In this article, we present a new descriptive model for industrial flexibility with respect to power consumption. The advancing digitization in the energy sector opens up new possibilities for utilizing and automatizing the marketing of flexibility potentials and therefore facilitates a more advanced energy management. This requires a standardized description and modeling of power-related flexibility. The data model in this work has been developed in close collaboration with several partners from different industries in the context of a major German research project. A suitable set of key figures allows for also describing complex production processes that exhibit interdependencies and storage-like properties. The data model can be applied to other areas as well, e.g., power plants, plug-in electric vehicles, or power-related flexibility of households.

The increasing share of volatile, renewable energy sources rises the demand for consumers who can shift their electrical power demand in time. In theory, the industrial sector offers great potential here, as it accounts for a large proportion of electricity demand. However, the heterogeneous structure of facilities in factories and the concerns of operators regarding data security and process control often prevent the implementation of demand side management measures in this sector. In order to counteract these obstacles, this paper presents a general mathematical framework for modelling and evaluating different types of inherent energy storages (IES) which typically can be found in industrial production systems. The method can be used to calculate the flexibility potential of the IES in a factory with focus on hysteresis-controlled devices and make the potential visible and usable for power grid stabilization. The method is applied in a typical production line from metalworking industry to provide live monitoring of the current flexibility potential of selected devices.

The increasing share of volatile, renewable energies, such as wind and solar power, leads to challenges in the stabilization of power grids and requires more flexibility in future energy systems. This article addresses the flexibilization of the consumer side and presents a simulation-based method for the technical and economic investigation of energy flexibility measures in industrial steam supply systems. The marketing of three different energy-flexibility measures—bivalence, inherent energy storage and adjusting process parameters—both at the spot market and at the balancing power market, are investigated from a technical as well as an economic point of view. Furthermore, the simulation-based methodology also considers pressure and temperature fluctuation induced by energy-flexibility measures. First, different energy-flexibility measures for industrial steam supply systems are introduced. Then, the physical modeling of the steam generation, distribution, and consumption as well as measure-specific control strategies will be discussed. Finally, the methodology is applied to a steam supply system of a chemical company. It is shown that the investigated industrial steam supply system shows energy-flexibility potentials up to 10 MW at peak and an annual average of 5.6 MW, which highly depend on consumer behavior and flexibility requirements.

In the context of the ongoing climate change and increasingly strict climate goals of the European Green Deal, industry faces a growing challenge to decrease its high demand for electrical energy and its greenhouse gas emissions. Demand-Side Integration measures have a great potential to reduce the greenhouse gas emissions of the industrial sector. However, there is still no definition and consistent characterising terms for Industrial Demand-Side Integration. The lack of clarity in concepts and definitions may impose hurdles in the transfer of results and methodologies from research activities and thus, in the implementation of measures in the industry. Furthermore, the economic value of implementing these measures is often unclear but of high relevance to industrial consumers. This paper proposes a comprehensive Industrial Demand-Side Integration definition and a methodology to classify and characterise its measures. The methodology is aimed at helping industrial consumers decide which measures can be implemented in their specific setting and how these measures can be monetised. The methodology is validated by applying it to eight relevant use cases in the ETA Research Factory.