AGC signal feature-driven bidding and control coordinated optimization for user-side energy storage in frequency regulation market

Leveraging User-Side Energy Storage (USES) for frequency regulation (FR) services is a vital way to unlock its potential value in providing grid-level flexibility. However, existing studies on USES in providing FR services fail to effectively quantify its ability to consistently track stochastic Automatic Generation Control (AGC) signals, resulting in disproportionately low FR benefits. To this end, a novel coordinated optimization method for day-ahead bidding and intra-day control of USES is proposed, which exploits the key features of AGC signals to optimize the deeply coupled FR bidding and control process in each period. Firstly, a coordinated optimization framework integrating AGC signal features is developed for FR decision-making in USES, where historical data-based and interval-predictive AGC features are employed to formulate the optimal bidding and rolling control strategy. Secondly, a characterization and modeling method for key statistical features of AGC signals is presented, which helps to measure the FR tracking responsiveness during different bidding periods on the operating day. Finally, a precautionary control mechanism with threshold intervals is embedded in the intra-day rolling control process, which ensures the FR responsiveness of USES in future periods by sacrificing the current response accuracy. Case studies validate the effectiveness of the proposed method in improving the overall frequency regulation performance while enhancing the trading revenue in the FR market.