新能源系统模型及应用研究

发布时间：2018-10-29 17:35

【摘要】：随着全球能源危机的进一步加深,新能源领域研究的重要性愈加凸显。将可再生能源作为发电源的微电网作为传统集中式大电网替代型技术研究发展潜力巨大。微电网系统规模小,电网容量有限,而负荷序列明显波动,具有高度的非平滑特性和非线性特性。同时风力、光伏发电受自然界客观条件制约,其发电功率及供电质量也受用户负荷影响。因此如何提高微电网短时负荷预测精确度、提高供电质量已经成为当前研究热点。本文基于风力发电、光伏发电及微电网系统结构设计做了深入研究,得出一些有意义的结论,这些研究成果为微电网技术研究提供了新思维和新路径。论文综述微电网短时负荷预测的背景、意义和国内外研究发展历程。设计太阳能,风能互补的微电网系统结构。首先介绍了太阳能、风能电源的基本工作原理；而后依据其明显的互补优势设计了太阳能、风能和储能一体的微电网的主接线结构图；剖析了主要环节的工作原理,给出了有特色的最大效率转换太阳能装置。其次,介绍了微电网电源数学模型,主要有光伏电池输出特性和并网系统信号模型,蓄电池充放电模型,风力发电机模型。然后研究复杂系统的多模型切换预测控制在线性时变和非线性时变下的系统结构和切换控制策略。再次,本文提出了一种用量子粒子群(QPSO)优化自适应神经模糊推理系统(ANFIS)的预测算法,通过归一化预处理负荷值的预测模型。在理论分析论证的基础上,通过仿真,并结合某海岛上的微电网实际负荷数据做模拟仿真论证,结果证明该方法的有效,为提高微电网系统的供电品质及减低运行成本提供了新思路。最后,探讨了微电网电能质量问题的影响因素,从中选择组合型无功补偿装置,建立分布式电源接入配电网后的无功优化模型,提出了一种改进量子粒子群算法来进行无功优化。最后进行仿真验证了该模型和算法的有效性,说明接入分布式能源后,通过合理的无功优化能够降低网损,提高电能质量。
[Abstract]:With the deepening of the global energy crisis, the importance of new energy research is becoming more and more prominent. There is great potential for the research and development of microgrid with renewable energy as power source as the substitute technology of traditional centralized power grid. The microgrid system is small in scale and limited in capacity, but the load sequence fluctuates obviously, and it has a high degree of nonsmooth and nonlinear characteristics. At the same time, wind and photovoltaic power generation is restricted by the objective conditions of nature, and its power generation and power supply quality are also affected by user load. Therefore, how to improve the accuracy of short-time load forecasting and improve the quality of power supply has become a hot topic. In this paper, based on wind power generation, photovoltaic generation and microgrid system structure design, some meaningful conclusions are drawn. These research results provide a new thinking and new path for the research of microgrid technology. This paper summarizes the background, significance and development of short-time load forecasting for micro-grid. The design of solar and wind energy complementary micro-grid system structure. Firstly, the basic working principle of solar and wind power supply is introduced, and then, according to its obvious complementary advantages, the main wiring structure of micro-grid with solar, wind and energy storage is designed. The working principle of the main link is analyzed, and the characteristic maximum efficiency conversion solar energy device is given. Secondly, the mathematical model of microgrid power supply is introduced, including photovoltaic cell output characteristics and grid-connected system signal model, battery charge and discharge model, wind turbine model. Then, the system structure and switching control strategy of multi-model switching predictive control for complex systems under linear and nonlinear time-varying conditions are studied. Thirdly, a prediction algorithm based on quantum particle swarm optimization (QPSO) for adaptive neural fuzzy inference system (ANFIS) is proposed. On the basis of theoretical analysis and demonstration, the simulation results show that the method is effective by simulation and combining with the actual load data of microgrid on a certain island. It provides a new way to improve the power supply quality and reduce the operation cost of microgrid system. Finally, the influence factors of power quality in microgrid are discussed, and the combined reactive power compensation device is selected to establish the reactive power optimization model after the distributed generation is connected to the distribution network. An improved Quantum Particle Swarm Optimization (QPSO) algorithm is proposed for reactive power optimization. Finally, the validity of the model and the algorithm is verified by simulation, which shows that the network loss can be reduced and the power quality can be improved by rational reactive power optimization after access to distributed energy.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM61

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