Yilin Wen (Student Member, IEEE) received the B.S. degree in electrical engineering from Tsinghua University, Beijing, China, in 2020, where he is currently pursuing the Ph.D. degree in electrical engineering. His current research interests include demand response, integrated transmission and distribution systems, and control and optimization in power systems.

This letter proposes a novel inner approximation method for the aggregated temporally-coupled power flexibility of distributed energy resources (DERs). Previous inner approximation methods were proposed without knowing the explicit formulation of the exact flexibility aggregation model of DERs. Recently, we have derived that explicit formulation [1], so its properties are exploited to develop an inner approximation in this letter. The proposed method significantly improves the accuracy and computation speed. Numerical tests verify the effectiveness of the proposed method.

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Fuel cell electric vehicles (FCEVs) are rapidly growing owing to the increased public awareness of energy and environmental issues. Infrastructure for hydrogen production, transportation, and allocation is essential for FCEV promotion. For consumers, availability of few hydrogen refuelling stations is the primary concern. Currently, public charging infrastructure for battery electric vehicles, for example, fast charging station, has a more widespread coverage compared to infrastructure for hydrogen refuelling. With an electrolyser, the existing power grid can be used as an alternative to hydrogen supply and transportation infrastructure, which is still being developed. The authors propose a new conceptual combo station acting as both a hydrogen refuelling station and a fast charging station. This station can satisfy the requirement of FCEVs and battery electric vehicles, and even operate under a blackout situation. To quantify the value of coordinated operation, an optimal operation formulation of a combo station is developed. It is found that such a combo station is capable of saving land rents, reducing power network reinforcement cost, and boosting energy self‐balance capability under blackout condition.

In the first part of the two-part series, the model to describe the exact aggregated feasible region (AFR) of multiple types of demand-side resources are derived. Based on a discretetime unified individual model of heterogeneous resources, the calculation of AFR is, in fact, a feasible region projection problem. Therefore, the Fourier-Motzkin Elimination (FME) method is used for derivation. By analyzing the redundancy of all possible constraints in the FME process, the mathematical expression and calculation method for the exact AFR is proposed. The number of constraints is linear with the number of resources, and is exponential with the number of time intervals, respectively. The computational complexity has been dramatically simplified compared with the original FME. However, the number of constraints in the model is still exponential and cannot be simplified any more. Hence, In Part II of this paper, several approximation methods are proposed and analyzed in detail.