GIST Professor Jin Ho Kim develops an A.I. / cloud-based smart building energy management platform
□ Professor Jin Ho Kim of the Institute of Integrated Technology at the Gwangju Institute of Science and Technology (GIST • President Seung Hyeon Moon) will develop a Flexible Demand Response Platform for small and medium sized buildings with Omni System Co., Ltd., over the next 3 years.
∘ Research Institute for Solar and Sustainable Energies Director Hyuk Lim said, " Flexible Demand Response Platform refers to new and renewable energy (PV), Energy Storage (ESS), Electric Vehicle (EV), Demand Resources (DR), etc., with a cloud-based smart building energy management platform that optimizes the flexibility and flexibility of energy production and consumption by combining real-time economic benefits such as distributed energy sources * and power demand patterns and energy market transactions and pricing information."
* Distributed energy source refers to small, environmentally friendly renewable, distributed power generation, storage devices, electric vehicles, demand reaction resources, etc. located near electric consumers instead of large power generators, such as nuclear power plants, coal, etc.).
□ The smart building energy management platform developed in this project analyzes the technical characteristics of various distributed energy sources (DER, renewal (PV), ESS, EV, DR, etc.) located in buildings with cloud-based artificial intelligence and big data technology, developing a service-linked business model that links the results to market trading mechanisms (DR trading market, distributed power brokerage market, emissions trading, REC market, retail electricity rates, etc.) .
∘ It is possible to dramatically improve the existing building energy management system by combining innovative technologies such as AI and Big Data and the new business model of the electric power market. That is the final goal of this project.
∘ GIST Professor Euiseok Hwang's research team predicts that the power demand of buildings based on stochastic modeling and AI techniques can accurately analyzes the operation patterns of storage devices (ESS) and EVs. Professor Hyuk Lim's research team will apply statistical techniques based on big data and the cloud based machine learning theory to develop smart building energy optimization technologies that reflect economic and technical characteristics.
∘ The technology and business model developed through this research will be demonstrated from next year at the Research Institute for Solar and Sustainable Energies, which will feature a 250kW storage system (ESS), a service- (EV) and a programmable bi-directional charger.
□ Professor Jin Ho Kim said, "The building demand response (DR) system and the energy management system developed so far have been at a rudimentary level that monitors customers' energy consumption and simple operation by pre-set standards. However, future smart energy management platforms to be developed by GIST will be a very innovative model that accurately analyzes the technical characteristics of distributed energy sources and connects the results to services and businesses in the energy market. Therefore, it will not only improve the domestic energy technology level dramatically but also create new energy business opportunities."
