A low-carbon optimization scheduling method of CIES based on PPO algorithm
The tiered carbon trading mechanism and optimization scheduling model solving algorithm are pivotal for the community integrated energy system (CIES). CIES plays a crucial role in optimizing scheduling, yet existing literature often does not fully consider these two factors. To address this gap, the...
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Editorial Department of Electric Power Engineering Technology
2024-11-01
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| Series: | 电力工程技术 |
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| Online Access: | https://www.epet-info.com/dlgcjsen/article/abstract/240411338 |
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| author | CHEN Fan WU Lingxiao WANG Man LYU Ganyun ZHANG Xiaolian |
| author_facet | CHEN Fan WU Lingxiao WANG Man LYU Ganyun ZHANG Xiaolian |
| author_sort | CHEN Fan |
| collection | DOAJ |
| description | The tiered carbon trading mechanism and optimization scheduling model solving algorithm are pivotal for the community integrated energy system (CIES). CIES plays a crucial role in optimizing scheduling, yet existing literature often does not fully consider these two factors. To address this gap, the adoption of the proximal policy optimization (PPO) algorithm is proposed, which incorporates a ladder-type carbon trading mechanism to solve the low-carbon optimization scheduling problem of CIES. This method constructs a reinforcement learning interactive environment based on a low-carbon optimization scheduling model. The intelligent agent's state, action space, and reward function are defined using device status and operating parameters. An intelligent agent capable of generating the optimal policy is obtained through offline training. Case study analysis results demonstrate that the low-carbon optimization scheduling scheme for CIES achieved through the PPO algorithm, effectively leverages the advantages of the tiered carbon trading mechanism, significantly reducing carbon emissions and improving energy utilization efficiency. |
| format | Article |
| id | doaj-art-eacfd2ea293a488a8d59af10035bf26a |
| institution | OA Journals |
| issn | 2096-3203 |
| language | zho |
| publishDate | 2024-11-01 |
| publisher | Editorial Department of Electric Power Engineering Technology |
| record_format | Article |
| series | 电力工程技术 |
| spelling | doaj-art-eacfd2ea293a488a8d59af10035bf26a2025-08-20T02:36:03ZzhoEditorial Department of Electric Power Engineering Technology电力工程技术2096-32032024-11-01436889910.12158/j.2096-3203.2024.06.009240411338A low-carbon optimization scheduling method of CIES based on PPO algorithmCHEN Fan0WU Lingxiao1WANG Man2LYU Ganyun3ZHANG Xiaolian4School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, ChinaSchool of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, ChinaSchool of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, ChinaSchool of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, ChinaSchool of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, ChinaThe tiered carbon trading mechanism and optimization scheduling model solving algorithm are pivotal for the community integrated energy system (CIES). CIES plays a crucial role in optimizing scheduling, yet existing literature often does not fully consider these two factors. To address this gap, the adoption of the proximal policy optimization (PPO) algorithm is proposed, which incorporates a ladder-type carbon trading mechanism to solve the low-carbon optimization scheduling problem of CIES. This method constructs a reinforcement learning interactive environment based on a low-carbon optimization scheduling model. The intelligent agent's state, action space, and reward function are defined using device status and operating parameters. An intelligent agent capable of generating the optimal policy is obtained through offline training. Case study analysis results demonstrate that the low-carbon optimization scheduling scheme for CIES achieved through the PPO algorithm, effectively leverages the advantages of the tiered carbon trading mechanism, significantly reducing carbon emissions and improving energy utilization efficiency.https://www.epet-info.com/dlgcjsen/article/abstract/240411338community integrated energy system (cies)optimize schedulingproximal policy optimization (ppo) algorithmladder-type carbon trading mechanismpenalty coefficientcarbon emission |
| spellingShingle | CHEN Fan WU Lingxiao WANG Man LYU Ganyun ZHANG Xiaolian A low-carbon optimization scheduling method of CIES based on PPO algorithm 电力工程技术 community integrated energy system (cies) optimize scheduling proximal policy optimization (ppo) algorithm ladder-type carbon trading mechanism penalty coefficient carbon emission |
| title | A low-carbon optimization scheduling method of CIES based on PPO algorithm |
| title_full | A low-carbon optimization scheduling method of CIES based on PPO algorithm |
| title_fullStr | A low-carbon optimization scheduling method of CIES based on PPO algorithm |
| title_full_unstemmed | A low-carbon optimization scheduling method of CIES based on PPO algorithm |
| title_short | A low-carbon optimization scheduling method of CIES based on PPO algorithm |
| title_sort | low carbon optimization scheduling method of cies based on ppo algorithm |
| topic | community integrated energy system (cies) optimize scheduling proximal policy optimization (ppo) algorithm ladder-type carbon trading mechanism penalty coefficient carbon emission |
| url | https://www.epet-info.com/dlgcjsen/article/abstract/240411338 |
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