Abstract:The forecasting of the load profile of the domestic sector is an area of increased concern for the power grid as it appears in many applications, such as grid operations, demand side management, energy trading, and so forth. Accordingly, a bottom-up forecasting framework is presented in this paper based upon bottom level data about the electricity consumption of household appliances. In the proposed framework, a load profile for group households is obtained with a similar day extraction module, household behavior analysis module, and household behavior prediction module. Concretely, similar day extraction module is the core of the prediction and is employed to extract similar historical days by considering the external environmental and household internal influence factors on energy consumption. The household behavior analysis module is used to analyse and formulate the consumption behavior probability of appliances according to the statistical characteristics of appliances' switch state in historical similar days. Based on the former two modules, household behavior prediction module is responsible for the load profile of group households. Finally, a case study based on the measured data in a practical residential community is performed to illustrate the feasibility and effectiveness of the proposed bottom-up household load forecasting approach.

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The increase of water shipping density, coupled with the increasing complexity of the waterway, the ship's intelligent collision avoidance system plays a pivotal role in the transportation safety of shipping. Therefore, it has gradually become the focus of water traffic safety research. In recent years, China is still facing a period of great development in navigation technology, safety, green, digital, intelligent will become the development trend. Although the waterway environment has been improving, the increase of shipping vessels has led to frequent accidents in the waterway, and the traditional management methods and means lack real-time monitoring and scheduling of vessels, and the management lacks intelligence and information technology. In this paper, we solve the ship path problem from the point of path planning of intelligent ships. RRT* algorithm is a common method for path planning, but the traditional RRT* algorithm has problems in ship path planning, slow convergence speed, many path turns and large curvature fluctuations. For these problems, an improved fast extended random tree algorithm (Bi-RRT) is proposed. The improved RRT* algorithm is simulated and verified by MATLAB simulation platform. The simulation results show that the research algorithm can shorten the planning time, reduce the number of iterations, and has better feasibility and effectiveness.

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The Unmanned Aerial System (UAS) is more and more widely used in modern warfare, and its problem of support mode is becoming more and more prominent. The support mode of UAS refers to the standard mode to ensure the operation and maintenance of UAS which mainly composed of maintenance level, organization structure and contractor logistical support system. In most cases the support mode of UAS draws lesson from manned vehicles’. For the research and application of support model of UAS is relatively lagging, for example, the division of maintenance level is not clear; the allocation of support resources is redundant; military force lacks maintenance support capability; logistical support professional setting is not reasonable; the contractor logistics support system is not normative. So, there is no a set of effective, reasonable and normative support mode to support the operation and maintenance of UAS, resulting in the operational readiness of UAS is not high and maintenance process wastes a lot of manpower and material and money, which greatly restricts the operation and development of UAS. Combined with the UAS support requirements and features under the military trade, this paper analyses the status of the redundant and inefficient support mode. Aiming at these problem, a new support model of UAS will be researched from three aspects including the allocation of maintenance level, the adjustment of military maintenance organization structure, and the establishment of contractor logistical support system. By applying the new support mode to user, the operation and support of UAS will be more effective and reasonable which will greatly promote the development of UAS.