Chemical/Energy
17992
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Chemical/Energy

Incheon Total Energy Company

Using AWS Forecast, a service based on AWS PaaS, the applicability of production management by predicting the heat demand of housing, work, and public users supplied by Incheon Total Energy Company

#Eco-friendly_And_Reliable_Energy_Supply, #Promoting_Comfortable_Living_Convenience, #Demand_Forecasting_Using_AWS_Forest, #Production_Management_Through_Demand_Forecasting

Company Overview

  • Incheon Energy was established in June 2004 to create a pleasant living environment and contribute to the national energy conservation by supplying cooling and heating to the Incheon area centered on Songdo International City.
  • The company is striving to provide high-quality energy services to more citizens by expanding the supply area to the old downtown area of Incheon.
  • It will take the lead in creating a happy energy world with customers by practicing active social contribution activities for the development of the community.

The Situation

  • Need to manage production volume by predicting heat demand of housing, work, and public users supplied by Incheon Total Energy Company
  • Need to make predictions based on historical data that actually occurred and verify the accuracy of demand forecasts by comparing demand over a specific period of time

The Solution

  • Pre-processing data such as correlation analysis and outlier verification through exploratory data analysis
  • Creating a case and scenario and then performing AWS Forecast
  • Analyzing accuracy and error rate with existing performance results

The benefit

Achieving high accuracy by reflecting highly relational influencing factors
Verifying the applicability of production management through demand forecasting
Identifying factors affecting energy demand

Cheongna Energy

Using AWS Forecast, an AWS PaaS-based service, to validate the applicability of production management through prediction of energy demand in time units supplied by Cheongna Energy

#Supply_Of_Cooling_And_Heating_Heat_To_Incheon_And_Gimpo_Areas, #An_Eco-friendly_Company_That_Grow_With_The_Community, #The_Big_4_With_KDHC,_GS_Power,_And_Seoul_Energy

Company Overview

  • Cheongna Energy is a collective energy business established in 2005 to stably supply high-quality cooling and heating heat to Incheon and Gimpo areas.
  • Starting with the Gimpo Janggi District in March 2008, the company is doing our best to supply eco-friendly energy to all business districts such as Cheongna, Gimpo Hangang New Town, Luwon City, and Geomdan New Town.
  • In 2019, for the first time in Korea, it received waste heat from SK Incheon Petrochemical, a large nearby factory, and used it as local heating and cooling energy, suggesting a new paradigm for unused energy sources.

The Situation

  • Need to manage production volume by predicting heat demand of housing, work, and public users supplied by Cheongna Energy
  • Need to make predictions based on historical data that actually occurred and verify the accuracy of demand forecasts by comparing demand over a specific period of time

The Solution

  • Performing variable characterization and variable relationship identification when analyzing data
  • Creating a case and scenario and then performing AWS Forecast
  • Analyzing accuracy and error rate with existing performance results

Understanding Variable Attributes

Identifying Variable Relationships

The benefit

Achieving high accuracy by reflecting highly relational influencing factors
Verifying the applicability of production management through demand forecasting
Identifying factors affecting energy demand