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Reduction of electricity consumption peaks and optimization problems induced on the demand side

Authors
  • Desdouits, Chloé
Publication Date
Feb 10, 2017
Source
HAL-UPMC
Keywords
Language
English
License
Unknown
External links

Abstract

While concerns about global warming have never been so important, one of its first causes: global electricity consumption, is still growing. One way to stem the phenomenon could be to better balance demand and production, in order to switch on less big production groups and to allow the integration of more renewable production sources. The new paradigm of electricity market incites customers to reduce their electricity consumption peak and to shift their consumption when the demand is lower, by introducing economical incentives. Thus, new optimization algorithms and methodologies are needed at the customers side to optimize power usage over time. Schneider Electric proposes, through the Arrowhead European project, to study three application use-cases: an elevator with multiple electricity sources, a manufac- turing plant, and a drinking water network. For each of these use-cases, a methodology to optimize power consumption peaks (sometimes through an electricity cost function) is given, as well as optimization algorithms. For the multisource elevator case, two coupled controllers are proposed: one at the strategic level solving a linear problem, the other one rule-based at the tactical level. For the manufacturing plant, the methodology we used to monitor, build energy models, and finally optimize is explained. Furthermore, three linear formulations are given, as well as a simple local search procedure and a naive constraint satisfaction formulation to handle the NP-hard scheduling problem. For the water network use-case, a quadratically constrained formulation is used to compare optimized pumping plans with the Business As Usual tactic. The methods proposed bring between 1.5% to 114% savings on the energy bill, depending on the context. Moreover, they allow electricity consumers to participate in the demand-response market. Finally, the knowledge extracted from our three use-cases is summarized, and guide- lines are given to optimize the electricity bill of any electricity consumer system.

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