# Research on High-Frequency Information-Transmission Method of Smart Grid Based on CNN-LSTM Model

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## Abstract

**:**

## 1. Introduction

## 2. CNN-LSTM Model

## 3. Smart Grid High-Frequency Information-Transmission Method

#### 3.1. Smart Grid Platform Buffer Division

#### 3.2. Optimizing Control System Using Neural Network Control Module

#### 3.3. Packing Method of Data-Transmission Information

## 4. Simulation

#### 4.1. Parameter Setting

#### 4.2. Experimental Setup

#### 4.3. Unicast vs. Multiplex Rate Comparison

## 5. Discussion

## 6. Conclusions

- (1)
- When the CNN-LSTM model algorithm transmits high-frequency information without adding any other artificial features, the total transmission efficiency is 89%, which not only effectively improves the security of data information but also obviously improves the processing speed. The classification effect of CNN-LSTM model algorithm is better than that of traditional algorithms.
- (2)
- According to CNN-LSTM model, it can ensure the real-time data transmission and the stability of system operations, and contribute to the promotion of the smart grid.
- (3)
- In the next step, we will study how to select a reasonable convolution kernel size in CNN layer for gray images with different sizes, so as to reduce the calculation amount of the algorithm.

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

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**Figure 2.**Comparison of different paths for transmission. (

**a**) Overall efficiency of single-channel transmission; (

**b**) average received bit rate of single-channel transmission; (

**c**) overall efficiency of multiplexing; (

**d**) average received bit rate of multiplex transmission.

Test Times/Time | Information Transmission Channel Model | CNN-LSTM Model | ||
---|---|---|---|---|

32 bit | 96 bit | 32 bit | 96 bit | |

5 | 10 bit/s | 20 bit/s | 19 bit/s | 42 bit/s |

10 | 12 bit/s | 21 bit/s | 20 bit/s | 41 bit/s |

15 | 13 bit/s | 21 bit/s | 22 bit/s | 40 bit/s |

20 | 14 bit/s | 25 bit/s | 22 bit/s | 45 bit/s |

25 | 15 bit/s | 25 bit/s | 24 bit/s | 45 bit/s |

30 | 11 bit/s | 24 bit/s | 24 bit/s | 46 bit/s |

Test Times/Time | Information Transmission Channel Model | CNN-LSTM Model | ||
---|---|---|---|---|

32 bit | 96 bit | 32 bit | 96 bit | |

5 | 10 bit/s | 20 bit/s | 19 bit/s | 42 bit/s |

10 | 12 bit/s | 21 bit/s | 20 bit/s | 41 bit/s |

15 | 13 bit/s | 21 bit/s | 22 bit/s | 40 bit/s |

20 | 14 bit/s | 25 bit/s | 22 bit/s | 45 bit/s |

25 | 15 bit/s | 25 bit/s | 24 bit/s | 45 bit/s |

30 | 11 bit/s | 24 bit/s | 24 bit/s | 46 bit/s |

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**MDPI and ACS Style**

Chen, X.
Research on High-Frequency Information-Transmission Method of Smart Grid Based on CNN-LSTM Model. *Information* **2022**, *13*, 375.
https://doi.org/10.3390/info13080375

**AMA Style**

Chen X.
Research on High-Frequency Information-Transmission Method of Smart Grid Based on CNN-LSTM Model. *Information*. 2022; 13(8):375.
https://doi.org/10.3390/info13080375

**Chicago/Turabian Style**

Chen, Xin.
2022. "Research on High-Frequency Information-Transmission Method of Smart Grid Based on CNN-LSTM Model" *Information* 13, no. 8: 375.
https://doi.org/10.3390/info13080375