Preprint Article Version 1 This version is not peer-reviewed

A Study on the Improvement of Thermal Energy Efficiency for District Thermal Energy Consumer Facility based on Reinforcement Learning

Version 1 : Received: 24 May 2018 / Approved: 24 May 2018 / Online: 24 May 2018 (16:05:27 CEST)

How to cite: Kim, Y.; Heo, K.; You, G.; Lim, H.; Choi, J.; Eom, J. A Study on the Improvement of Thermal Energy Efficiency for District Thermal Energy Consumer Facility based on Reinforcement Learning. Preprints 2018, 2018050353 (doi: 10.20944/preprints201805.0353.v1). Kim, Y.; Heo, K.; You, G.; Lim, H.; Choi, J.; Eom, J. A Study on the Improvement of Thermal Energy Efficiency for District Thermal Energy Consumer Facility based on Reinforcement Learning. Preprints 2018, 2018050353 (doi: 10.20944/preprints201805.0353.v1).

Abstract

This paper presents a study on the thermal efficiency improvement of the user equipment room in the district heating system based on reinforcement learning [1], and suggests a general method of constructing a learning network(DQN)[2] using deep Q learning[3], which is a reinforcement learning algorithm that does not specify a model. In addition, we introduce the big data platform system and the integrated heat management system for the energy field in the massive data processing from the IoT sensor installed in large number of thermal energy control facilities.

Subject Areas

big data; big data system; energy; district heating; reinforcement learning

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