The prediction of the heating and cooling loads of a building is an essential aspect in studies involving the analysis of energy consumption in buildings. An accurate estimation of heating and cooling load leads...The prediction of the heating and cooling loads of a building is an essential aspect in studies involving the analysis of energy consumption in buildings. An accurate estimation of heating and cooling load leads to better management of energy related tasks and progressing towards an energy efficient building. With increasing global energy demands and buildings being major energy consuming entities, there is renewed interest in studying the energy performance of buildings. Alternative technologies like Artificial Intelligence (AI) techniques are being widely used in energy studies involving buildings. This paper presents a review of research in the area of forecasting the heating and cooling load of buildings using AI techniques. The results discussed in this paper demonstrate the use of AI techniques in the estimation of the thermal loads of buildings. An accurate prediction of the heating and cooling loads of buildings is necessary for forecasting the energy expenditure in buildings. It can also help in the design and construction of energy efficient buildings.展开更多
Voltage source converter(VSC) based high voltage direct current(HVDC) transmission is most suited for the wind farm as it allows flexibility for reactive power control in multi-terminal transmission lines and transmit...Voltage source converter(VSC) based high voltage direct current(HVDC) transmission is most suited for the wind farm as it allows flexibility for reactive power control in multi-terminal transmission lines and transmits low power over smaller distance. In this work, a new method has been proposed to detect the fault, identify the section of faults and classify the pole of the fault in DC transmission lines fed from onshore wind farm. In the proposed scheme, voltage signal from rectifier end terminal is extracted with sampling frequency of 1 k Hz given as the input to the detection, classification and section discrimi-nation module. In this work, severe AC faults are also considered for section discrimination. Proposed method uses fuzzy inference system(FIS) to carry out all relaying task. The reach setting of the relay is 99.9% of the transmission line. Besides, the protection covers and discriminates the grounding fault with fault resistance up to 300 Ω.Considering the results of the proposed method, it can beused effectively in real power network.展开更多
文摘The prediction of the heating and cooling loads of a building is an essential aspect in studies involving the analysis of energy consumption in buildings. An accurate estimation of heating and cooling load leads to better management of energy related tasks and progressing towards an energy efficient building. With increasing global energy demands and buildings being major energy consuming entities, there is renewed interest in studying the energy performance of buildings. Alternative technologies like Artificial Intelligence (AI) techniques are being widely used in energy studies involving buildings. This paper presents a review of research in the area of forecasting the heating and cooling load of buildings using AI techniques. The results discussed in this paper demonstrate the use of AI techniques in the estimation of the thermal loads of buildings. An accurate prediction of the heating and cooling loads of buildings is necessary for forecasting the energy expenditure in buildings. It can also help in the design and construction of energy efficient buildings.
文摘Voltage source converter(VSC) based high voltage direct current(HVDC) transmission is most suited for the wind farm as it allows flexibility for reactive power control in multi-terminal transmission lines and transmits low power over smaller distance. In this work, a new method has been proposed to detect the fault, identify the section of faults and classify the pole of the fault in DC transmission lines fed from onshore wind farm. In the proposed scheme, voltage signal from rectifier end terminal is extracted with sampling frequency of 1 k Hz given as the input to the detection, classification and section discrimi-nation module. In this work, severe AC faults are also considered for section discrimination. Proposed method uses fuzzy inference system(FIS) to carry out all relaying task. The reach setting of the relay is 99.9% of the transmission line. Besides, the protection covers and discriminates the grounding fault with fault resistance up to 300 Ω.Considering the results of the proposed method, it can beused effectively in real power network.
