Contributing to DSO’s Energy-Reserve Pool: A Chance-Constrained Two-Stage μ VPP Bidding Strategy

Hao Fu; Zhi Wu; Xiao-ping Zhang; Joachim Brandt

doi:10.1109/JPETS.2017.2749256

Contributing to DSO’s Energy-Reserve Pool: A Chance-Constrained Two-Stage μ VPP Bidding Strategy

Hao Fu, Zhi Wu, Xiao-ping Zhang, Joachim Brandt

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Abstract

This paper presents the strategic proposition for a micro virtual power plant (μ VPP) to participate in the distribution level energy-reserve pool managed by a distribution system operator. A chanceconstrained two-stage stochastic formulation is proposed to derive the bidding strategy for μ VPP maximizing its daily profit. The stochastic nature of renewable generation and load profile of the μ VPP is captured by the Monte Carlo method. The security of supply is guaranteed by controlling the loss of load probability, which is modeled as chance constraint. The numerical tests are performed on μ VPPs with different penetration levels of distributed energy resource (DER) and renewable energy source (RES), where the impact of the DER and RES indexes and the impact of uncertainty levels are demonstrated. Also, the advantages of chanceconstrained formulation as the means of risk-hedging are addressed. Finally, the impact of rival μ VPPs on the bidding behaviors and the impact of carbon taxes on the profit are analyzed.

Original language	English
Pages (from-to)	94-105
Journal	IEEE Power and Energy Technology Systems Journal
Volume	4
Issue number	4
Early online date	5 Oct 2017
DOIs	https://doi.org/10.1109/JPETS.2017.2749256
Publication status	Published - 1 Dec 2017

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title = "Contributing to DSO{\textquoteright}s Energy-Reserve Pool: A Chance-Constrained Two-Stage μ VPP Bidding Strategy",

abstract = "This paper presents the strategic proposition for a micro virtual power plant (μ VPP) to participate in the distribution level energy-reserve pool managed by a distribution system operator. A chanceconstrained two-stage stochastic formulation is proposed to derive the bidding strategy for μ VPP maximizing its daily profit. The stochastic nature of renewable generation and load profile of the μ VPP is captured by the Monte Carlo method. The security of supply is guaranteed by controlling the loss of load probability, which is modeled as chance constraint. The numerical tests are performed on μ VPPs with different penetration levels of distributed energy resource (DER) and renewable energy source (RES), where the impact of the DER and RES indexes and the impact of uncertainty levels are demonstrated. Also, the advantages of chanceconstrained formulation as the means of risk-hedging are addressed. Finally, the impact of rival μ VPPs on the bidding behaviors and the impact of carbon taxes on the profit are analyzed.",

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AU - Fu, Hao

AU - Wu, Zhi

AU - Zhang, Xiao-ping

AU - Brandt, Joachim

PY - 2017/12/1

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Contributing to DSO’s Energy-Reserve Pool: A Chance-Constrained Two-Stage μ VPP Bidding Strategy

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