학술논문

Energy flexibility assessment of an industrial coldstore process
Document Type
Conference
Source
2016 IEEE International Energy Conference (ENERGYCON) Energy Conference (ENERGYCON), 2016 IEEE International. :1-6 Apr, 2016
Subject
Power, Energy and Industry Applications
Compressors
Boundary conditions
Training
Predictive models
Cooling
Computational modeling
Industries
Language
Abstract
Power-intensive industry plays a key role in balancing supply and demand in the energy grid: by offering flexible power, industry can reduce operating costs and grid operators can avoid technical failures. Recently, research has started to try and address the challenging question of determining the amount of power curtailment (i.e., how much power can be reduced for how long) without violating any process constraints. We consider several machine learning methods to assess the curtailment potential in a coldstore, based on historical data.