Optimal design of a borehole heat exchanger, as the outer part of a ground source heat pump heating system, requires information on the thermal properties of the soil. Those data, the effective thermal conductivity of the soil λeff and the average temperature of the soil T0, enable us to determine the necessary number and depth of boreholes. The determination of thermal conductivity of the soil in laboratory experiments does not usually coincide with the data under in-situ conditions. Therefore, an in-situ method of experimental determination of these parameters, the so-called thermal response test, is presented in this paper. In addition to the description of the experimental procedure and installation overview, the paper describes methods based on theory and presents their basic limitations, through the presentation of experimental data. [Acknowledgment. This paper is made in a scope of the project TR 33047 “Intelligent climate control systems to achieve energy efficient regime in the complex conditions of exploitation” funded by the Ministry of Education and Science of the Republic of Serbia.
In this paper we present a conceptual solution of modular panel for measuring health parameters of the elderly. The conceptual solution was followed by a study that analyzed the design and evaluated interface of the system. Modular panel contains sensors, processing unit, and interface enabling data acquisition and communication between the user and the medical staff. Positioning of the panel within the residential unit was determined by the categories of actions which it should provide and functional areas of typical housing unit. Interface design is based on a specific type of users and is on the basis of the type of data that should be collected and displayed. Evaluation of interface is conducted by using two user groups, where the first is made up of people older than 60 years and represents the interest group of the study, while the second group consisted of people younger than 60 years as the control group. The collected data were analyzed and the results indicate that the simplicity of the interface suits good to the users. Elderly users need more time to conduct certain commands, but most of them understood interface completely. The limitations of the system, such as lack of information provided for the users, will be considered in the future work.
In this paper a radiator heating system of a building is considered. For the purpose of the heating system optimization, a mathematical model of the system is developed. The linear quadratic algorithm with integral action is proposed and analyzed. This solution has proven to be expensive. Further analysis of the model is done and a reduction of the order of the system is proposed. An inverse-based controller design approach for minimum-phase first order system is used to provide realizable controller in the form of proportional integral controller. Optimal parameters of the control algorithm parameters have been chosen by integral of time absolute error criterion, and also by metaheuristic optimization. According to the real heating demand, a simulation of the plant is performed. Proposed controllers were tested by numerical simulation for a typical winter day for geographical region of the building. It is shown that advanced performance can be achieved with optimized control systems, and that by controller optimization a significant reduction of the energy consumption is obtained without losing the indoor comfort. This has also proved to be more economical solution.
In this paper a temperature control system for an automated educational classroom is optimized with several advanced computationally intelligent methods. Controller development and optimization has been based on developed and extensively tested mathematical and simulation model of the observed object. For the observed object cascade P-PI temperature controller has been designed and conventionally tuned. To improve performance and energy efficiency of the system, several metaheuristic optimizations of the controller have been attempted, namely genetic algorithm optimization, simulated annealing optimization, particle swarm optimization and ant colony optimization. Efficiency of the best results obtained with proposed computationally intelligent optimization methods has been compared with conventional controller tuning. Results presented in this paper demonstrate that heuristic optimization of advanced temperature controller can provide improved energy efficiency along with other performance improvements and improvements regarding equipment wear. Not only that presented methodology provides for determination and tuning of the core controller, but it also allows that advanced control concepts such as anti-windup controller gain are optimized simultaneously, which is of significant importance since interrelation of all control system parameters has important influence on the stability and performance of the system as a whole. Based on the results obtained, general conclusions are presented indicating that metaheuristic computationally intelligent optimization of heating, ventilation, and air conditioning control systems is a feasible concept with strong potential in providing improved performance, comfort and energy efficiency.
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