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
The study presents possibilities for reconstruction of electric power supply systems in Bulgarian Black Sea resorts and possibilities to use statistical methods in energy planning. The paper shows the use of classic s...The study presents possibilities for reconstruction of electric power supply systems in Bulgarian Black Sea resorts and possibilities to use statistical methods in energy planning. The paper shows the use of classic statistical methods in combination with advanced digital measurement systems in order to obtain the correlation dependencies, nature of energy consumption and opportunities for energy forecasting. The main purpose of the study is to obtain statistical dependencies of the nature of power consumption and correlations between electricity consumption and ambient temperature in order to improve the accuracy of energy planning. The analysis includes application of energy management systems for proper energy planning, improving economical efficiency and reducing power and energy losses.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The study presents possibilities for reconstruction of electric power supply systems in Bulgarian Black Sea resorts and possibilities to use statistical methods in energy planning. The paper shows the use of classic statistical methods in combination with advanced digital measurement systems in order to obtain the correlation dependencies, nature of energy consumption and opportunities for energy forecasting. The main purpose of the study is to obtain statistical dependencies of the nature of power consumption and correlations between electricity consumption and ambient temperature in order to improve the accuracy of energy planning. The analysis includes application of energy management systems for proper energy planning, improving economical efficiency and reducing power and energy losses.
