A low-carbon scheduling method for multi-energy flow buildings based on deep reinforcement learning
Building emissions reduction has become a crucial pathway for China to achieve its ‘dual-carbon’ goals. As an integrated energy entity coupled with multi-energy flow networks， smart buildings face challenges such as high carbon emissions， a high degree of coupling in multi-energy flow networks， and...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
zhejiang electric power
2024-02-01
|
| Series: | Zhejiang dianli |
| Subjects: | |
| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=bb6cbc28-ae2f-4b45-9011-d5ab14bcfae9 |