2-Stage Electric Load Forecasting Scheme for Day-Ahead CCHP Scheduling

Sungwoo Park, Jihoon Moon, Eenjun Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Smart grid technology has been gaining much attention as a solution for energy shortage and environmental pollution problems. For the deployment of the smart grid, among the various energy systems, CCHP (Combined Cooling, Heating and Power) has attracted much attention because it can reduce energy costs effectively by using the thermal energy generated by the power generation process for heating and cooling. In this paper, we propose a novel 2-stage load forecasting model and perform value-based CCHP operation scheduling based on the model. To construct our model, we first perform an hourly load forecasting using two popular algorithms for time series forecasting, XGBoost (Extreme Gradient Boosting) and Random Forest. And then, we combine their forecasting results using a sliding window-based Multiple Linear Regression to reflect the energy consumption pattern more accurately. The basic guideline of the CCHP operating schedule is to run CCHP only when using CCHP is more economical than using the public power system. We report some of the results.

Original languageEnglish
Title of host publication2019 IEEE 13th International Conference on Power Electronics and Drive Systems, PEDS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538664995
DOIs
Publication statusPublished - 2019 Jul
Event13th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2019 - Toulouse, France
Duration: 2019 Jul 92019 Jul 12

Publication series

NameProceedings of the International Conference on Power Electronics and Drive Systems
Volume2019-July
ISSN (Print)2164-5256
ISSN (Electronic)2164-5264

Conference

Conference13th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2019
CountryFrance
CityToulouse
Period19/7/919/7/12

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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