Chance-Constrained and CVaR Optimal Dispatch for Co-Phase Traction Power Supply System with PV and HESS

Abstract

Co-phase traction power supply system (CTPSS) integrated with photovoltaic (PV) and hybrid energy storage system (HESS) can enhance power supply capacity while facilitating the on-site consumption of renewable energy. This integration provides a pathway toward green development and the achievement of the “carbon peaking and carbon neutrality” goal. However, the stochastic nature of PV poses challenges to safe and economical operation of the system. Existing energy management methods remain limited in simultaneously balancing operational economy and extreme risks caused by PV uncertainty, making it difficult to achieve an effective trade-off between operating cost and constraint violation risk. To address this issue, a risk-sensitive optimal scheduling framework integrating probabilistic PV forecasting, correlated scenario generation, and risk-aware optimization is developed. First, a PV probabilistic prediction model based on parallel TCN-BiLSTM-Attention is proposed, which extracts multiscale local features and long-range temporal features from PV for accurate uncertainty quantification. Second, a t-Copula PV scenario generation method driven by weather classification and temporal correlation is proposed. On this basis, a day-ahead optimal scheduling strategy integrating chance constraints programming (CCP) and conditional value at risk (CVaR) is established to simultaneously control constraint violation risk and extreme economic risk. The proposed prediction model can accurately quantify uncertainty, achieving an R2 value of 0.9979. When the allowable power supply loss probability is 0.5%, the proposed scheme’s operating cost is reduced by 1.36% compared with the baseline scheme. The results demonstrate that the proposed framework can effectively coordinate operating economy and extreme-risk control, thereby improving the risk-sensitive operational performance of CTPSS with PV and HESS. The proposed strategy balances economy and extreme risk, providing a reference for safe, low-carbon and economical operation of CTPSS with PV and HESS.