An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system w...An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day’s cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.展开更多
In the last few decades, in the world and also in the European Union, considerable resources had been invested in the rapid development of renewable energy sources and distributed generation in general. At the same ti...In the last few decades, in the world and also in the European Union, considerable resources had been invested in the rapid development of renewable energy sources and distributed generation in general. At the same time, power consumption is continuously increasing, and consumers are becoming more complex, which ultimately requires new investments in the distribution network. Concept of smart grids is generally accepted as a possible solution. Smart grid is a concept with many elements, where monitoring and control of every element in the chain of production, transmission, distribution and final consumption enable much more efficient delivery and use of electricity. One of the elements of smart grid efficiency is the ability of real-time demand-supply balancing. This balancing is carried out by monitoring of consumption and redistribution of electricity among individual end users, according to their needs. The aim of this paper is creating algorithm for real-time load management using power measurements. Algorithm for real-time load management at the ETFOS （Faculty of Electrical Engineering in Osijek）, Croatia is created based on measurements of photovoltaic power plant production, the power consumption of air conditioning system and the faculty building total electricity consumption. Expected result of real-time re-dispatching of air conditioners consumption, depending on the level of electricity production in photovoltaic power plant is decreasing peak demand of the faculty.展开更多
The modal analysis of piping system in air conditioner (AC) outdoor unit is essential to investigate the vibration properties of the system. In view of the growing significance of numerical finite element (FE) model f...The modal analysis of piping system in air conditioner (AC) outdoor unit is essential to investigate the vibration properties of the system. In view of the growing significance of numerical finite element (FE) model for vibration behaviour prediction, the AC piping elastic end support characterization has been explored. The axial and radial stiffness variables (ka, kr1, kr2) of the compressor-piping mounting are obtained and represented by dynamic stiffness of compressor grommet. They are obtained from dynamic load deflection test based on compressor operating condition such as excitation frequency and amplitude. The unknown stiffness variables of the other tube end (chassis-piping mounting) are determined by parameter fine tuning. An experimental modal analysis using impact hammer test has also been employed to determine the vibration properties such as natural frequencies, mode shapes and damping ratio of the piping structures. The modal parameters acquisition using SCADAS mobile acquisition system and LMS Impact Testing software is compared with the corresponding simulated modal properties using Abaqus. Most of the simulated natural frequencies achieve good correlation with the measured frequencies and it is reasonably a good prediction model to predict vibration behaviour of AC piping structures.展开更多
文摘An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day’s cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.
文摘In the last few decades, in the world and also in the European Union, considerable resources had been invested in the rapid development of renewable energy sources and distributed generation in general. At the same time, power consumption is continuously increasing, and consumers are becoming more complex, which ultimately requires new investments in the distribution network. Concept of smart grids is generally accepted as a possible solution. Smart grid is a concept with many elements, where monitoring and control of every element in the chain of production, transmission, distribution and final consumption enable much more efficient delivery and use of electricity. One of the elements of smart grid efficiency is the ability of real-time demand-supply balancing. This balancing is carried out by monitoring of consumption and redistribution of electricity among individual end users, according to their needs. The aim of this paper is creating algorithm for real-time load management using power measurements. Algorithm for real-time load management at the ETFOS （Faculty of Electrical Engineering in Osijek）, Croatia is created based on measurements of photovoltaic power plant production, the power consumption of air conditioning system and the faculty building total electricity consumption. Expected result of real-time re-dispatching of air conditioners consumption, depending on the level of electricity production in photovoltaic power plant is decreasing peak demand of the faculty.
文摘The modal analysis of piping system in air conditioner (AC) outdoor unit is essential to investigate the vibration properties of the system. In view of the growing significance of numerical finite element (FE) model for vibration behaviour prediction, the AC piping elastic end support characterization has been explored. The axial and radial stiffness variables (ka, kr1, kr2) of the compressor-piping mounting are obtained and represented by dynamic stiffness of compressor grommet. They are obtained from dynamic load deflection test based on compressor operating condition such as excitation frequency and amplitude. The unknown stiffness variables of the other tube end (chassis-piping mounting) are determined by parameter fine tuning. An experimental modal analysis using impact hammer test has also been employed to determine the vibration properties such as natural frequencies, mode shapes and damping ratio of the piping structures. The modal parameters acquisition using SCADAS mobile acquisition system and LMS Impact Testing software is compared with the corresponding simulated modal properties using Abaqus. Most of the simulated natural frequencies achieve good correlation with the measured frequencies and it is reasonably a good prediction model to predict vibration behaviour of AC piping structures.
