This paper presents a novel approach for an energy control of a DC microgrid. It combines decentralized grid management and energy management. For this purpose, the conventional voltage droop curves are extended to a characteristic diagram with electricity costs as a further dimension. The support points of these characteristic diagrams are then optimized with a particle swarm optimizer. The target criterion of this optimization is a monetary cost function, that takes several effects, such as depth of discharge, on the operating costs into account. The optimized characteristic diagrams are designed more robust by a sensitivity analysis. The proposed method has been tested successfully in simulations and experiment and was always more cost-efficient than the initial characteristics diagram. Index Terms-energy control, DC microgrid, characteristic diagrams, voltage droop control This is the author's version of an article that has been published in the ICIT 2019 proceedings.
A new approach for more energy efficient industrial production processes are smart industrial direct current (DC) microgrids with one or more connections to the alternative current (AC) grid. The advantage of the DC-technology is an easier integration of renewable energies sources and energy storage systems (ESS). Different applications for ESS are possible, for instance an uninterruptible power supply (UPS) for a DC microgrid. Within this paper, a new handling concept for a mains supply failure (e.g. a blackout of the supplying AC grid) with a droop curve control is introduced. In this approach, the droop curve controlling the ESS is adapted, depending on the ESS' state of charge (SoC), which results in a droop curve with a hysteresis. This concept realizes the charging of the ESS only with recuperation energy, that occurs in the DC microgrid during the production process. Thus, all recuperation energy will be kept in the DC microgrid and a transformation of the energy in AC or an energy loss through braking resistors will be avoided. Furthermore, no additional energy is needed to charge the ESS. This increases the energy efficiency of the entire production process. The concept was verified in simulation and validated in experiment and it has shown a DC voltage deviation of less than two percent.
This paper presents an approach to significantly improve modeling accuracy for the power and energy demands of industrial robots. This is achieved by taking the temperature dependency of the joint's viscuous friction parameters into account. While the connection is commonly known, it is usually neglected in state-of-the-art energy consumption models for industrial robots. This paper shows that a consideration of temperature-dependent friction provides significant improvement of energy modeling accuracy. The approach is validated on a test rig with a KUKA KR 16 robotic manipulator. Measurements show that the grid energy consumption modeling error can be reduced from up to 45 % to approx. 5 % over the whole spectrum of operating temperatures.
Reducing the energy consumption is a major concern in industrial production systems. One approach is recuperating the braking energy of robot axes. Ideally, their acceleration and deceleration phases should be synchronized so that the braking energy of one axis can be reused directly to accelerate another. This requires a detailed alignment of the axes' trajectories, but also a careful design of the overall discrete control. Finding an optimal control strategy manually, however, is difficult, as also many functional and safety requirements must be considered. We therefore propose an automated methodology that consists of three parts: (1) A scenario-based language to flexibly specify the discrete production system behavior, (2) an automated procedure to synthesize optimal control strategies from such specifications, including PLC code generation, and (3) a procedure for the detailed trajectory optimization. We describe the methodology, focusing on parts (1) and (2) in this paper, and present tool support and evaluation results.
This paper presents a new approach to estimate the benefit of a energy storage for certain robots. This method can be used directly in the planning phase of production. First, a robot model is developed including the DC grid coupling of the individual drives. This model is validated by several measurements of the absorbed power, brake power and DC grid voltage in a real car body shop. In a next step, the model is used to estimate the potential of an energy storage system for robots in a specific production. The estimation was successfully validated with and without energy storage. In the experimental evaluation an energy saving of 10 % was achieved.
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