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This paper proposes a computationally efficient electricity market simulation tool (MST) suitable for future grid scenario analysis. The market model is based on a unit commitment (UC) problem and takes into account the uptake of emerging technologies, like demand response, battery storage, concentrated solar thermal generation, and HVDC transmission. To allow for a subsequent stability assessment, the MST requires an explicit representation of the number of online generation units, which affects power system inertia and reactive power support capability. These requirements render a full-fledged UC model computationally intractable, so we propose unit clustering, a rolling horizon approach, and constraint clipping to increase the computational efficiency. To showcase the capability of the proposed tool, we use a simplified model of the Australian National Electricity Market with different penetrations of renewable generation. The results are verified by a comparison to a more expressive and computationally intensive binary UC, which confirm the validity of the approach for long term future grid studies.

Computationally Efficient Market Simulation Tool for Future Grid Scenario Analysis