A robust optimisation approach using CVaR for unit commitment in a market with probabilistic offers

W. A. Bukhsh; A. Papakonstantinou; P. Pinson

A robust optimisation approach using CVaR for unit commitment in a market with probabilistic offers

W. A. Bukhsh, A. Papakonstantinou, P. Pinson

Electronic And Electrical Engineering

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Abstract

The large scale integration of renewable energy sources (RES) challenges power system planners and operators alike as it can potentially introduce the need for costly investments in infrastructure. Furthermore, traditional market clearing mechanisms are no longer optimal due to the stochastic nature of RES. This paper presents a risk-aware market clearing strategy for a network with significant shares of RES.We propose an electricity market that embeds the uncertainty brought by wind power and other stochastic renewable sources by accepting probabilistic offers and use a risk measure defined by conditional value-at-risk (CVaR) to evaluate the risk of high re-dispatching cost due to the mis-estimation of renewable energy. The proposed model is simulated on a 39-bus network, whereby it is shown that significant reductions can be achieved by properly managing the risks of mis-estimation of stochastic generation.

Original language	English
Pages	1-6
Number of pages	6
Publication status	Accepted/In press - 1 Sept 2015
Event	IEEE International Energy Conference - Leuven, Belgium Duration: 4 Apr 2016 → 8 Apr 2016

Conference

Conference	IEEE International Energy Conference
Country/Territory	Belgium
City	Leuven
Period	4/04/16 → 8/04/16

Keywords

conditional value-at-risk
market clearing
optimal power flow
risk analysis
renewable energy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Bukhsh-etal-IEC2016-robust-optimisation-approach-using-CVaR-unit-commitment-marketAccepted author manuscript, 2.26 MB

Cite this

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abstract = "The large scale integration of renewable energy sources (RES) challenges power system planners and operators alike as it can potentially introduce the need for costly investments in infrastructure. Furthermore, traditional market clearing mechanisms are no longer optimal due to the stochastic nature of RES. This paper presents a risk-aware market clearing strategy for a network with significant shares of RES.We propose an electricity market that embeds the uncertainty brought by wind power and other stochastic renewable sources by accepting probabilistic offers and use a risk measure defined by conditional value-at-risk (CVaR) to evaluate the risk of high re-dispatching cost due to the mis-estimation of renewable energy. The proposed model is simulated on a 39-bus network, whereby it is shown that significant reductions can be achieved by properly managing the risks of mis-estimation of stochastic generation.",

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AU - Bukhsh, W. A.

AU - Papakonstantinou, A.

AU - Pinson, P.

N1 - © 2016 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

PY - 2015/9/1

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N2 - The large scale integration of renewable energy sources (RES) challenges power system planners and operators alike as it can potentially introduce the need for costly investments in infrastructure. Furthermore, traditional market clearing mechanisms are no longer optimal due to the stochastic nature of RES. This paper presents a risk-aware market clearing strategy for a network with significant shares of RES.We propose an electricity market that embeds the uncertainty brought by wind power and other stochastic renewable sources by accepting probabilistic offers and use a risk measure defined by conditional value-at-risk (CVaR) to evaluate the risk of high re-dispatching cost due to the mis-estimation of renewable energy. The proposed model is simulated on a 39-bus network, whereby it is shown that significant reductions can be achieved by properly managing the risks of mis-estimation of stochastic generation.

AB - The large scale integration of renewable energy sources (RES) challenges power system planners and operators alike as it can potentially introduce the need for costly investments in infrastructure. Furthermore, traditional market clearing mechanisms are no longer optimal due to the stochastic nature of RES. This paper presents a risk-aware market clearing strategy for a network with significant shares of RES.We propose an electricity market that embeds the uncertainty brought by wind power and other stochastic renewable sources by accepting probabilistic offers and use a risk measure defined by conditional value-at-risk (CVaR) to evaluate the risk of high re-dispatching cost due to the mis-estimation of renewable energy. The proposed model is simulated on a 39-bus network, whereby it is shown that significant reductions can be achieved by properly managing the risks of mis-estimation of stochastic generation.

KW - conditional value-at-risk

KW - market clearing

KW - optimal power flow

KW - risk analysis

KW - renewable energy

UR - http://www.ieee-energycon2016.org/

M3 - Paper

SP - 1

EP - 6

T2 - IEEE International Energy Conference

Y2 - 4 April 2016 through 8 April 2016

ER -

A robust optimisation approach using CVaR for unit commitment in a market with probabilistic offers

Abstract

Conference

Keywords

UN SDGs

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