Title:	Leveraging Industry Energy Flexibility to Enable Higher Shares of Renewable Energy in the Power System – an Experimental Case Study
Author(s):	A. Aamoume, J.S. da Costa Fernandes, R. Gasper, N. Hartmann, Y. Kenoussi, M. Schmidt, E. Schmitt
Keywords:	Energy Management, Digitalization, Energy systems modeling, Demand side flexibility, Optimization and control
Topic:	Energy Transition – Integration, Storage, Sustainability, Policy, Economics, Energy Poverty, Society
Subtopic:	Energy System Integration; Storage
Event:	8th World Conference on Photovoltaic Energy Conversion
Session:	5DV.2.16
Pages:	1600 - 1604
ISBN:	3-936338-86-8
Paper DOI:	10.4229/WCPEC-82022-5DV.2.16
Price:	0,00 EUR
Document(s):	paper

Abstract/Summary:

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One of the major challenges impeding the energy transition is the intermittency of solar and wind electricity generation due to their dependency on weather changes. The demand-side energy flexibility contributes considerably to mitigate the energy supply/demand imbalances resulting from external influences such as the weather. As one of the largest electricity consumers, the industrial enterprises present a high demand-side flexibility potential from their production processes and on-site energy assets. In this direction, methods are needed with a focus on enabling the energy flexibility and ensure an active participation of such enterprises in the electricity markets especially with variable prices of electricity. This paper presents a generic model library for an industrial enterprise implemented with optimal control for energy flexibility purposes. The components in the model library represent the typical technical units of an industrial enterprise on material, media, and energy flow levels with their operative constraints. A case study of a plastic manufacturing plant using the generic model library is also presented, in which the results of two simulation with different electricity prices are compared and the behavior of the model can be assessed. The results show that the model provides an optimal scheduling of the manufacturing system according to the variations in the electricity prices, and ensures an optimal control for utilities and energy systems needed for the production.