微电网经济运行的优化算法研究

发布时间：2018-07-06 20:46

本文选题：微电网 + 经济运行　；参考：《浙江大学》2014年硕士论文

【摘要】：微电网是一组由分布式电源、储能设备、用电设备以及控制装置构成的新型网络结构。微电网作为解决电力系统众多问题的重要手段,需要尽可能地发挥出其带来的巨大的经济效益。因此,微电网经济运行是吸引用户并使其能够在电力系统中得以推广的关键。然而,随着微电网中设备种类增加、规模不断扩大,微电网经济运行的优化问题变得越来越复杂。现有的优化调度策略已经不能满足微电网新的发展趋势。本文从优化微电网经济运行入手,提出了基于拉格朗日松弛新的分布式优化算法,降低了微电网运行的成本,提高了算法运行效率。本文主要完成的工作如下： 1)本文解决了微电网需求侧负荷调度问题。现有文献需求侧负荷调度算法不能处理大规模负荷调度的问题。因此,本文在拉格朗日松弛分解的基础上,改进了有界二次规划和Benders分解,提出了一种适用于大规模计算的新的分布式算法,解决了用电设备和储能设备的联合调度优化问题。通过仿真验证了该算法不仅能够有效降低需求侧运行成本,而且计算时间明显好于已有的集中式算法。 2)本文解决了微电网中热能机组和用电设备的联合调度优化问题。考虑的场景是只包含热能机组和用电设备的微电网运行优化。研究目的是当大电网出现故障时,处于孤网状态下的微电网也能低成本可靠地运行。本文采用拉格朗日松弛分解对联合优化问题进行解耦。针对解耦后的单机问题采用了动态规划进行求解。通过仿真证明了算法能够有效地降低微电网运行成本和转移峰值负荷。 3)本文解决了考虑风力发电,处于并网状态微电网经济运行随机调度问题。本文使用了机会约束描述风力发电的随机性,解决了使用期望值模型概率上的局限性。另外,本文提出了微电网经济运行优化的分布式实现架构,并且给出了微电网并网状态下经济运行的一般优化策略,降低了微电网的运行成本。通过仿真证明了本文提出的算法能够高效地解决微电网经济运行问题。
[Abstract]:Microgrid is a new network structure composed of distributed generation, energy storage equipment, electric equipment and control device. As an important means to solve many problems of power system, microgrid needs to bring into full play the enormous economic benefits brought by it. Therefore, the economic operation of microgrid is the key to attract users and make it popularize in power system. However, with the increase of equipment types and scale in microgrid, the optimization of microgrid economic operation becomes more and more complicated. The existing optimal dispatching strategy can not meet the new development trend of microgrid. In this paper, a new distributed optimization algorithm based on Lagrangian relaxation is proposed to optimize the economic operation of microgrid, which can reduce the cost of microgrid operation and improve the efficiency of the algorithm. The main work of this paper is as follows: 1) this paper solves the demand side load dispatching problem of micro grid. The existing literature on demand side load scheduling algorithm can not deal with the problem of large scale load scheduling. Therefore, on the basis of Lagrangian relaxation decomposition, the bounded quadratic programming and Benders decomposition are improved, and a new distributed algorithm for large-scale computation is proposed, which solves the joint scheduling optimization problem of power equipment and energy storage equipment. The simulation results show that the algorithm not only can effectively reduce the cost of demand-side operation, And the computational time is obviously better than the existing centralized algorithm. 2) this paper solves the problem of joint dispatch optimization of thermal energy unit and electric equipment in microgrid. The scenario considered is microgrid operation optimization with only thermal units and electrical equipment. The purpose of this study is that when the large power grid fails, the microgrid in the isolated network can also operate reliably at low cost. In this paper, Lagrangian relaxation decomposition is used to decouple the joint optimization problem. Dynamic programming is used to solve the decoupled single machine problem. The simulation results show that the algorithm can effectively reduce the operating cost and transfer peak load of microgrid. 3) this paper solves the stochastic scheduling problem of economic operation of microgrid considering wind power generation and grid-connected state. In this paper, the chance constraint is used to describe the randomness of wind power generation, and the probability limitation of using the expected value model is solved. In addition, this paper proposes a distributed implementation framework for the economic operation optimization of microgrid, and gives the general optimization strategy of economic operation under the condition of microgrid connection, which reduces the operation cost of microgrid. Simulation results show that the proposed algorithm can efficiently solve the problem of economic operation of microgrid.
【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】：TM732

【参考文献】