Nowadays a Virtual Power Plant (VPP) represents an aggregation of distributed energy resource such as Distributed Generation (DG), Combined Heat and Power generation (CHP), Energy Storage Systems (ESS) and load in order to operate as a single power plant by using Information and Communication Technologies, ICT. The VPP has been developed and verified based on a single virtual plant platform which is connected with a number of various distributed energy resources. As the VPP's distributed energy resources increase, so does the number of data from distributed energy. Moreover, it is obviously inefficient in the aspects of technique and cost that a virtual plant platform operates in a centralized manner over widespread region. In this paper the concept of the large-scale VPP which can reduce a error probability of system's load and increase the robustness of data exchange among distributed energy resources will be proposed. In addition, it can directly control and supervise energy resource by making small size's virtual platform which can make a optimal resource scheduling to consider of variable and sensitive load in the large-scale VPP. It makes certain the result is verified by simulation.
In this paper, we developed a mixed-integer linear programming model for transportation planning of athletes in sports events. The transportation planning of athletes involves finding the lowest-cost and fastest-time plan for distributing athletes from multiple accommodation to stadium. The decision variables associate with the number of driving events, and the total transportation cost is the objective function that needs to be minimized. The proposed method uses mixed integer linear programming to solve transportation problem, thus the global optimality is guaranteed. In order to verify the effectiveness of proposed method, we performed simulation and built the sports event management service platform (SEMSP) for transportation planning.
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