The simulation precision of the classic load model (CLM) is affected by the increasing proportion of installed energy storage capacity in the grid. This paper studies the all-vanadium redox flow battery (VRB) and proposes an equivalent model based on the measurement-based load modeling method, which can simulate the maximum output of the VRB energy storage system and fit the external characteristic of the system precisely in the occurrence of large disturbance and continuous small disturbance. The equivalent model is connected to CLM to form a generalized synthesis load model (GSLM), which considers the parameters of distribution network and reactive power compensation. Compared with CLM, GSLM has better structures and can describe the load characteristics of distribution network with energy storage system more precisely. Simulation results validate the effectiveness and good parameter stability of GSLM, and show that the higher the proportion of energy storage in the grid is the better description ability GSLM has.

Based on the research on the basis of analyzing the mechanism of polynomial fitting model, The polynomial fitting model or method was established based on intelligent optimization algorithm. The proposed method was applied to electric power system load forecasting, by a practical example’s calculation and analysis, this proposed intelligent optimization algorithm or method was verified to be feasible in the power system load forecasting, the results also showed that the method was compared with the traditional algorithm has superiority and has a broad application prospect in the field of polynomial fitting.

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As an important part of the underwater robots, bionic robot fish is one of the international forefront in the related research fields. This thesis first designs specific ways of robot fish path planning based on genetic algorithm, then builds the environment model and selects the appropriate fitness function. Finally, it uses the MATLAB to simulate the robotic fish barrier shield path, then analyses and summarizes the experimental results.

Multi-objective optimization model on sitting and sizing of Distributed Generation (DG) was proposed in this paper, and it was based on the comprehensive consideration of total system network loss and total deviation of node voltage, aiming at the optimization of DG’s access, the simulation tests were carried out on the 13 bus test system using Particle Swarm Optimization (PSO) algorithm that belonged to swarm intelligence algorithm, receiving the improved network loss and node voltage as the evaluation index, the mutation operator was introduced into the basic PSO algorithm, which improved the possibility to find a more optimal value ,the results showed that IPSO algorithm had strong global searching ability and rapid convergence speed for optimal allocation of Distributed Generation in the distribution network, and it created a new idea for further Distributed Generation allocation.