통합인지 IoT G/W를 통한 빅데이터 기반 에너지 절감 솔루션 연구

Abstract

본 논문에서는 한전에서 시행하는 방향과는 다른 측면에서 소규모 전력 소비처 즉, 중소기업 공장 및 빌딩, 개인 등의 불필요한 전기에너지 소비를 줄이고 최대의 효과를 얻기 위해 각 소비처의 전기에너지 소비를 위한 데이터를 축적(빅데이터)·분석(머신 러닝)·컨설팅에 대한 기술연구이다.; Recently, de-nuclear power generation based on eco-friendly trends has become a major issue in Korea, raising interest in renewable energy, and saving energy due to the depletion of fossil energy worldwide has become the biggest challenge. Currently, 54 percent of all industrial electricity is used in Korea, but the reduction in industrial electricity is not necessary due to the business owner's perception as the system of the fare is provided at a cheaper price than for home or general use. In particular, DSM (Demand Side Management) through electricity reduction is urgently needed for manufacturing businesses that use 48% of their total electricity use. It is deemed necessary to maximize and optimize the energy efficiency of manufacturing plants as the industrial sector is expected to have a significant impact on the increase in electricity prices due to de-nuclear power generation or fossil energy depletion, or from the change in the system of electricity rates in the manufacturing industry. However, it is true that manufacturing plants that consume a lot of energy lack preparedness for efficiency and savings and are burdened with the cost of building facilities. Developing an integrated, cognitive IoT energy-saving platform that can be easily applied to these consumers will help to reduce energy costs for each consumer as well as streamline the nation's power demand with fast and flexible demand management responses. This paper is a technical study on the accumulation (big data) and analysis (machine running) and consulting of small and medium-sized power consumption sources, i.e., small and medium-sized enterprises factories, buildings, and individuals, in order to reduce unnecessary electricity consumption and achieve maximum effectiveness.