Predictive Control methods for Building Control and Demand Response
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Existing methods for demand response either assume direct control of appliances by supplier, or assume that consumers adapt their load by reacting to pricing signals. The former are intrusive and might not scale well; the latter expose consumers to price v ...
We propose an alternative approach, based on ``service curves", which uses the following two ingredients. (1) The rate at which a consumer may draw power from the grid may be controlled by real time signals. Typical concerned devices would be heating syste ...
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In this work, we investigated the interplay and the influence of lighting and blind control models on the heating, cooling, and lighting energy loads of an office room. By including different stochastic models for occupancy and appliances, we built a compl ...
Increasing heat dissipation density is becoming a limiting factor in air-cooled data centers. The main control objective in data center thermal management is to keep the temperature of all the data processing equipment below a certain threshold and at the ...
The present paper addresses the use of a Windows™ DLL to simulate the real code of a DSP for faster development time and advanced testing, especially in high power systems. The development of power system control usually starts with simulations and the dev ...
Robust state-feedback model predictive control (MPC) of discrete-time periodic affine systems is considered. States and inputs are subject to periodically time-dependent, hard, convex, polyhedral constraints. Disturbances are additive, bounded and subject ...
A predictive optimal control system for micro-cogeneration in domestic applications has been developed. This system aims at integrating stochastic inhabitant behavior and meteorological conditions as well as modelling imprecisions, while defining operation ...
A nonlinear model-predictive hierarchical control approach is presented for coordinated ramp metering of freeway networks. The utilized hierarchical structure consists of three layers: the estimation/prediction layer, the optimization layer and the direct ...