基于膜计算的微电网协调管控与能量优化研究
发布时间：2019-05-08 15:54
【摘要】：微电网在分布式电源的高效应用、灵活运行以及可调度性能等方面表现出极大的潜能和优势,成为目前解决能源危机问题的主要战略之一。微电网的协调管控和能量优化一直是微电网研究的两个热点。微电网协调管控的主要目标是实现系统的稳定运行。在此基础上,可以进一步考虑系统的能量优化,实现微电网的最优运行。但由于微电网结构繁多,控制方式灵活多样,不仅需要考虑系统稳定性、电能质量以及并网时对大电网的冲击影响等,还需考虑经济、环保、应用场所等多种因素,因此还需进一步全面深入地研究微电网的协调管控和能量优化技术。膜计算不仅具有强大的信息处理、推理和建模能力,还具有极大并行性,可克服控制系统结构多样等问题,满足系统多样化的控制需求,适用于求解多种实际问题。因此,本文结合膜计算理论模型与膜优化算法,深入开展了关于微电网协调管控和能量优化两方面的研究工作。在微电网协调管控方面,本文结合细胞型膜系统和模糊理论,提出了语言模糊细胞型模糊P系统(Fuzzy Language Cell-like Fuzzy P System,FLCFPS),给出了其详细定义,进行推理演示,总结其特点并与其他P系统进行比较;随后,使用FLCFPS构建微电网FLCFPS协调管控系统,包括微电网结构选择确认、控制对象选择、输入量的确认、输入量的模糊化、基本控制流程确立以及各种分布式电源的FLCFPS模型搭建,并进行了系统推理测试;最后,通过MATLAB仿真对该微电网FLCFPS协调管控系统的合理性和有效性进行了进一步验证。实验结果表明,微电网FLCFPS协调管控系统能有效管理和控制微网,实现功率分配平衡,满足重要负荷供电可靠性,维持交流馈线频率稳定,提高分布式发电单元利用率。在微电网能量优化方面,本文结合细胞型膜系统框架和第二代非支配遗传算法,提出了非支配遗传膜算法(Non-dominated Sorting Genetic Membrane-inspired Algorithm,NSGMIA),并进行性能测试;然后,搭建考虑微电网运行成本、污染物排放和新能源利用率等因素的微电网多目标能量优化模型;最后,采用NSGMIA算法对微电网多目标能量优化模型进行求解,并用模糊决策选择出综合解,实现微电网两目标能量优化和微电网三目标能量优化并进行详细的实验结果分析。实验结果表w\0,该微电网多目标能量优化模型可以有效地实现成本、排污和新能源利用率的综合控制策略,且利用NSGMIA求解,得到的最优解集具有更好的分布性和多样性,有效地提高了微电网的运行管理水平。
[Abstract]:Microgrid has great potential and advantage in the efficient application of distributed power supply, flexible operation and schedulable performance, and has become one of the main strategies to solve the energy crisis problem at present. The coordination control and energy optimization of microgrid have been two hot spots in the research of microgrid. The main goal of coordinated control and control of microgrid is to realize the stable operation of the system. On this basis, the energy optimization of the system can be further considered, and the optimal operation of the microgrid can be realized. However, due to the variety of microgrid structures and flexible control methods, it is necessary not only to consider the stability of the system, the power quality and the impact of grid connection on the large power grid, but also to consider many factors such as economy, environmental protection, application places, and so on. Therefore, it is necessary to study the coordinated control and energy optimization technology of microgrid in a more comprehensive and in-depth way. Membrane computing not only has the powerful ability of information processing, reasoning and modeling, but also has great parallelism. It can overcome the problems of diverse control system structures, meet the diverse control requirements of the system, and is suitable for solving a variety of practical problems. Therefore, based on the theoretical model of membrane calculation and membrane optimization algorithm, the research work on coordinated control and energy optimization of microgrid is carried out in this paper. In the aspect of coordination control and control of microgrid, this paper proposes a fuzzy cellular fuzzy P system (Fuzzy Language Cell-like Fuzzy P System,FLCFPS) based on cellular membrane system and fuzzy theory, and gives its detailed definition and reasoning demonstration. Summarize its characteristics and compare with other P systems; Then, FLCFPS is used to construct the micro-grid FLCFPS coordination control system, including micro-grid structure selection, control object selection, input validation, input fuzzification, basic control process establishment and FLCFPS model construction of various distributed power sources. The system reasoning test is carried out. Finally, the rationality and effectiveness of the micro-grid FLCFPS coordinated control system are further verified by MATLAB simulation. The experimental results show that the micro-grid FLCFPS coordinated control system can effectively manage and control the micro-grid, realize the balance of power distribution, satisfy the reliability of power supply of important load, maintain the frequency stability of AC feeder, and improve the utilization rate of distributed power generation unit. In the aspect of energy optimization of microgrid, combining the framework of cellular membrane system and the second generation of non-dominated genetic algorithm, this paper proposes the non-dominated genetic membrane algorithm (Non-dominated Sorting Genetic Membrane-inspired Algorithm,NSGMIA), and carries on the performance test. Then, the multi-objective energy optimization model of microgrid considering the operating cost of microgrid, pollutant emission and new energy efficiency is set up. Finally, the NSGMIA algorithm is used to solve the multi-objective energy optimization model of microgrid, and the comprehensive solution is selected by fuzzy decision-making. The two-objective energy optimization and three-objective energy optimization of microgrid are realized and the experimental results are analyzed in detail. The experimental results show that the multi-objective energy optimization model of microgrid can effectively realize the integrated control strategy of cost, pollution discharge and new energy utilization, and the optimal solution set obtained by using NSGMIA has better distribution and diversity. It effectively improves the level of operation and management of microgrid.
【学位授予单位】：西华大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727
本文编号：2472032
[Abstract]:Microgrid has great potential and advantage in the efficient application of distributed power supply, flexible operation and schedulable performance, and has become one of the main strategies to solve the energy crisis problem at present. The coordination control and energy optimization of microgrid have been two hot spots in the research of microgrid. The main goal of coordinated control and control of microgrid is to realize the stable operation of the system. On this basis, the energy optimization of the system can be further considered, and the optimal operation of the microgrid can be realized. However, due to the variety of microgrid structures and flexible control methods, it is necessary not only to consider the stability of the system, the power quality and the impact of grid connection on the large power grid, but also to consider many factors such as economy, environmental protection, application places, and so on. Therefore, it is necessary to study the coordinated control and energy optimization technology of microgrid in a more comprehensive and in-depth way. Membrane computing not only has the powerful ability of information processing, reasoning and modeling, but also has great parallelism. It can overcome the problems of diverse control system structures, meet the diverse control requirements of the system, and is suitable for solving a variety of practical problems. Therefore, based on the theoretical model of membrane calculation and membrane optimization algorithm, the research work on coordinated control and energy optimization of microgrid is carried out in this paper. In the aspect of coordination control and control of microgrid, this paper proposes a fuzzy cellular fuzzy P system (Fuzzy Language Cell-like Fuzzy P System,FLCFPS) based on cellular membrane system and fuzzy theory, and gives its detailed definition and reasoning demonstration. Summarize its characteristics and compare with other P systems; Then, FLCFPS is used to construct the micro-grid FLCFPS coordination control system, including micro-grid structure selection, control object selection, input validation, input fuzzification, basic control process establishment and FLCFPS model construction of various distributed power sources. The system reasoning test is carried out. Finally, the rationality and effectiveness of the micro-grid FLCFPS coordinated control system are further verified by MATLAB simulation. The experimental results show that the micro-grid FLCFPS coordinated control system can effectively manage and control the micro-grid, realize the balance of power distribution, satisfy the reliability of power supply of important load, maintain the frequency stability of AC feeder, and improve the utilization rate of distributed power generation unit. In the aspect of energy optimization of microgrid, combining the framework of cellular membrane system and the second generation of non-dominated genetic algorithm, this paper proposes the non-dominated genetic membrane algorithm (Non-dominated Sorting Genetic Membrane-inspired Algorithm,NSGMIA), and carries on the performance test. Then, the multi-objective energy optimization model of microgrid considering the operating cost of microgrid, pollutant emission and new energy efficiency is set up. Finally, the NSGMIA algorithm is used to solve the multi-objective energy optimization model of microgrid, and the comprehensive solution is selected by fuzzy decision-making. The two-objective energy optimization and three-objective energy optimization of microgrid are realized and the experimental results are analyzed in detail. The experimental results show that the multi-objective energy optimization model of microgrid can effectively realize the integrated control strategy of cost, pollution discharge and new energy utilization, and the optimal solution set obtained by using NSGMIA has better distribution and diversity. It effectively improves the level of operation and management of microgrid.
【学位授予单位】：西华大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727
【引证文献】
相关硕士学位论文 前1条
1 明俊;基于神经型P系统的微电网功率协调控制研究[D];西华大学;2018年
，本文编号：2472032
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