Bidding optimization for cascade hydropower plants in multi-regional electricity markets

Abstract

Efficient cross-regional allocation of hydropower is critical for the low-carbon energy transition. However, co-optimizing bidding curves for different regional markets presents significant challenges for hydropower producers, due to the complex interplay of bidding strategies, multiple factors that contribute to uncertainty, and the diversity of regional markets. This paper proposes a novel bi-level model to optimize the bidding curves of cascade hydropower plants for multi-regional electricity markets with detailed modeling of their spatio-temporal correlations. The proposed model can adapt to regional markets with varying information transparency by employing a flexible approach to market modeling. A modified interval programming method is proposed to address the multiple uncertainties in the bidding, which mitigates the excessive conservatism inherent in traditional interval programming while preserving its robustness to the distribution estimation error. To efficiently solve the mathematical model, the complex nonlinear dependencies among interval variables are first eliminated through Taylor expansion and a modified multi-dimensional interpolation method. Subsequently, the order relation of interval and Karush-Kuhn-Tucker conditions are utilized to reformulate the proposed model into a tractable mixed-integer linear programming model. Numerical tests conducted on a real cascade hydropower system located in China validate the effectiveness and advantages of the proposed method.