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In the Paris subway system, stations represent about one-third of the overall energy consumption. Within stations, ventilation is among the top consuming devices; it is operated at maximum airflow all day long, for air quality reasons. In this paper, we present a concept of energy system that displays comparable air quality while consuming much less energy. The system comprises a battery that makes it possible to recover the trains braking energy, arriving under the form of erratic and strong peaks. We propose an energy management system that, at short time scale, controls energy flows and ventilation airflow. By using proper optimization algorithms, we manage to match supply with demand, while minimizing energy daily costs. For this purpose, we have designed algorithms that take into account the braking variability. They are based on the so-called stochastic dynamic programming (SDP) mathematical framework. We fairly compare SDP-based algorithms with the widespread model predictive control (MPC) ones. First, both SDP and MPC yield energy/money operating savings of the order of one-third, compared to the current management without battery. Second, depending on the specific design, we observe that SDP outperforms MPC by a few percent, with an easier online numerical implementation. [ABSTRACT FROM AUTHOR]

One of the measures for saving energy is the implementation of control strategies that reduce energy consumption during the machine idle periods. This paper proposes a framework that integrates different control policies for switching the machine off when the production is not critical, and on when the part flow has to be resumed. A general policy is formalized by modeling explicitly the power consumed in each system state. With this policy, the service can be resumed according to time threshold and when N parts have accumulated in the buffer. The behavior of the control strategy under different scenarios is numerically evaluated. Numerical results are based on data acquired with dedicated experimental measurements on a real machining center. A comparison with the common practice in manufacturing and with control policies that do not consider buffer information is also reported. [ABSTRACT FROM AUTHOR]