Journal Article FZJ-2026-01751

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Unlocking reactive power potential of industrial processes for voltage support through scheduling optimization

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2026
Elsevier Science Amsterdam [u.a.]

Computers & chemical engineering -, 109591 () [10.1016/j.compchemeng.2026.109591]

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Abstract: Demand response of industrial processes generally accounts for active power, but not reactive power which grows in importance for balancing local voltage levels in future electricity grids. We present an optimization-based approach to integrate reactive power into demand response scheduling and derive first estimates on the arising potentials. To this end, we extend a resource-task network scheduling model to account for the reactive power of electrically-powered process tasks, local power converters, and the local power grid. As an illustrative example, we study the multi-step copper production. We find a large achievable range of reactive power provision without compromising production volume or operating cost. Furthermore, we demonstrate how reactive power could be provided as an ancillary service by following a signal. Our results show that penalties or additional investment in compensation devices for power factor correction can be avoided through reactive power control of local power converters. Moreover, we demonstrate that industrial processes with sufficient capacity can alleviate voltage problems in transmission grids. Our work therefore lays the groundwork towards determining the reactive power scheduling potential of power-intensive production processes, and showcases its potential support for the voltage stability of future power grids.

Classification:

Contributing Institute(s):
  1. Modellierung von Energiesystemen (ICE-1)
Research Program(s):
  1. 1121 - Digitalization and Systems Technology for Flexibility Solutions (POF4-112) (POF4-112)
  2. 1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112) (POF4-112)

Database coverage:
Medline ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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 Datensatz erzeugt am 2026-02-10, letzte Änderung am 2026-02-11



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