in several …
Partially adaptive multistage stochastic programming
SE Kayacık, B Basciftci, AH Schrotenboer… - European Journal of …, 2024 - Elsevier
Multistage stochastic programming is a powerful tool allowing decision-makers to revise
their decisions at each stage based on the realized uncertainty. However, organizations are …
their decisions at each stage based on the realized uncertainty. However, organizations are …
A study of distributionally robust multistage stochastic optimization
J Huang, K Zhou, Y Guan - arXiv preprint arXiv:1708.07930, 2017 - arxiv.org
In this paper, we focus on a data-driven risk-averse multistage stochastic programming
(RMSP) model considering distributional robustness. We optimize the RMSP over the worst …
(RMSP) model considering distributional robustness. We optimize the RMSP over the worst …
A polyhedral study on fuel-constrained unit commitment
The electricity production of a thermal generator is often constrained by the available fuel
supply. These fuel constraints impose a maximum bound on the energy output over multiple …
supply. These fuel constraints impose a maximum bound on the energy output over multiple …
Integrated stochastic optimal self-scheduling for two-settlement electricity markets
The complexity of current electricity wholesale markets and the increased volatility of
electricity prices because of the intermittent nature of renewable generation make …
electricity prices because of the intermittent nature of renewable generation make …
Adaptive Multistage Stochastic Programming
Multistage stochastic programming is a powerful tool allowing decision-makers to revise
their decisions at each stage based on the realized uncertainty. However, in practice …
their decisions at each stage based on the realized uncertainty. However, in practice …
An adaptive model with joint chance constraints for a hybrid wind-conventional generator system
We analyze scheduling a hybrid wind-conventional generator system to make it
dispatchable, with the aim of profit maximization. Our models ensure that with high …
dispatchable, with the aim of profit maximization. Our models ensure that with high …