Dynamic Model Predictive Control for Load Sharing in Electric Power Plants for Ships

Abstract

The main contribution of this thesis is an investigation of model predictive control(MPC) for marine diesel electric power plants. Recommendations and new ideasfor further development are emphasized.The motivation of the thesis is to develop a controller for diesel electric power plantsthat can control the plant in a more efficient way. This includes reducing wear andtear, fuel consumption, and emissions. However, the safety aspect is always themost important factor and must be handled with care.The case plant to be studied is a diesel electrical power plant consisting of severaldiesel driven generators (genset). These gensets produce electrical power to servethe electrical demands on a marine vessel. The consumers can be propulsion units,heave compensators, drilling equipment, and hotel loads. These highly dynamicconsumers are large compared with the producers. This gives unwanted fluctuationof frequency. In some vessels this effect is so large that more gensets are requiredfor transients than for peak demands. This can be avoided with better controlstrategies.The controller developed in this thesis adjusts the local controllers on the dieselengines. The objective is to keep the genset at a given load sharing, while keepingthe frequency within rules and regulations. In addition is the plant controlled to astate where a single point failure does not lead to blackout.Blackout is prevented by calculating a failure case in addition to the normal case.The failure case may be a disconnection of the largest genset on the power bussegment. The case is calculated in the controller to make sure that if the caseoccurs the plant is able to handle the failure without a blackout. A normal case,where everything goes as normal, is calculated to optimize the current operation.The controller is verified by simulation done in MATLAB/Simulink. Theimplemented controller performs well during all of the simulated cases. However,the predictions made by the controller are in some cases conservative. This is dueto the choice of the fuel rate constraints. Lastly, suggestions for how to improvethe performance of the controller are included. The most important suggestionsare to include a model of the turbocharger in the control plant model and toinclude more failure cases.