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Distribution network scheduling (DNS) is the basis for distribution network management, which is computed in a periodical way via solving the formulated mixed-integer programming (MIP). To achieve the online scheduling, a provably robust learn-to-optimize approach for online DNS is proposed in this paper, whose key lies in the transformation of the MIP-based DNS into the simple linear program problem with a much faster solving time. It formulates the parametric DNS model to construct the offline training dataset and then proposes the provably robust learning approach to learn the integer variables of MIP. The proposed learning approach is adversarial to minor perturbation of input scenario. After training, the learning model can predict the integer variables to achieve online scheduling. Case study verifies the acceleration effectiveness for online DNS.

Distribution network scheduling (DNS) is the basis for distribution network management, which is computed in a periodical way via solving the formulated mixed-integer programming (MIP). To achieve the online scheduling, a provably robust learn-to-optimize approach for online DNS is proposed in this paper, whose key lies in the transformation of the MIP-based DNS into the simple linear program problem with a much faster solving time. It formulates the parametric DNS model to construct the offline training dataset and then proposes the provably robust learning approach to learn the integer variables of MIP. The proposed learning approach is adversarial to minor perturbation of input scenario. After training, the learning model can predict the integer variables to achieve online scheduling. Case study verifies the acceleration effectiveness for online DNS.

The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

PHPs (pulsating heat pipes) are widely used as an efficient heat transfer element in equipment thermal management and waste heat recovery due to their flexibility. The purpose of this study was to design a heat transfer device that utilizes an asymmetric pulsating heat pipe structure by adjusting the lengths of selected pipes within the entire circulation pipeline. In the experiment, a constant temperature water bath was used as the heat source, with heat dissipated in the condensing section via natural convection. An infrared thermal imager was used to record the temperature of the condensing section, and the local wall temperature distribution was measured in different channels of the condensing section. Based on an in-depth analysis of the wavelet frequency, the following research conclusions are drawn: Firstly, as the heat source temperature increases, the start-up time of the pulsating heat pipe is shortened, the operating state changes from start–stop–start to stable and continuous oscillation, and the oscillation mode changes from high amplitude and low frequency to low amplitude and high frequency. These changes are especially pronounced when the heat source temperature is 80 °C, which is when the thermal resistance reaches its lowest value of 0.0074 K/W, and the equivalent thermal conductivity reaches its highest value of 666.29 W/(m·K). Secondly, the flow and oscillation of the working fluid can be effectively promoted by appropriately shortening the length of the condensing section of the pulsating heat pipes or the heat transfer distance between the evaporation and condensing sections. Third, under a low-temperature heat source, the oscillation frequency of each channel of a pulsating heat pipe is found to be low based on wavelet analysis. However, as the heat source temperature increases, the energy content of the temperature signal of the working fluid in each channel changes from a low- to a high-frequency value, gradually converging to the same characteristic frequency. At this point, the working fluid in the pipes no longer flows randomly in multiple directions but rather in a single direction. Finally, we determined that the maximum oscillation frequency of working fluid in a PHP is around 0.7 HZ when using the water bath heating method.

PHPs (pulsating heat pipes) are widely used as an efficient heat transfer element in equipment thermal management and waste heat recovery due to their flexibility. The purpose of this study was to design a heat transfer device that utilizes an asymmetric pulsating heat pipe structure by adjusting the lengths of selected pipes within the entire circulation pipeline. In the experiment, a constant temperature water bath was used as the heat source, with heat dissipated in the condensing section via natural convection. An infrared thermal imager was used to record the temperature of the condensing section, and the local wall temperature distribution was measured in different channels of the condensing section. Based on an in-depth analysis of the wavelet frequency, the following research conclusions are drawn: Firstly, as the heat source temperature increases, the start-up time of the pulsating heat pipe is shortened, the operating state changes from start–stop–start to stable and continuous oscillation, and the oscillation mode changes from high amplitude and low frequency to low amplitude and high frequency. These changes are especially pronounced when the heat source temperature is 80 °C, which is when the thermal resistance reaches its lowest value of 0.0074 K/W, and the equivalent thermal conductivity reaches its highest value of 666.29 W/(m·K). Secondly, the flow and oscillation of the working fluid can be effectively promoted by appropriately shortening the length of the condensing section of the pulsating heat pipes or the heat transfer distance between the evaporation and condensing sections. Third, under a low-temperature heat source, the oscillation frequency of each channel of a pulsating heat pipe is found to be low based on wavelet analysis. However, as the heat source temperature increases, the energy content of the temperature signal of the working fluid in each channel changes from a low- to a high-frequency value, gradually converging to the same characteristic frequency. At this point, the working fluid in the pipes no longer flows randomly in multiple directions but rather in a single direction. Finally, we determined that the maximum oscillation frequency of working fluid in a PHP is around 0.7 HZ when using the water bath heating method.

Geological energy has a long history in China [...]

Geological energy has a long history in China [...]