微网调度优化模型与方法研究

发布时间：2018-06-17 22:10

本文选题：微网 + 能量管理和优化　；参考：《天津大学》2014年博士论文

【摘要】：微网作为分布式电源的有效组织形式，，不仅能充分发挥分布式发电技术在资源节约和环境保护方面的优势，同时还可有效解决其并网时的技术和管理难题，但目前微网能量管理和优化仍缺乏系统、有效的方法。本文系统研究了微网调度优化的模型和方法，主要工作如下：（1）综合考虑微网系统组成的多样性和能量流动的复杂性，建立了微网所含多种类分布式发电、分布式储能和分布式供热设备的准稳态模型，在分析典型微网组成和结构特征的基础上，提出一种微网通用母线式结构描述方式。该结构不仅协调了设备独立性和系统复杂性之间的矛盾，清晰展示了系统的组成结构和能量流动关系；同时也搭建了系统描述和模型建模之间的桥梁，有利于实现通用模型的程序化、自动化建模。（2）针对含冷热电联供（CCHP）系统的综合型微网调度优化问题，以微网设备准稳态模型和母线式结构能量流描述方法为基础，提出基于母线式结构的微网调度优化模型和方法。以典型的微网经济调度优化模型为例，通过对其目标函数、优化变量和约束条件三项基本要素的分析和处理，详细阐述微网调度优化模型的建模过程。根据微网经济调度优化模型的特征，选择数学规划方法和智能算法对模型进行求解，分析了调度策略、设备模型、电价机制等对调度计划和运行费用的影响。（3）进一步结合多目标优化、随机优化和调度设计一体化问题对微网调度优化模型进行了扩展，丰富了调度优化模型的体系结构。通过多目标调度优化模型、随机调度优化模型和调度设计双层优化模型的建模和算例分析，研究了微网环境成本、不确定因素和系统配置对调度计划的影响，证实了基于母线式结构微网调度优化模型的通用性和鲁棒性。针对此三类扩展模型，通过Pareto优化与初始点引导技术的结合、Monte Carlo仿真与遗传算法的结合、多目标进化算法和数学规划方法的结合，有效提升了扩展模型的求解能力和优化效果。
[Abstract]:As an effective organization of distributed power generation, microgrid can not only give full play to the advantages of distributed power generation technology in resource conservation and environmental protection, but also effectively solve the technical and management problems when connected to the grid. However, there is still a lack of systematic and effective methods for microgrid energy management and optimization. This paper systematically studies the model and method of microgrid scheduling optimization. The main work is as follows: 1) considering the diversity of microgrid system composition and the complexity of energy flow, a multi-type distributed generation system is established. The quasi-steady model of distributed energy storage and distributed heating equipment is presented. Based on the analysis of typical microgrid composition and structural characteristics, a bus structure description method for micro-network communication is proposed. The structure not only coordinates the contradiction between the independence of the equipment and the complexity of the system, but also clearly shows the relationship between the composition of the system and the energy flow, and also builds a bridge between the system description and the modeling of the system. It is helpful to realize the programming and automatic modeling of the general model. (2) aiming at the optimization of integrated microgrid scheduling for CCHPs with combined cooling and heat supply system, based on the quasi-steady model of microgrid equipment and the energy flow description method of generatrix structure, The optimization model and method of microgrid scheduling based on busbar structure are presented. Taking the typical microgrid economic scheduling optimization model as an example, the modeling process of the microgrid scheduling optimization model is described in detail through the analysis and processing of its objective function, optimization variables and constraints. According to the characteristics of microgrid economic scheduling optimization model, the mathematical programming method and intelligent algorithm are selected to solve the model, and the scheduling strategy and equipment model are analyzed. The influence of electricity pricing mechanism on scheduling plan and operation cost. (3) combining with multi-objective optimization, stochastic optimization and scheduling design integration, the optimization model of micro-grid scheduling is extended. It enriches the architecture of scheduling optimization model. Based on the modeling of multi-objective scheduling optimization model, stochastic scheduling optimization model and scheduling design bilevel optimization model, the effects of microgrid environment cost, uncertainty factors and system configuration on scheduling plan are studied. The generality and robustness of the scheduling optimization model based on generatrix structure are confirmed. By combining Pareto optimization with initial point guidance technique, Monte Carlo simulation and genetic algorithm, and the combination of multi-objective evolutionary algorithm and mathematical programming method, the solving ability and optimization effect of the extended model are improved effectively.
【学位授予单位】：天津大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TM73

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