access icon free Coordination of wind generation and demand response to minimise operation cost in day-ahead electricity markets using bi-level optimisation framework

© The Institution of Engineering and Technology
Received 31/01/2018, Accepted 11/06/2018, Revised 30/04/2018, Published 20/06/2018

Demand response (DR) can play an important role when dealing with the increasing variability of renewables in power system. This study proposes a bi-level market model for wind-integrated electricity market, where the DR requirement is paired with the wind profile to deal with wind variability. At the upper level, an electricity market operator aims to minimise the day-ahead operation cost considering plausible wind generation scenarios. At the lower level, the DR exchange operator aims to maximise social welfare by trading aggregated DR among several aggregators. The solution at this level determines the optimal DR amount and price setting for each aggregator. The DR from the flexible loads is modelled from the end-users' perspective considering their willingness parameter. The market model is formulated as a bi-level optimisation problem using Lagrangian relaxation with Karush–Kuhn–Tucker optimality conditions. The effectiveness of the proposed scheme is demonstrated on sample 4-bus and IEEE 24-bus systems. Different scenarios such as high, medium and low levels of wind and DR are investigated. The high-wind low-DR scenario leads to minimum operation cost and is least inconvenient for end users as it sets the DR at a minimum level while keeping the higher levels of wind generation.

Inspec keywords: power generation economics; power markets; mathematical programming; wind power plants; demand side management; minimisation; power generation scheduling

Other keywords: electricity market operator; Lagrangian relaxation; demand response; wind-integrated electricity market; DR-capable loads; associated Karush-Kuhn-Tucker optimality conditions; monetary benefit maximisation; day-ahead electricity markets; bilevel optimisation framework; mathematical programming problem; DR exchange operator; plausible wind generation scenarios; DR requirement; social welfare maximisation; complementarity constraints; wind profile; day-ahead operation cost minimisation; wind variability; bilevel market model; power system; wind generation

Subjects: Power system management, operation and economics; Optimisation techniques; Wind power plants

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