4.4 Article

Strategic CBDR bidding considering FTR and wind power

Journal

IET GENERATION TRANSMISSION & DISTRIBUTION
Volume 10, Issue 10, Pages 2464-2474

Publisher

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-gtd.2015.1305

Keywords

wind power plants; power markets; power transmission economics; costing; demand side management; integer programming; linear programming; power generation economics; power generation dispatch; strategic CBDR bidding; wind power; independent system operators; ISO; financial transmission right; financial instrument; electricity market participant; transmission congestion cost; demand response development; DR development; load serving entities; LSE opportunities; coupon-based demand response program; CBDR program; strategic bidders; whole-sale market; congestion compensation; comprehensive strategic CBDR model; LSE bidder FTR holding; bi-level optimisation problem; LSE net revenue maximisation; ISO economic dispatch; wind power uncertainty; mathematic program; equilibrium constraint technique; mixed-integer linear programming; PJM 5-bus system; IEEE 39-bus system

Funding

  1. CURENT, a US NSF/DOE Engineering Research Center under NSF Award [EEC-1041877]

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The independent system operators (ISOs) usually offer financial transmission right (FTR) as a financial instrument for electricity market participants to hedge against the transmission congestion cost. Meanwhile, the development of demand response (DR) provides load serving entities (LSEs) opportunities to perform coupon based demand response (CBDR) programs, and thus LSEs can behave as strategic bidders in the whole-sale market by adjusting its demand level. In the existing approaches for modelling CBDR, the potential impact of FTR which leads LSEs to obtain the congestion compensation under a high load level is overlooked. Therefore, this study proposes a comprehensive strategic CBDR model in which the LSE's profit is maximised by providing CBDR to customers and the congestion compensation from the LSE bidder's FTR holding is also considered. The proposed model is formulated as a bi-level optimisation problem with the LSE's net revenue maximisation as the upper level and the ISO's economic dispatch considering wind power uncertainty as the lower level problem. The bi-level model is addressed with mathematic program with equilibrium constraints technique and mixed-integer linear programming, which can be solved using available optimisation software tools. In addition, the case studies of an illustrative two bus system, the PJM 5-bus system, and IEEE 39-bus system verify the proposed method.

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