Pendulum Wave Power System's Pivotal Problems Research On The Simulation And Optimization

Since the 21st century, the world's energy crisis and the consequent environmental crisis are getting worse. In China, solar and wind power have made considerable progress, but in the area of ocean energy utilization especially wave energy area, still has obvious gap with the world. China has abundant wave energy resources. In order to take advantage of the ocean, to take the inexhaustible green renewable energy, the wave power generation system researching has important practical significance and strategic significance.Considering the factors of power generation ratio and engineering properties, pitch-type wave power device is the most optimum. However, in domestic, investigation on pitch-type wave device is still empty, especially of the system performance optimization, it is never started. This thesis proposes, a ideal pitch-style wave energy absorbing device must be high efficiency, high reliability, low construction difficulty, easy to maintain etc. Investigating wave height, wave period, water depth, swing body width, displacement, center of gravity height, load size and other environmental parameters and mechanical parameters on system performance, using fluid mechanics, wave mechanics, power electronics, motor learning, modern control theory and other knowledge and methods, establishing a rational wave power comprehensive simulation and analysis model, and a correct simulation and model experiment analysis systems, especially with excellent power control algorithm to improve system performance, reducing the unit cost of electricity, seeking practical solutions to the wave power is necessary and meaningful。Among them, to optimize performance, with emphasis on the following key research issues:1 Build a pitch-type wave power optimization mathematical analysis model system, it implements the system analysis based on MATLAB / SIMULINK platform wave power, provides a mathematical basis by solving the second order differential equations with variable coefficients, estimated the entire system, reduces the workload of system evaluation. And load parameters modify, control algorithm modify can be achieved on the modeling system. Different from the generator, the system is divided into two parts, one based on permanent magnet synchronous generator (PSSG), the other part is based on the switched reluctance generator (SRG), Both them are currently the mainstream application direction. Mathematical analysis model of switched reluctance generator is highly nonlinear, accurate modeling is the key of analysis. The authors conducted depth research in this area, the model was modeling with BP neural network algorithm firstly, and the effects of various iteration methods were compared then, from them, a LM optimal solution was found. In addition, Comprehensive Improved PSO and BP neural network algorithm was then combined, further optimized the nonlinear parameter identification results of SRG.2 Propose a novel and complete power control strategy to optimize the system status. To achieve power control, design a successful load strength control solution by building a BOOST circuit and then controlling the PWM signal duty cycle. According to the different incident wave energy, when the wave height energy is lower than the rated value, In order to maximum output power, mountain climbing or adaptive fuzzy PID tracking algorithm are implemented; when the incident wave power is over rated power, in order to improve the system stability, a fuzzy sliding mode control strategies is then used. The control strategies were vivificated by system simulation or experimental model test.3 At South China University of Technology, based on the similarity principle of Flores, a set of pitch-type wave power system model test environment was designed and established, to further reliable basis of experimental data. The equipment can experiment with different wave height, wave period, water depth, swing the body displacement, and the response status under different metacentric height. Using of industrial computer and high speed data acquisition card real-time acquisition swing angle, swing speed, output torque, the absorption of mechanical power and output electrical power etc. the maximum power and constant power control algorithm was verified by model experiments.4 Wave height and power prediction was invested to further enhance the energy output performance of wave power system. In the natural environment, waves has chaos characteristic, combining with the phase space reconstruction and chaotic neural network method to predict wave height is successful, it provides a relatively reliable control timing for the control system.