Electric-hydrogen energy systems, which enable the interconnection of electricity and hydrogen, are an important measure for the consumption of intermittent renewable energy generation and the achievement of dual-carbon goals. Meanwhile, long-period hydrogen storage systems have attracted widespread attention due to their ability to compensate for medium- and long-term fluctuations in renewable energy. However, risk defense planning models involving electric-hydrogen energy systems are usually limited by model complexity as they must cover the complete charging and discharging cycles of long-cycle hydrogen storage. Therefore, this paper proposes a risk defense planning method for electric-hydrogen energy systems based on adaptive time-series aggregation, in which, firstly, an adaptive time-series aggregation algorithm is designed based on the predicted values of renewable energy sources and load demand to reduce the variable dimensions of the operational simulation; secondly, conditional value-at-risk theory is introduced to model renewable energy sources and electric load fluctuations using multivariate Gaussian distributions, which is used to quantify the potential operational risks of the system; Finally, taking into account the system investment and operation cost, an optimal planning model for electric-hydrogen energy system based on adaptive time-series aggregation is constructed with the optimization objective of minimizing the total annualized cost. Example results show that the proposed method can simultaneously consider the adjustment ability of long/short cycle hydrogen storage and the potential operating risks, improve the risk defense ability of the system, and effectively balance the system"s potential operating risks and investment costs.