Operational Control for Earth-to-Air Heat Exchanger through Proximal Policy Optimization
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- HIRATA Kazuma
- Graduate School, The University of Kitakyushu
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- TOMODA Kento
- HEROZ, Inc.
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- SHIRAISHI Yasuyuki
- The University of Kitakyushu
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- HASEGAWA Kenichi
- Akita Prefecture University
Bibliographic Information
- Other Title
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- Proximal Policy Optimizationによる土壌熱交換システムの運用制御
Abstract
<p>Earth-to-air heat exchangers (EAHEs) utilize the heat capacity of soil to pre-cool or pre-heat outside air. However, condensation can build up within an EAHE, and can potentially lead to air pollution. It is necessary to optimize the control of EAHE in the operational phase. In this study, we focused on reinforcement learning (RL) control. In our previous study, we proposed a Deep Q-Network (DQN) based control method and showed its effectiveness as an operational control for EAHEs. DQN is a value-based algorithm that learns the value function Q to find the policies. In contrast, a policy-based algorithm learns policies directly, without learning a value function. However, the operation control of an EAHE using a policy-based algorithm has not been examined. The purpose of this study is to establish the optimal control rules for an EAHE using proximal policy optimization (PPO), which is a policy-based RL algorithm. First, we define the control problem for RL using the environment estimated by a long-term performance prediction method of EAHE based on CFD. Then, we implement PPO. We verify the effectiveness of PPO by comparing random control with DDQN. The following results were obtained. 1) The number of learning iterations required to converge was about 200 for PPO and 150 for DDQN. At the end of the study, the sum of rewards was about -2,000 for DDQN and -1,500 for PPO. 2) Compared with random control and DDQN, PPO achieved the highest control performance in both energy saving and condensation control.</p>
Journal
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- Transactions of the Society of Heating,Air-conditioning and Sanitary Engineers of Japan
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Transactions of the Society of Heating,Air-conditioning and Sanitary Engineers of Japan 47 (301), 27-36, 2022-04-05
The Society of Heating, Air-Conditioning & Sanitary Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390295658315349504
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- ISSN
- 24240486
- 0385275X
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed