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Quantifying the Flexibility From Industrial Steam Systems for Supporting the Power Grid
- Source :
- IEEE Transactions on Power Systems. 36:313-322
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- With more variable and uncertain patterns of electricity production and consumption, the need for flexibility in the power grid is becoming increasingly crucial. Industrial energy systems have the potential to contribute to providing such flexibility. Yet, there is still a lack of effective methods to quantify the magnitude of available flexibility from industrial energy systems that can be optimally dispatched to support the operation of the power grid. This paper studies the flexibility provision from steam systems, which exist in many energy-intensive industries. A generic model of industrial steam systems with turbine-generators is presented to reflect its interactions with the power grid. Then, a hybrid physics-based and data-driven approach is developed to approximate the boundaries of the flexibility domain at different operating conditions of the steam systems. The proposed flexibility quantification method is applied to two real industrial steam systems in a paper mill and a steel mill. The results show that the proposed method can approximate the flexibility boundaries under uncertainty steam states and reflect key factors that affect the boundaries. Also, it is shown that neglecting the limits imposed by the steam network leads to an overestimation of flexibility boundaries at certain operating conditions.
- Subjects :
- Flexibility (engineering)
business.industry
020209 energy
Energy Engineering and Power Technology
02 engineering and technology
Domain (software engineering)
Variable (computer science)
Electricity generation
Key factors
Steel mill
0202 electrical engineering, electronic engineering, information engineering
Power grid
Electrical and Electronic Engineering
Process engineering
business
Energy (signal processing)
Subjects
Details
- ISSN :
- 15580679 and 08858950
- Volume :
- 36
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Power Systems
- Accession number :
- edsair.doi...........758dbf13f7566b7b24ae728b0fd01978