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Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches
2014
European Journal of Operational Research
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We demonstrate how the pricing problem for electricity swing options can be considered as a stochastic bilevel program with asymmetric information. ...
We also discuss some methods for nding numerical solutions of stochastic bilevel problems with a special emphasis on methods using duality gap penalizations. ...
Stochastic bilevel problems A bilevel problem with random parameters is called a stochastic bilevel problem. ...
doi:10.1016/j.ejor.2013.12.029
fatcat:4rks2tnpc5fh5pveovymqtx7k4
Optimal Control of Conditional Value-at-Risk in Continuous Time
[article]
2017
arXiv
pre-print
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2016 pre-print arXiv:1512.05015v2 fatcat:b3asjopaibekhcl3d2dm726jvmOther Versions
To resolve this challenge, we convert to an equivalent bilevel optimization problem in which the inner optimization problem is standard stochastic control. ...
To broaden the applicability of the proposed algorithm, we propose convergent approximation schemes in cases where our key assumptions do not hold and characterize relevant suboptimality bounds. ...
Our method can handle control problems with criteria including various combinations of (2.3), (2.4) , and (2.5). ...
arXiv:1512.05015v3
fatcat:gzhp2nbj3ndo7h7pcrxcnfqn34
Optimal Control of Conditional Value-at-Risk in Continuous Time
2017
SIAM Journal of Control and Optimization
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To resolve this challenge, we convert to an equivalent bilevel optimization problem in which the inner optimization problem is standard stochastic control. ...
To broaden the applicability of the proposed algorithm, we propose convergent approximation schemes in cases where our key assumptions do not hold and characterize relevant suboptimality bounds. ...
Our method can handle control problems with criteria including various combinations of (2.3), (2.4) , and (2.5). ...
doi:10.1137/16m1058492
fatcat:6sbskgzbkfewvojuig2rdtgzjm
Mathematical Modeling for Resources and Environmental Systems
2013
Mathematical Problems in Engineering
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bootstrap sample, such that the sampling distribution of design value was constructed; based on the sampling distribution, the uncertainty of quantile estimation could be quantified. ...
The paper "Bilevel multiobjective programming applied to water resources allocation" by S. Q. ...
bootstrap sample, such that the sampling distribution of design value was constructed; based on the sampling distribution, the uncertainty of quantile estimation could be quantified. ...
doi:10.1155/2013/674316
fatcat:n2bzvudydba7rfivnk6fr4hvb4
Optimal Adaptive Prediction Intervals for Electricity Load Forecasting in Distribution Systems via Reinforcement Learning
[article]
2022
arXiv
pre-print
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Compared with offline-trained methods, it obtains PIs with better quality and is more robust against concept drift. ...
It relies on the online learning ability of reinforcement learning to integrate the two online tasks, i.e., the adaptive selection of probability proportion pairs and quantile predictions, both of which ...
ACKNOWLEDGEMENT This work was supported by the National Natural Science Foundation of China (U1866206). ...
arXiv:2205.08698v1
fatcat:6t765kbvibe3lgu3q6miterzqi
Microgrid management with weather-based forecasting of energy generation, consumption and prices
[article]
2021
arXiv
pre-print
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Most of the generation technologies based on renewable sources are non-dispatchable, and their production is stochastic and complex to predict in advance. ...
(2) How to make decisions with uncertainty using probabilistic forecasts? ...
programming and approaches to handle
uncertainty in the parameters with the stochastic programming and robust approach. ...
arXiv:2107.01034v7
fatcat:c5a7d2w2uzez3par3q6gs3elaq
A review of short‐term wind power probabilistic forecasting and a taxonomy focused on input data
2021
IET Renewable Power Generation
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The short-term concept of forecasts is analysed in detail, along with the case studies and examples proposed by the reviewed literature. ...
The improvement of the accuracy and efficiency of probabilistic forecasting models has been in the centre of attention of researchers in recent years, since the need to further comprehend and efficiently ...
ACKNOWLEDGEMENTS This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH ...
doi:10.1049/rpg2.12330
fatcat:wk2piydl4fcrvd22jq5qsc7aem
Modeling the shelter site location problem using chance constraints: A case study for Istanbul
2018
European Journal of Operational Research
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In particular, we propose a maxmin probabilistic programming model that includes two types of probabilistic constraints: one concerning the utilization rate of the selected shelters and the other concerning ...
By invoking the central limit theorem we are able to obtain an optimization model with a single set of non-linear constraints which, nonetheless, can be approximated using a family of piecewise linear ...
Acknowledgments This research has been partially supported by the Turkish Academy of Sciences and by the Portuguese Science Foundation , projects UID/MAT/04561/2013 (CMAF-CIO/FCUL) and UID/MAT/00297/2013 ...
doi:10.1016/j.ejor.2018.03.006
fatcat:xy7hhccnfzbwfa7gs6og75k5va
Challenges in the Application of Mathematical Programming in the Enterprise-wide Optimization of Process Industries
2014
Теоретические основы химической технологии
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in the information societyShunei Norikumo
Robustness in stochastic programs with the first order stochastic dominance and/or probabilistic constraints Milos Kopa, Jitka Dupacova 2 -Chance constrained ...
problem, where the technology coefficients in the stochastic constraints are normally distributed random variables Andras Prekopa, Tamas Szantai 2 -Solution of probabilistic constrained stochastic programming ...
OEE simulation Werner Schroeder, Markus Gram
-A Two Stage Solution Procedure of Stochastic Programming Problem for Production Planning with Advance Demand Information Nobuyuki Ueno, Koji Okuhara, Takashi ...
doi:10.7868/s0040357114050054
fatcat:kli7aeuyxbaplfhup2t6nmuyxq
Challenges in the application of mathematical programming in the enterprise-wide optimization of process industries
2014
Theoretical foundations of chemical engineering
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in the information societyShunei Norikumo
Robustness in stochastic programs with the first order stochastic dominance and/or probabilistic constraints Milos Kopa, Jitka Dupacova 2 -Chance constrained ...
problem, where the technology coefficients in the stochastic constraints are normally distributed random variables Andras Prekopa, Tamas Szantai 2 -Solution of probabilistic constrained stochastic programming ...
OEE simulation Werner Schroeder, Markus Gram
-A Two Stage Solution Procedure of Stochastic Programming Problem for Production Planning with Advance Demand Information Nobuyuki Ueno, Koji Okuhara, Takashi ...
doi:10.1134/s0040579514050182
fatcat:3ra5yqooyzgmroo5qccbnauftm
Optimization of real asset portfolio using a coherent risk measure: application to oil and energy industries
2010
Optimization and Engineering
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We consider the problem of optimally determining an investment portfolio for an energy company owning a network of gas pipelines, and in charge of purchasing, selling and distributing gas. ...
As a consequence, state of the art planning models are stochastic, and usually consider some kind of risk measure as well as financial instruments to hedge the investment portfolio. ...
Fig. 5 5 CPU time of equivalent deterministic problem versus number of scenarios.
Fig. 6 6 Asset allocation with the deterministic and stochastic models. ...
doi:10.1007/s11081-010-9127-x
fatcat:7tyrior32zcwzi4zejfw7ilc64
On Exponential Utility and Conditional Value-at-Risk as Risk-Averse Performance Criteria
[article]
2021
arXiv
pre-print
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For EU, the transformation is φ(y) = exp(-θ/2y), and under certain conditions, the quantity φ^-1(E(φ(Y))) can be approximated by a linear combination of the mean and variance of Y. ...
Here, we study the applications of risk-averse functionals to controller synthesis and safety analysis through the development of numerical examples, with emphasis on EU and CVaR. ...
ACKNOWLEDGMENTS The authors thank Laurent Lessard, Claire Tomlin, Marco Pavone, and Chuanning Wei for fruitful discussions. ...
arXiv:2108.01771v1
fatcat:cq7xitkkqbg3lha76pg74pw4l4
An approach to the distributionally robust shortest path problem
[article]
2020
arXiv
pre-print
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Under some additional assumptions the resulting distributionally robust shortest path problem (DRSPP) admits equivalent robust and mixed-integer programming (MIP) reformulations. ...
The ambiguity set is formed by all distributions that satisfy prescribed linear first-order moment constraints with respect to subsets of arcs and individual probability constraints with respect to particular ...
The article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (Sections 1-4) and RFBR grant 20-37-90060 (Sections 5-6). ...
arXiv:1910.08744v3
fatcat:ewhvgxddxbgwdd3hten37rk4fe
The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping
2013
European Journal of Operational Research
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of planning and vehicle-routing models, d) optimization of oilfield infrastructures under uncertainty that lead to multistage stochastic programming problems with endogenous uncertain parameters. ...
We illustrate the application of these ideas in four major problems: a) integration of planning and scheduling in batch processes that lead to large-scale mixed-integer linear programs, b) optimization ...
to solve a stochastic program with individual probabilistic constraints. ...
doi:10.1016/j.ejor.2012.08.016
fatcat:c27kagfnxnhjfbil2rydhjhomm
Energy and reserve scheduling under correlated nodal demand uncertainty: An adjustable robust optimization approach
2014
2014 Power Systems Computation Conference
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The resulting problem is formulated as a trilevel program and solved by means of Benders decomposition. ...
In this model, up-and down-spinning reserves provided by generators are endogenously defined as a result of the optimization problem. ...
ACKNOWLEDGMENT The authors would like to thank FICO (Xpress-MP developer) for the academic partnership program with the Electrical Engineering Department of the Pontifical Catholic University of Rio de ...
doi:10.1109/pscc.2014.7038415
dblp:conf/pscc/MoreiraSA14
fatcat:yriybdcb4zddvcgoh2pklm4y4y
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