Previous studies focused on meeting the demand of traditional single-energy loads by dispatching resources within a regionally integrated energy system (RIES), while overlooking the growing dominance of multi-energy loads. Meanwhile, uncertainty and communication link failures caused by contingencies gradually gain attention. Therefore, we propose a decentralized robust synthetic restoration strategy (SRS) that combines the integrated demand response (IDR) program and repair order to enhance the resilience of RIES. Considering the uncertainty of the repair time of the faulty components, we formulate the problem as a two-stage robust optimization model to minimize the restoration cost and interruption duration. We propose a decentralized approach to decouple the model based on different stakeholders to alleviate the communication tension. Meanwhile, we develop a specific solution procedure that considers the interference of binary variables and potential communication link failures in the decentralized solution. The results show that the proposed SRS improves the restoration cost anticipatively and reduces the interruption duration. The robust model can obtain restoration results for different degrees of conservatism. The proposed decentralized approach is reliable and scalable.

Large-scale access of distributed photovoltaic (PV) in distribution networks (DNs), if not properly evaluated, brings several operational problems. Uncertainties arising from both PV outputs and load demand significantly impact evaluation results. To address this issue, this paper proposes a possibilistic approach to evaluate PV hosting capacity (PVHC). First, possibility distribution is used to model load demand in order to reflect uncertainties associated with human factor, whereas the interval model is applied to deal with uncertainties of PV outputs. Second, a voltage deterioration index is proposed considering overvoltage risk of entire system on time scale. After that, possibilistic PVHC evaluation method based on this index is proposed. A 6-bus system is used to illustrate advantages of the proposed method, followed by a discussion of role of PVHC possibility distribution in actual decision-making of utilities. Moreover, sensitivity of simulation parameters is analyzed to reduce computational burden. Finally, the proposed method is tested on the IEEE 123-bus DN to validate adaptability to a larger system and to analyze impact of PVHC results against different acceptable values set by utilities.