2016
DOI: 10.1109/tpwrs.2015.2424974
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Tutorial on Stochastic Optimization in Energy—Part I: Modeling and Policies

Abstract: There is a wide range of problems in energy systems that require making decisions in the presence of different forms of uncertainty. The fields that address sequential, stochastic decision problems lack a standard canonical modeling framework, with fragmented, competing solution strategies. Recognizing that we will never agree on a single notational system, this two-part tutorial proposes a simple, straightforward canonical model (that is most familiar to people with a control theory background), and introduce… Show more

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Cited by 113 publications
(39 citation statements)
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“…Sample future power scenarios can be produced by considering all three stochastic models to be probable in the future. These scenarios are quite useful while solving stochastic optimization problems such as designing a battery storage policy [46]. This is future work.…”
Section: Discussionmentioning
confidence: 99%
“…Sample future power scenarios can be produced by considering all three stochastic models to be probable in the future. These scenarios are quite useful while solving stochastic optimization problems such as designing a battery storage policy [46]. This is future work.…”
Section: Discussionmentioning
confidence: 99%
“…A wide range of O&M processes can be modeled as a Markov process in continuous time, by selecting an appropriate set of state variables (e.g., these variables describe the complex evolution of damage patterns in structural systems). [17][18][19] This process can be converted into an approximate POMDP, by discretizing the time and domain of possible states and by defining costs, available actions, and corresponding transitions. 14,20 In turn, the POMDP can be solved by implementing an appropriate numerical scheme to identify the optimal control policy.…”
Section: Problem Statementmentioning
confidence: 99%
“…One widely used approach to capture the uncertainties in renewable resources is by using a set of timeseries scenarios [3]. By using a set of possible power generation scenarios, renewables producers and system operators are able to make decisions that take uncertainties into account, such as stochastic economic dispatch/unit commitment, optimal operation of wind and storage systems, and trading strategies (e.g., see [4], [5], [6], [7] and the references within).…”
Section: Introductionmentioning
confidence: 99%