<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>As the core of park intelligence, the smart park energy control platform realizes the efficient management and optimal use of park energy by integrating and applying IoT technology. This study focuses on the research development and application of a smart park energy management and control platform using IoT technology, firstly constructing the IoT smart park platform, designing the login module, the park information module, and the energy consumption analysis module, and describing the steps of the smart park energy collection algorithm, and then designing the model of the energy prediction and planning algorithms, i.e.In the construction of the LSTM heating temperature prediction model and the GRU network modeling. Testing and research can be done by using a smart park as an example. The empirical study shows that the construction of the IoT smart park platform can improve the accuracy of monitoring, and the difference between the actual collection results and the system monitoring results is no more than 0.03 kW. After optimizing the configuration, the park’s energy supply system can meet the electric heating and cooling loads with optimal efficiency. Through the comprehensive evaluation of the operation of the extensive energy information monitoring platform, the environmental pollutant emissions are reduced by about 20%, and the platform has a remarkable effect on energy saving and emission reduction.</p>
</abstract>

As the core of park intelligence, the smart park energy control platform realizes the efficient management and optimal use of park energy by integrating and applying IoT technology. This study focuses on the research development and application of a smart park energy management and control platform using IoT technology, firstly constructing the IoT smart park platform, designing the login module, the park information module, and the energy consumption analysis module, and describing the steps of the smart park energy collection algorithm, and then designing the model of the energy prediction and planning algorithms, i.e.In the construction of the LSTM heating temperature prediction model and the GRU network modeling. Testing and research can be done by using a smart park as an example. The empirical study shows that the construction of the IoT smart park platform can improve the accuracy of monitoring, and the difference between the actual collection results and the system monitoring results is no more than 0.03 kW. After optimizing the configuration, the park’s energy supply system can meet the electric heating and cooling loads with optimal efficiency. Through the comprehensive evaluation of the operation of the extensive energy information monitoring platform, the environmental pollutant emissions are reduced by about 20%, and the platform has a remarkable effect on energy saving and emission reduction.

R&amp;D and Application of Smart Park Energy Control Platform Combined with MLM Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

R&D and Application of Smart Park Energy Control Platform Combined with MLM Technology

As the core of park intelligence, the smart park energy control platform realizes the efficient management and optimal use of park energy by integrating and...

R&D and Application of Smart Park Energy Control Platform Combined with MLM Technology

Online veröffentlicht: 03. Juni 2024

Seitenbereich: -

Eingereicht: 13. Feb. 2024

Akzeptiert: 19. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1305

Schlüsselwörter
IOT technology, Energy control platform, LSTM model, GRU network model

© 2024 Bin Xu, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

R&D and Application of Smart Park Energy Control Platform Combined with MLM Technology

Online veröffentlicht: 03. Juni 2024

Seitenbereich: -

Eingereicht: 13. Feb. 2024

Akzeptiert: 19. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1305

SchlüsselwörterIOT technology, Energy control platform, LSTM model, GRU network model

© 2024 Bin Xu, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
IOT technology, Energy control platform, LSTM model, GRU network model