Continuous time multi-stage stochastic reserve and unit commitment

Kari Hreinsson; Bita Analui; Anna Scaglione

doi:10.23919/PSCC.2018.8442490

Continuous time multi-stage stochastic reserve and unit commitment

Kari Hreinsson, Bita Analui, Anna Scaglione

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

In this paper we introduce a continuous time multi stage stochastic optimization for scheduling generating units, their commitment, reserve capacities and their continuous time generation profiles in the day-ahead wholesale electricity market. Our formulation approximates the solution of a variational problem, in which the balance, generation capacity and ramping constraints are in continuous time. Due to the greater accuracy of our representation of ramping events this approach improves the system reliability and lowers the real-time cost.

Original language	English (US)
Title of host publication	20th Power Systems Computation Conference, PSCC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781910963104
DOIs	https://doi.org/10.23919/PSCC.2018.8442490
State	Published - Aug 20 2018
Event	20th Power Systems Computation Conference, PSCC 2018 - Dublin, Ireland Duration: Jun 11 2018 → Jun 15 2018

Other

Other	20th Power Systems Computation Conference, PSCC 2018
Country	Ireland
City	Dublin
Period	6/11/18 → 6/15/18

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Keywords

Continuous time unit commitment
Multistage stochastic programming
Stochastic unit commitment

ASJC Scopus subject areas

Energy Engineering and Power Technology
Computer Networks and Communications
Safety, Risk, Reliability and Quality

Cite this

Hreinsson, K., Analui, B., & Scaglione, A. (2018). Continuous time multi-stage stochastic reserve and unit commitment. In 20th Power Systems Computation Conference, PSCC 2018 [8442490] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/PSCC.2018.8442490

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AB - In this paper we introduce a continuous time multi stage stochastic optimization for scheduling generating units, their commitment, reserve capacities and their continuous time generation profiles in the day-ahead wholesale electricity market. Our formulation approximates the solution of a variational problem, in which the balance, generation capacity and ramping constraints are in continuous time. Due to the greater accuracy of our representation of ramping events this approach improves the system reliability and lowers the real-time cost.

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Access to Document

10.23919/PSCC.2018.8442490