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This paper addresses the optimization of energy flows between electric drives in conveying systems. Thereby, load peaks and the feedback of electric energy into the grid are reduced. The approach is based on the solution of a mixed integer quadratic optimization problem which incorporates models for energy flows and energy consumption of the electric drives. Models for energy flows and energy consumption can be parametrized from sensor data. Besides, movement constraints such as start positions, end positions and time limits are taken into account. The solution of the optimization problem is accomplished in realtime by application of standard solvers. Experimental results show that the proposed methods allows recovering regenerative energy of electric drives as motoric power for other drives. Integration into material flow planning of an automated warehouse is straightforward so that an inexpensive and simply usuable way for power saving in intralogistics is presented

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This article addresses the automatic optimization of driving speeds in conveying systems. Electric drives in existing conveying systems are usually accelerated and decelerated according to predetermined movement profiles. Such an approach is inflexible for conveying applications with changing constraints and, in many cases, not optimal with respect to energy efficiency. In the present work, a method for automatic computation of energy efficient movement profiles is proposed. The proposed method is based on accurate models for electric drives and several types of conveying applications such as roll conveyors, belt conveyors and vertical conveyors. Furthermore, joint energy efficiency optimization for two drives, which are attached to an intermediate circuit, is investigated. Thereby, additional constraints on the energy flow between the drives are imposed in order to reduce load peaks and energy feedback into the grid. The resulting optimization problem is a mixed integer quadratic program (MIQP), which can be solved in a few milliseconds. Experimental results show that energy losses of electric drives are cut down by using the obtained non-trivial movement profiles instead of standard trapezoid movement profiles. The additional constraints on the energy flow between two drives lead to further significant improvements with respect to the overall energy losses.

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