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Model predictive control (MPC) has been successfully applied to many transportation systems. For the control of overhead cranes, existing MPC approaches mainly focus on improving the regulation performance, such as tracking error or steady-state error. In this paper, energy efficiency as well as safety is newly considered in our proposed MPC approach. Based on the system model designed, the MPC approach is applied to minimize an objective function that is formulated as the integration of energy consumption and swing angle. In our approach, promising results in terms of low energy consumption and small swing angle can be found, whilst the solutions obtained can satisfy all practical constraints. Our test results indicate that the MPC approach can ensure stability and robustness of improving energy efficiency and safety.

In this paper, an energy dispatch model that satisfies the load demand, taking into account the intermittent nature of the solar and wind energy sources and variations in demand, is presented for a solar photovoltaic-wind-diesel hybrid power supply system. Model predictive control techniques are applied in the management and control of such a power supply system. The emphasis in this work is on the co-ordinated management of energy flow from the battery, wind, photovoltaic and diesel generators when the system is subject to disturbances. The results show that the advantages of the approach become apparent in its capability to attenuate and its robustness against uncertainties and external disturbances. When compared with the open loop model, the closed-loop model is shown to be more superior owing to its ability to predict future system behavior and compute appropriate corrective control actions required to meet variations in demand and radiation. Diesel consumption is generally shown to be more in winter than in summer. This work thus presents a more practical solution to the energy dispatch problem. Keywords: energy management, disturbance, intermittent nature, hybrid energy system, optimization scheme

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