Contributing to DSO’s Energy-Reserve Pool: A Chance-Constrained Two-Stage $\mu $ VPP Bidding Strategy
Author(s) -
Hao Fu,
Zhi Wu,
Xiao-Ping Zhang,
Joachim Brandt
Publication year - 2017
Publication title -
ieee power and energy technology systems journal
Language(s) - English
Resource type - Journals
ISSN - 2332-7707
DOI - 10.1109/jpets.2017.2749256
Subject(s) - power, energy and industry applications , geoscience
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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