Natural gas hydrates (NGHs), which extensively exist in sea-floor and permafrost regions, are considered as an alternative energy in the future for the fossil fuels approaching depletion with the gradually increasing energy consumption. Because of the particularity of NGH stabilizing only in the conditions of the high pressure and the low temperature, the exploitation of NGH is distinguished from those of petroleum and natural gas. Researchers over the world are devoting themselves to developing the technologies of NGH exploitation. However, till now, few NGH exploitation technology is identified and employed to exploit commercially NGH. Although there do be two cases of short-term NGH exploitation in Mackenzie Delta (CAN), Alaska North Slope (USA) and Nankai Trough (JAP) in the past 10 years. It is mainly because some characteristics of the flow (gas, water, gas-hydrate slurry, quicksand, etc.), the issues of heat and mass transfer, the risk assessment and the economic evaluation are still not comprehensively recognized. Presently, the researches of NGH exploitation are mainly carried out from three aspects, numerical simulation and analysis, experimental simulation and field trial exploitation for the different technologies. In this paper, we comprehensively review the relevant studies of NGHs and propose our comments. We not only represent the achievements for the NGH exploitation researches, but also discuss the limitations and challenges, raise some questions and put forward some suggestions from our points of view.

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Because of the non-uniformity of the electric power CPS network and the dynamic nature of the risk propagation process, it is difficult to quantify the critical point of a cyber risk explosion. From the perspective of the dependency network, this paper proposes a method for quantitative evaluation of the risk propagation threshold of power CPS networks based on the percolation theory. First, the power CPS network is abstracted as a dual-layered network-directed unweighted graph according to topology correlation and coupling logic, and the asymmetrical balls-into-bins allocation method is used to establish a "one-to-many" and "partially coupled" non-uniform power CPS characterization model. Then, considering the directionality between the cyber layer and the physical layer link, the probability of percolation flow is introduced to establish the propagation dynamic equations for the internal coupling relationship of each layer. Finally, the risk propagation threshold is numerically quantified by defining the survival function of power CPS network nodes, and the validity of the proposed method is verified by the IEEE 30-bus system and 150-node Barabsi-Albert model. 2169-3536 (c) INDEX TERMS Electric power CPS, interdependent network, Percolation probability, Propagation dynamics

The scale of the electric cyber physical system (ECPS) is continuously extending, and the existing cascade failure models ignore both the information flow and power flow transferring characteristics and also lack effective survivability analysis. In this paper, the quantitative evaluation method for cascading failure of ECPS survivability considering optimal load allocation is proposed. Firstly, according to the system topological structure and correlation, the degree-betweenness weighted correlation matrix of ECPS is established by defining the degree function as well as the electric betweenness, and the formal representation of coupled ECPS network model is realized. Secondly, based on the structural connectivity change and risk propagation range of ECPS cascade failure, the survivability evaluation model is designed by taking into account the constraints such as node load capacity limitation, information flow optimal allocation strategy, power flow optimization equation, and system safety operation. Finally, the firefly algorithm with chaotic Lévy flight is proposed to solve the evaluation model efficiently. The case study vividly shows that the evaluation method can effectively quantify the survivability of ECPS and thus enhance the evaluation efficiency of large-scale coupled systems.