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|Title:||A risk-averse stochastic dynamic programming approach to energy hub optimal dispatch||Authors:||Moazeni, Somayeh
Miragha, Amir H.
|Keywords:||Engineering::Electrical and electronic engineering
|Issue Date:||2019||Source:||Moazeni, S., Miragha, A. H., & Defourny, B. (2019). A risk-averse stochastic dynamic programming approach to energy hub optimal dispatch. IEEE Transactions on Power Systems, 34(3), 2169-2178. doi:10.1109/TPWRS.2018.2882549||Series/Report no.:||IEEE Transactions on Power Systems||Abstract:||This paper studies the optimal operation problem of an energy hub with multiple energy sources to serve stochastic electricity and heat loads in the presence of uncertain prices as well as operational constraints, such as minimum uptime and downtime requirements. Price and demand uncertainties are modeled by stochastic processes. The goal is to minimize some risk functional of the energy hub operational cost. A stochastic dynamic optimization formulation is introduced for the problem. An approximate dynamic programming framework, based on cost function approximation, is proposed to obtain dynamic dispatch policies. The approach enables a risk-sensitive energy hub operator to consider a non-differentiable risk measure and various constraints. The performance of the approach for the energy hub dispatch problem and characteristics of the storage levels are numerically investigated.||URI:||https://hdl.handle.net/10356/104690
|ISSN:||0885-8950||DOI:||http://dx.doi.org/10.1109/TPWRS.2018.2882549||Rights:||© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TPWRS.2018.2882549||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||ERI@N Journal Articles|
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