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Battery modeling, analysis and optimization (Matlab code implementation)

2022-08-09 10:00:00 【Electrical Engineering Workshop】

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本文目录如下：️️️

目录
1 概述
2 数学模型
3 Stability and linear
4 模拟结果与分析
5 Matlab代码及文章详细讲解
6 写在最后

1 概述

In the past few years there are many problems,These questions to stimulate interest in developing smart grid.Some of these issues is growing,Because carbon,The uncertainty of fossil fuel has stimulated transportation electrification market.此外,Demand for high quality without any interruption power continues to grow,And without loss of transport the electricity.These are created demand for smart grid.建模、控制、Optimization and modeling will be used in the technology of the smart grid work together.The smart grid will be driven by network infrastructure,Through wide-area sensing、先进通信、Control and distributed drive power flow.All issues in today's power grid and sustainable energy hidden control problem.This paper presents a battery active power control、使用 FACTS Carries on the coordination control of variable power generation and use of distributed renewable energy for reactive power control sample.

2 数学模型

1.分析：Simulation or prediction.给定当前 u(t),x(0) 的未来轨迹,以及系统模型 σ,预测 y(t) .
2. 状态估计：Given a time history u(t) 和 y 的系统 σ (t),找到与 σ,u,y 一致的 x.This is the problem monitoring.也就是说,You can't measure each state,But want to monitor each state.
3. System design or planning：给定 u(t) And some of the expected y(t),找到 σ 使得 u(t) Effects on the system will produce y(t).Most engineering disciplines are integrated processing design.传统上,People may create a variety of physical prototype to make the required system.
4. 模型识别：Given time journey u(t) 和 y(t),Usually from experimental data,确定与 u 和 y Consistent with the model and its parameter values.
5. 控制综合.Given a with the current state x(0) And some of the expected y(t) 的系统,找到 u(t) Make the system will generate y(t).The energy management problem.

$V(t)-O C V(z(t))-V_{c}(t)-R_{1} I(t)=0$

$V(t)=O C V(z(t))+V_{c}(t)+R_{1} I(t)$

$\frac{d}{d t}\left[\begin{array}{c} z(t) \\ V_{c}(t) \end{array}\right]=\left[\begin{array}{cc} 0 & 0 \\ 0 & \frac{-1}{C R_{2}} \end{array}\right]\left[\begin{array}{c} z(t) \\ V_{c}(t) \end{array}\right]+\left[\begin{array}{c} \frac{1}{Q} \\ \frac{1}{C} \end{array}\right] I(t)$

Mathematical model and explain in detail to see5部分.

3 Stability and linear

$\dot{x}(t)=\frac{d}{d t}\left[\begin{array}{c} z(t) \\ V_{c}(t) \end{array}\right]=\left[\begin{array}{cc} 0 & 0 \\ 0 & \frac{-1}{C R_{2}} \end{array}\right]\left[\begin{array}{c} z(t) \\ V_{c}(t) \end{array}\right]=\left[\begin{array}{cc} 0 & 0 \\ 0 & -0.4 \end{array}\right]\left[\begin{array}{c} z(t) \\ V_{c}(t) \end{array}\right] .$

See the rest5部分.

4 模拟结果与分析

当 OCV Stability and fall,Linearized version will off track.Because of the change in the direction of the second derivative,Linear model will produce the error,It only considers a derivative. OCV From the concave up to down.Linear model can only help us estimate system to a certain point.显而易见的是,当 OCV Change the direction and the second derivative error occurs.