Abstract-As Cloud Computing technology becomes more mature, many organizations and individuals are interested in storing more sensitive data e.g. personal health records, customers related information in the cloud. Such sensitive data needs to be encrypted before it is outsourced to the cloud. Typically, the cloud servers also need to support a keyword search feature for these encrypted files. Traditional searchable encryption schemes typically only support exact keyword matches. However, users sometimes have typos or use slightly different formats e.g. "data-mining" versus "data mining". Thus, fuzzy keyword search is a useful feature to have. Recently, some researchers propose using wildcard based approach to provide fuzzy keyword search. They also propose a solution for multikeyword search. Their approaches have some limitations, namely (a) their fuzzy keyword search solution consumes large storage size since it inserts every fuzzy keyword as a leaf node in the index tree, (b) their fuzzy single-keyword search solution does not support multi-keyword search, (c) the existing multi-keyword search scheme does not provide efficient incremental updates. In this paper, we propose a privacy-aware bedtree based approach to support fuzzy multi-keyword feature. Incremental updates can be easily done using our solution. We have implemented our solution. Our evaluation results show that our approach is more cost-effective in terms of storage size and construction time. Our search time is usually better than the wildcard approach for multi-keyword queries where many encrypted files are returned using single-word queries for approaches that do not support multi-keyword queries.

Owing to random load changes and transmission time delays in interconnected power systems with renewable energy, the load frequency control scheme has become one of the main methods to keep stability and security of power systems. To relieve communication burden and increase network utilisation, an adaptive event-triggered scheme is explored. Then, a new fractional-order global sliding mode control scheme comprising the fractional-order term in the sliding surface is adopted to improve robustness of load frequency control. The fractional-order term generates a new degree of freedom and more adjustable parameters to improve control performance. Furthermore, the Markov theory is applied in the modelling process to better describe the uncertainty of parameters and external disturbances. The stability and stabilisation criteria for multi-area power systems load frequency control are put forward by employing the improved Lyapunov function and integral inequalities with auxiliary functions. Finally, two simulation examples containing a two-area power system and modified IEEE 39-bus New England test power system with three wind farms are presented to investigate the effectiveness of the proposed method. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

The concept of virtual synchronous machine (VSM) was proposed to deal with the shortcomings of low inertia and damping of traditional control strategies for power electronic converters. But what if all distributed energy resources and controllable loads in a microgrid adopt the VSM control strategy, and will it present better performance than conventional droop control-based microgrid (DMG)? In this paper, the VSM-based microgrid (VSMG) is analyzed. The small-signal modeling of the VSMG is studied at first. Then static stability and dynamic characteristics of the VSMG are analyzed and compared with the DMG in both frequency-domain and time-domain. With the growing scale of microgrids, their modeling and simulation are becoming significant computational burdens. Inspired by the participation factor analysis of the VSMG and the concept of coherency in power systems, the VSMG small-signal model is equivalent to a modified third-order synchronous generator (SG) model in this paper. The equivalencing involves gray-box system identification and is realized by estimating equivalent electrical parameters alternately and iteratively. The equivalent SG (EqSG) model is compared with three representative model order reduction methods to verify its effectiveness. Simulation results confirm the accuracy of the EqSG model substituting detailed VSMG model in time-domain simulations. INDEX TERMS Microgrid modeling, model order reduction, virtual synchronous machine, small-signal modeling.

In this paper, a distributed economic dispatch scheme considering power limit is proposed to minimize the total active power generation cost in a droop-based autonomous direct current (DC) microgrid. The economical dispatch of the microgrid is realized through a fully distributed hierarchical control. In the tertiary level, an incremental cost consensus-based algorithm embedded into the economical regulator is utilized to search for the optimal solution. In the secondary level, the voltage regulator estimating the average voltage of the DC microgrid is used to generate the voltage correction item and eliminate the power and voltage oscillation caused by the deviation between different items. Then, the droop controller in the primary level receives the reference values from the upper level to ensure the output power converging to the optimum while recovering the average voltage of the system. Further, the dynamic model is established and the optimal communication network topology minimizing the impact of time delay on the voltage estimation is given in this paper. Finally, a low-voltage DC microgrid simulation platform containing different types of distributed generators is built, and the effectiveness of the proposed scheme and the performance of the optimal topology are verified.

Articulated tracked vehicles are used as special off-road transportation vehicles, and their mobility is gaining more attention now than before. As an important evaluation indicator of the mobility of articulated tracked vehicles, steering performance receives wide attention in particular. Most of the present studies focus on the planar steering performance; few studies employing current models concentrate on the slope steering performance of articulated tracked vehicles. To address this research gap, this study proposes a dynamic modeling method for analyzing the slope steering performance of articulated tracked vehicles. A kinematic model of a vehicle is initially constructed to analyze its kinematic characteristics during slope steering; these characteristics include velocity and acceleration. A dynamic model of a vehicle is then developed to analyze its mechanical characteristics during slope steering; these characteristics include vertical loads, driving forces, and driving moments of tracks. The created dynamic model is then applied to analyze the slope steering performance of a specific articulated tracked vehicle. A mechanical-control united simulation model and an actual test of an articulated tracked vehicle are suggested to verify the established steering model. Comparison results show the effectiveness of the proposed dynamic steering model.