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fengji2
- 风力发电模型，此模型较简单，可以模拟风机的功率输出，可以应用于微电网等分布式能源。(Wind power generation model, which is simple and can simulate the power output of wind turbine, can be applied to distributed energy sources such as micro-grid.)
ga_microgrid_dayahead
- 考虑微网发电成本的经济性，以微型燃气轮机发电成本、 储能运行维护成本和微网与主网之间买、卖电的交互成本为系统总成本，以电力平衡及机组运行的相关约束为模型的约束条件，建立使系统的总成本最低为目标函数的日前经济优化调度模型。 日前经济优化调度一般以 24 小时为调度周期，电网的调度中心根据次日调度周期内的负荷以及可再生能源出力预测数据，提前安排次日每个小时内发电机机组或储能设备等的出力情况以及要从上层电网购买或售出的电量，以达到发电成本最小或收益最大的目的。(Considering the econ
period_average_inverter20190123
- 本模型是基于matlab Simulink搭建的PQ控制和下垂控制模型，可以用于微电网的并网和孤岛运行PID参数已经调好，效果理想，可以供参考。(This model is based on the model of PQ control and droop control built by MATLAB Simulink. It can be used in the parallel operation of microgrid and islanding operation. The PID
动态无功优化
- 改进的快速粒子群优化算法计算含DG配电网无功优化和运行费用最优解(Improved Fast Particle Swarm Optimization for Reactive Power Optimization and Operation Cost Optimization of Distribution Network with DG)
Network reconstruction
- 仿真配电网IEEE33节点，创建群粒子，然后判断是否为环路，利用粒子群算法对网络网络重构。(Simulate the IEEE33 node of the distribution network, create group particles, and then judge whether it is a loop, and use the particle swarm algorithm to reconstruct the network network.)
基于多源信息的配电网故障定位技术研究
- 有关配电网故障定位技术的研究，重点分析了阻抗法和行波法
客户验收
- 采用Matlab语言或C语言对配电网节点边际电价计算算例进行编程实现，对多种方案分别进行解算，得到规划结果；分析各条件下的配电网节点边际电价计算结果，得出基于博弈论的配电网节点边际电价计算的研究结论(Matlab or C language is adopted to realize the programming of the marginal price calculation example of distribution network node, and various schemes
DFIG-master
- 含有风力发电的微电网系统仿真，通过控制策略进行功率合理分配(Research on Grid-connected microgrid and its control strategy simulation of microgrid system with wind power generation and reasonable power distribution through control strategy)
基于最优流的配电网络重构程序
- 提出了一种基于改进最优流和遗传算法的配电网重构算法.该算法先利用配电网的同胚图将重构问题的全局寻优空间划分为若干子空间,然后利用改进最优流法寻找子空间内的最优解,之后再利用遗传算法搜索全局最优解所在的子空间,从而实现在局部最优解中寻找全局最优解.(A distribution network reconfiguration algorithm based on improved optimal flow and genetic algorithm is proposed. First, the
粒子优化群算法进行配电网络重构
- 配电网网络重构是配电系统极为重要的优化手段.以配电网网损最低为目标函数,结合约束条件确定配电网静态重构的数学模型,提出基于环路编码、分环替代的策略对配电网重构问题进行求解,最后结合IEEE-33节点算例,证明提出的算法,在降低搜索空间,提高寻优成功率和增加寻优效率上都有突出表现.(Distribution network reconfiguration is a very important means of optimization in distribution system. Taking
EMS_DCMG-master
- 直流微电网运行控制仿真算法，能量管理策略(DC microgrid operation control simulation algorithm, energy management strategy)
配网故障恢复算法方法
- 实现配电网故障恢复和故障重构算法，文件算例是IEEE33节点系统(Implementation of fault recovery and fault reconstruction algorithms for distribution networks.File example is IEEE33 nodes system.)
三目标微网调度
- 对微电网的经济性进行优化调度，有需要的 可以借鉴参考(It can be used for reference if necessary to optimize the economic dispatch of microgrid)
33节点系统重构程序实现
- 33节点潮流计算，用于IEEE-33节点配电网系统重构程序的实现(33-node power flow calculation for the implementation of IEEE-33-node distribution network system reconstruction program)
power system scheme
- 用遗传算法求解电网规划问题，双层算法求解，上层为遗传算法，下层利用拉格朗日对偶线性化后求解(Genetic algorithm is used to solve the power grid planning problem, double-layer algorithm is used to solve the problem, the upper layer is genetic algorithm, and the lower layer is solved by Lagrange dua
reconfiguration
- 本程序用于配电网的网络重构，能有效、快速的对配电网做出重构，方便实用。(This program is used for the network reconstruction of the distribution network, which can effectively and quickly reconstruct the distribution network, which is convenient and practical.)
l
- 本程序实现了22节点的交直流配电网潮流计算。(This program implements the 22-node AC-DC distribution network power flow calculation.)
Distribution network planning
- 提出了一套基于供电网格优化划分的中压配电网规划思路和方法。首先，确定规划区域主干通道布局，确保土地资源预留。然后，在明确网格划分目的和原则的基础上，基于就近选择负荷备供变电站和负荷聚类方法，实现供电网格在全局范围内的优化划分。最后，分别在各供电网格内，基于其供区分类优选接线模式和一、二次建设改造标准，并进行主干线布线规划。(This paper presents a set of ideas and methods for medium voltage distribution network
reactive power optimization of DG
- 建立了基于模型预测控制的配电网多时间尺度无功优化模型，包含日前优化调节层和实时滚动调控层。日前优化侧重于运行经济性，协调配合不同类型无功设备进行大尺度无功调节，并预留充足动态无功储备响应动态调控，降低运行风险；实时滚动调控侧重于系统运行可靠性。(A multi-time scale reactive power optimization model for distribution network based on model predictive control is established,
DBN
- 根据历史电网负荷数据，用深度置信网络预测未来负荷大小(Forecast future load size based on historical grid load data)