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Home refrigerators produce a substantial part of the annual power consumption in an average household. To further improve the efficiency of these devices, new intelligent control solutions are required. These solutions necessitate the behaviour modeling of the refrigerators.We seek models with as simple structure as possible, since future intelligent controllers may use such models in real time, thus their evaluation must be feasible even on simple microcontrollers. We investigate various dynamic models to describe the behavior of the refrigerator, i.e. the cool-down and warm-up phases.For model parameter identification real data was collected from a real home refrigerator. Data processing, modeling and the parameter identification were performed in MATLAB environment.

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A Coloured Petri Net (CPN) based method for Programmable Logic Controller (PLC) program validation is proposed in this paper. It uses a simple fixed net structure and does not require the creation of different Petri Nets for every new PLC program. The base of the method is the so-called technology description and operation state table used in engineering practice. The CPN simulates the operation of the PLC and compares the resulted values to the desired ones. In the case of a difference it indicates the existence of an error. The method is capable of automatic program validation and safety analysis, which is demonstrated through the example of an oil tank system.

As a step towards sustainable energy management systems, energy providers use various demand side management techniques to reduce fluctuations in consumer energy demand. Dynamic pricing schemes encourage consumers to shift their energy usage patterns from peak hours towards off-peak periods, but here usually the active participation of consumers is anticipated. Smart household devices, which can autonomously shift their time of operation, can efficiently support such demand side management techniques. In this paper an adaptive model-based control scheme is proposed to create intelligent cost-aware household appliances, which can change their behaviour to minimize the cost of consumed energy and at the same time provide the required quality of service. The controller utilizes the dynamically changing energy price list, published ahead by the energy provider, thus it cooperatively supports demand side management. The proposed methods are evaluated in a case study, utilizing a household refrigerator. The proposed adaptive model predictive controller can save 5-10% of the energy bill, according to simulation results.