基于风力-PVT-燃料电池的微型热电联供系统优化与控制研究
发布时间：2018-09-19 13:46
【摘要】：热电联供微网系统是解决当下能源危机的一项重要技术,高效的能源利用率,种类繁多的分布式单元为联供系统的组建提供了多种类的选择。本文选择建立基于风力-PVT-燃料电池-电解装置的热电联供微网系统,旨在实现能源的节约和环境的保护。但由于风力、光伏发电因环境因素带来的发电随机性、波动性和间歇性的特点,以及负载需求的季节性和阶段性特点,使得系统的容量配置成为研究重点。本文就系统20年全寿命周期下,如何优化配置各单元容量,在满足系统热电负载需求的同时最小化系统运行成本进行研究。主要研究工作围绕PVT效率优化控制和风力-PVT-燃料电池热电联供系统容量配比优化展开,研究思路如下:首先介绍研究当下我国面临的能源问题和背景,提出基于风力、PVT、燃料电池等新能源为基础的热电联供微网系统是解决当下能源问题的一种重要手段。其次设计PVT热电联供系统,对当下已有的PVT系统进行优化;控制PVT系统水循环速率达到最优集热效率,通过热力学第一定律综合效率来评价系统的综合效率,通过对比独立型热水器系统与PV光伏系统来评判系统的优点。重点研究热电联供系统最优容量配置问题,对热电联供微能系统中的各单元进行建模,以NASA气象数据库为依据,获取特定区域的气象资料,并对实时风力光照资源进行分析;提出了以电定热的运行模式,通过分析风力、光伏实时发热电输出与热电负荷需求的不同,建立供需平衡关系式;对系统整体运行策略进行分析,并由此推导出燃料电池、制氢装置的容量的计算公式,以及各分布式单元容量范围。进而建立以最小投资成本为优化目标的目标函数,为接下来具体算法的选择和最优容量配比的计算提供依据。最后通过对比各类算法的特点,选择了自适应型改进型粒子群算法(PSO)作为本文求解最优配比的算法。运用已建立的目标函数作为优化适应度函数来求解最优配比,最后对最优配比下的热电联供系统从成本、实时供需状况、及环保性等多条件下的可行性分析;并选择系统某一时间段运行状况,详细分析系统中各单元如何相互配合来满足用户热电负载平衡。综合多个方面对系统进行了分析和评估,证明系统的有效性及合理性。
[Abstract]:The microgrid system is an important technology to solve the energy crisis. High efficiency of energy utilization and a wide variety of distributed units provide a variety of options for the construction of the co-supply system. In this paper, a thermoelectric microgrid system based on wind power PVT- fuel cell electrolytic unit is established, which aims to save energy and protect the environment. However, due to wind power, the characteristics of randomness, volatility and intermittence of photovoltaic power generation due to environmental factors, as well as the seasonal and phased characteristics of load demand, the capacity allocation of the system becomes the focus of research. In this paper, we study how to optimize the capacity of each unit in order to meet the requirement of thermoelectric load and minimize the operating cost of the system under the life cycle of 20 years. The main research work is focused on the optimization of PVT efficiency control and the optimization of the capacity ratio of the wind-PVT- fuel cell heat and power system. The research ideas are as follows: firstly, the energy problems and background facing our country are introduced. Based on new energy sources, such as wind power PVT and fuel cell, a thermoelectric microgrid system is proposed as an important means to solve the energy problem. Secondly, the PVT heat and power supply system is designed to optimize the existing PVT system, to control the water cycle rate of the PVT system to achieve the optimal heat collection efficiency, and to evaluate the comprehensive efficiency of the system through the first law of thermodynamics synthesis efficiency. The advantages of the system are evaluated by comparing the independent water heater system with the PV photovoltaic system. This paper focuses on the optimal capacity allocation of the combined heat and power supply system, models each unit in the heat and power supply micro-energy system, obtains the meteorological data of the specific area based on the NASA meteorological database, and analyzes the real-time wind power and illumination resources. By analyzing the difference between the demand of wind power, photovoltaic real-time heating output and thermoelectric load, the relationship between supply and demand is established, and the overall operation strategy of the system is analyzed, and the fuel cell is deduced. The calculation formula of the capacity of hydrogen production unit and the capacity range of each distributed unit. Then the objective function with the minimum investment cost as the optimization objective is established, which provides the basis for the selection of the following specific algorithm and the calculation of the optimal capacity ratio. Finally, the adaptive modified particle swarm optimization (PSO) algorithm is chosen as the algorithm to solve the optimal matching by comparing the characteristics of various algorithms. The established objective function is used as the optimization fitness function to solve the optimal matching. Finally, the feasibility analysis of the heat and power co-supply system under the optimal ratio is made under the conditions of cost, real-time supply and demand, and environmental protection. At the same time, the operation condition of the system is selected, and how the units in the system cooperate with each other to meet the load balance of the users is analyzed in detail. The system is analyzed and evaluated in many aspects, and the validity and rationality of the system are proved.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727
[Abstract]:The microgrid system is an important technology to solve the energy crisis. High efficiency of energy utilization and a wide variety of distributed units provide a variety of options for the construction of the co-supply system. In this paper, a thermoelectric microgrid system based on wind power PVT- fuel cell electrolytic unit is established, which aims to save energy and protect the environment. However, due to wind power, the characteristics of randomness, volatility and intermittence of photovoltaic power generation due to environmental factors, as well as the seasonal and phased characteristics of load demand, the capacity allocation of the system becomes the focus of research. In this paper, we study how to optimize the capacity of each unit in order to meet the requirement of thermoelectric load and minimize the operating cost of the system under the life cycle of 20 years. The main research work is focused on the optimization of PVT efficiency control and the optimization of the capacity ratio of the wind-PVT- fuel cell heat and power system. The research ideas are as follows: firstly, the energy problems and background facing our country are introduced. Based on new energy sources, such as wind power PVT and fuel cell, a thermoelectric microgrid system is proposed as an important means to solve the energy problem. Secondly, the PVT heat and power supply system is designed to optimize the existing PVT system, to control the water cycle rate of the PVT system to achieve the optimal heat collection efficiency, and to evaluate the comprehensive efficiency of the system through the first law of thermodynamics synthesis efficiency. The advantages of the system are evaluated by comparing the independent water heater system with the PV photovoltaic system. This paper focuses on the optimal capacity allocation of the combined heat and power supply system, models each unit in the heat and power supply micro-energy system, obtains the meteorological data of the specific area based on the NASA meteorological database, and analyzes the real-time wind power and illumination resources. By analyzing the difference between the demand of wind power, photovoltaic real-time heating output and thermoelectric load, the relationship between supply and demand is established, and the overall operation strategy of the system is analyzed, and the fuel cell is deduced. The calculation formula of the capacity of hydrogen production unit and the capacity range of each distributed unit. Then the objective function with the minimum investment cost as the optimization objective is established, which provides the basis for the selection of the following specific algorithm and the calculation of the optimal capacity ratio. Finally, the adaptive modified particle swarm optimization (PSO) algorithm is chosen as the algorithm to solve the optimal matching by comparing the characteristics of various algorithms. The established objective function is used as the optimization fitness function to solve the optimal matching. Finally, the feasibility analysis of the heat and power co-supply system under the optimal ratio is made under the conditions of cost, real-time supply and demand, and environmental protection. At the same time, the operation condition of the system is selected, and how the units in the system cooperate with each other to meet the load balance of the users is analyzed in detail. The system is analyzed and evaluated in many aspects, and the validity and rationality of the system are proved.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727
【参考文献】
相关期刊论文 前10条
1 解东来;骆锦辉;单杰;聂廷哲;;广州地区应用微型热电联产系统的运行成本及碳减排分析[J];应用化工;2016年03期
2 余长富;阮应君;吴家正;;太阳能光伏光热一体化系统性能影响因素[J];热力发电;2015年11期
3 翟俊义;任建文;周明;李整;;基于模糊多目标粒子群算法的热电联供型微网环境经济调度[J];华北电力大学学报(自然科学版);2015年05期
4 刘美s，
本文编号：2250304
本文链接：https://www.wllwen.com/kejilunwen/dianlidianqilunwen/2250304.html
