Modular building energy management strategy based on a three-level hierarchical model predictive control is proposed in the paper. Building zones, central medium conditioning and microgrid subsystems are controlled independently by individual linear and nonlinear model predictive controllers, and further integrated together as levels of hierarchical coordination control structure based on price-consumption information exchange. The three-level coordination provides a holistic energy management strategy and enables significant demand response ancillary services for buildings as prosumers, while retaining the independence of required expertise in very different building subsystems. The approach is applied for daily operation scheduling of a full-scale building consisting of 248 offices. Models of building subsystems are obtained by identification procedures on measurement data. Compared to rule-based control, detailed realistic simulations show that the overall building operation cost for typical days in summer is reduced by 9-12% for level-by-level energy-optimal and by 15-24% for price-optimal, coordinated operation. The application of predictive control in the proposed way also improves the indoor comfort substantially.
Complex mechanical systems, such as wind turbines, often include safety constraints which should not be violated in order to avoid high risk of structural damage. Adherence to the safety constraints is ensured with a well-designed operating envelope protection. In this paper, we present an invariant set-based protection concept with the application to the wind turbine overspeed protection. The approach is model-based and operates without wind-preview measurements. Instead, it is based on the evolution model of the wind disturbance in the worst-case scenario manner. Accurate system estimation utilizing the blade root in-plane measurement is proposed, along with the efficient algorithm for the hard real-time operation of the protection system. The overspeed protection system is validated in extensive simulations on extreme turbulent wind, performed in GH Bladed. The results show the effectiveness of the proposed concept compared with the baseline controller performance.
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