Efficient operation method of aquifer thermal energy storage system using demand response

Jewon Oh, Daisuke Sumiyoshi, Masatoshi Nishioka, Hyunbae Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The mass introduction of renewable energy is essential to reduce carbon dioxide emissions. We examined an operation method that combines the surplus energy of photovoltaic power generation using demand response (DR), which recognizes the balance between power supply and demand, with an aquifer heat storage system. In the case that predicts the occurrence of DR and performs DR storage and heat dissipation operation, the result was an operation that can suppress daytime power consumption without increasing total power consumption. Case 1-2, which performs nighttime heat storage operation for about 6 h, has become an operation that suppresses daytime power consumption by more than 60%. Furthermore, the increase in total power consumption was suppressed by combining DR heat storage operation. The long night heat storage operation did not use up the heat storage amount. Therefore, it is recommended to the heat storage operation at night as much as possible before DR occurs. In the target area of this study, the underground temperature was 19.1 °C, the room temperature during cooling was about 25 °C and groundwater could be used as the heat source. The aquifer thermal energy storage (ATES) system in this study uses three wells, and consists of a well that pumps groundwater, a heat storage well that stores heat and a well that used heat and then returns it. Care must be taken using such an operation method depending on the layer configuration.

Original languageEnglish
Article number3129
JournalEnergies
Volume14
Issue number11
DOIs
Publication statusPublished - Jun 1 2021

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

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