基于预测控制的微电网能量管理系统研究

发布时间：2019-06-16 17:15

【摘要】：电力需求的持续增长,日益严重的环境污染以及传统化石燃料短缺等问题正驱使电网朝着高效、灵活、智能和可持续方式发展。微电网技术提高了分布式发电系统的供电可靠性,通过对分布式电源(DG)尤其是可再生能源的规模化接入与应用实现了分布式电源与负荷的一体化运行,是智能配电网未来的发展趋势,是实现可持续发展、可再生能源高效利用和在配电网中广泛接入的重要手段。然而,由于新能源的间歇性、负荷种类多样性、网络拓扑复杂性及电力市场约束性等多种技术难点的出现,使得传统的能量管理策略难以满足实际的控制需求,实现微电网安全、可靠、经济地运行,就需要对微电网能量管理问题进行研究。模型预测控制(Model Predictive Control,MPC)是一种先进的广泛应用于工业领域的控制技术,其突出的优势特点是对被控对象的模型要求不高,能有效处理大量的约束条件并能通过反馈机制实现闭环控制,同样契合于微电网系统的能量管理和协调控制。本文围绕微电网系统的协调控制和能量管理展开研究,主要研究内容有:(1)研究国内外关于微电网发展的状况,分析现有微网存在的主要问题和需要克服的技术挑战,对于系统级的能量管理和协调控制,研究集中式和分散式两种先进的控制策略,介绍模型预测控制的基本原理和在微电网中应用的先进性。(2)针对典型的微电网系统,综合考虑机组组合,经济调度,储能,从电网中买卖电能和负荷削减规划等问题。基于对系统未来行为的预测,可再生能源发电和负荷的预测值,以最小化经济运行成本为目标对微电网运行进行优化控制。对于微电网中不可避免的扰动和预测误差,通过引入反馈机制将其嵌入到MPC框架通过滚动时域方法补偿系统扰动。同时使用混合逻辑动态架构保证储能和电网交互行为的可行性(即非即时的充放电、买卖电)。并使用大量的约束和变量来模型化发电技术和物理特点,考虑蓄电池的寿命和衰退影响。(3)针对存在多用户的微电网中的功率调度,使用多时间尺度预测控制的能量管理策略。上层控制优化储能系统的充放电时间和充放电功率,可控发电单元发电功率并调节负荷需求,下层控制器优化能量在用户间的流动以满足实时的负荷需求。(4)介绍了能量管理系统的发展概况,从功能结构、控制结构以及通信结构三个角度进行分析,根据微电网能量管理系统需求的关键功能,确定微网能量管理系统的设计目标及体系结构,从而设计了基于PCS7的微电网能量管理系统。
[Abstract]:The continuous growth of power demand, the increasing environmental pollution and the shortage of traditional fossil fuels are driving the power grid to develop in an efficient, flexible, intelligent and sustainable way. Microgrid technology improves the power supply reliability of distributed power generation system. Through the large-scale access and application of distributed power supply (DG), especially renewable energy, the integrated operation of distributed power supply and load is the future development trend of intelligent distribution network and an important means to realize sustainable development, efficient utilization of renewable energy and extensive access in distribution network. However, due to the intermittent of new energy, the diversity of load types, the complexity of network topology and the constraint of power market, the traditional energy management strategy is difficult to meet the actual control needs and realize the safe, reliable and economical operation of microgrid, so it is necessary to study the energy management of microgrid. Model Predictive Control (Model Predictive Control,MPC) is an advanced control technology which is widely used in industrial field. its outstanding advantage is that the model of the controlled object is not high, it can effectively deal with a large number of constraints and can realize closed-loop control through feedback mechanism, which is also suitable for energy management and coordinated control of microgrid system. In this paper, the coordinated control and energy management of microgrid system are studied. the main research contents are as follows: (1) to study the development of microgrid at home and abroad, to analyze the main problems and technical challenges to be overcome in the existing microgrid, and to study two advanced control strategies, centralized and decentralized, for energy management and coordinated control at the system level. This paper introduces the basic principle of model predictive control and the advanced application in microgrid. (2) for typical microgrid systems, the problems of unit combination, economic dispatching, energy storage, buying and selling electric energy and load reduction planning from power grid are considered comprehensively. Based on the prediction of the future behavior of the system and the prediction of renewable energy power generation and load, the operation of microgrid is optimized with the goal of minimizing the economic operation cost. For the inevitable disturbance and prediction error in microgrid, the feedback mechanism is introduced into the MPC framework to compensate the disturbance of the system by rolling time domain method. At the same time, the hybrid logic dynamic architecture is used to ensure the feasibility of energy storage and power grid interaction (that is, non-immediate charging and discharging, buying and selling electricity). A large number of constraints and variables are used to model the power generation technology and physical characteristics, considering the life and decline of the battery. (3) the energy management strategy of multi-time scale predictive control is used for power scheduling in multi-user microgrid. The upper layer control optimizes the charge-discharge time and charge-discharge power of the energy storage system, the controllable power generation unit generates power and adjusts the load demand, and the lower layer controller optimizes the energy flow between users to meet the real-time load demand. (4) the development of the energy management system is introduced, and the development of the energy management system is analyzed from three angles of function structure, control structure and communication structure, according to the key functions of the energy management system requirements of the micro-grid. The design goal and architecture of microgrid energy management system are determined, and a microgrid energy management system based on PCS7 is designed.
【学位授予单位】：北方工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727

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