Embedding reservoirs in industrial models to exploit their flexibility

Abstract

In the context of energy transition, industrial plants that heavily rely on electricity face more and more price volatility. To continue operating in these conditions, the directors become continually more willing to increase their flexibility, i.e. their ability to react to price fluctuations. This work proposes an intuitive methodology to mathematically model electro-intensive processes in order to assess their flexibility potential. To this end, we introduce the notion of reservoir, a storage of either material or energy, that allows models based on this paradigm to have interpretations close to the physics of the processes. The design of the reservoir methodology has three distinct goals: (i) to be easy and quick to build by an energy-sector consultant; (ii) to be effortlessly converted into mixed-integer linear or nonlinear programs; (iii) to be straightforward to understand by nontechnical people, thanks to their graphic nature. We apply this methodology to two industrial case studies, namely an induction furnace (linear model) and an industrial cooling installation (nonlinear model), where we can achieve significant cost savings. In both cases, the models can be quickly written using our method and solved by appropriate solver technologies.

Demand-Side Flexibility in Power Systems: A Survey of Residential, Industrial, Commercial, and Agricultural Sectors

“…Moreover, the raw and cement mills can provide power flexibility at short advance notice without causing an interruption to the production line. In the steel, metal, and aluminum industries, the operation of smelting pots can be scheduled during off-peak hours [16]. Generally, the smelting pots are operated in discrete processes; therefore, the next round of pots' operation can be shifted or delayed in response to power system requirements.…”