Timm Weitzel

Energy management for stationary electric energy storage systems: A systematic literature review

Electric Energy Storage Systems (EESS) have received an increased attention in recent years due to their important role in an active management of energy supply systems. Fueled by the increasing shares of intermittent Renewable Energy Sources (RES) in todays energy supply, balancing energy demand and energy supply over time becomes more and more challenging. EESS are recognized as a key technology to overcome this challenge by storing energy and converting it back when needed. Even though some EESS solutions are already available on the market, EESS suffer from technical limitations and entail high investment costs. Energy management is responsible for managing the operations of EESS and the interactions with the surrounding systems. An optimal energy management is an important precondition to ensure economic viability of EESS.

More applicable environmental scanning systems leveraging modern information systems

With Ansoff’s article about weak signals as a flagship example, a substantial body of knowledge about environmental scanning systems exists. However, these concepts often go unused in practice. The 2008/2009 economic crisis provided a strong, ongoing impulse for redesigning such information systems (IS). This article develops six guidelines for the conceptual design of environmental scanning systems that are more applicable than those specified by previous research. We start with literature research, which reveals three gaps in existing approaches. Then we develop design guidelines to fill these gaps with the help of “modern” IS. To address the lack of sound requirements analysis, our first design principle proposes 360-degree environmental scanning systems for executives and suggests how to select the most important scanning areas. Three further findings cover weaknesses in the IS model perspective, focusing on more effective implications of weak signals. In terms of method, we propose incorporating scanning results more closely into executives’ decision-making processes. Applying the design guidelines at a raw materials and engineering company, we arrive at a prototype we call the “corporate radar.” It includes an IS-based tree with economic value added at risk on top. The resulting lessons learned help to evaluate our findings and the research method presented here, as well provide concrete starting points for future research.

Scheduling a Storage-Augmented Discrete Production Facility under Incentive-based Demand Response.

Demand response (DR) is considered as one of the most important measures for balancing energy supply and demand in the smart grid paradigm. Incentive-based programs, one manifestation of DR, contribute to short-term system stability and prevent critical periods when system stability is at risk by enabling the system operator (SO) to directly change total energy demand. The fact that a third party would be empowered to interfere with internal operations is, however, also one of the major drawbacks of DR that prevents especially industrial consumers from participating with full capacity in such programs. This paper considers an alternative Incentive-based program with application to a discrete manufacturing facility where load reduction curves (LRCs) are generated a priori outlining the potential load reduction in the DR period. The SO uses the LRC to determine the desired level of load reduction for critical periods. To illustrate the generation of the LRC, this paper builds on a flexible flow shop (FFS) formulation for a discrete manufacturing facility and presents a model that includes multiple machine modes and product- and machine-specific energy consumption trajectories. Based on the FFS, a procedure is developed to generate the LRC. The paper also investigates the potential of including a battery energy storage system (BESS) into the production facility and illustrates the effects of the BESS on the LRC.