• Energy Research

Abstract In a passive nuclear plant, the main control room must provide self-support functions for 72 h after an accident occurs. In this isolation mode, the heat generated by indoor occupants and equipment should be removed by using concrete walls that are 610 mm thick, and the finned ceiling made of concrete should maintain thermal habitability. However, the finned ceiling design has not been studied in normal buildings, and the cooling storage effect of plate-shaped fins is usually ignored during the design phase. In this study, a novel parametric resistance–capacitance thermal network is proposed to simulate the thermal performance of different fin-plate layout forms in the case of an accident. An experiment was conducted on a 1200 mm × 1200 mm × 610 mm fin-concrete module for 72 h to validate the model under constant air temperature conditions. Based on the model, multi-objective optimization was conducted to obtain optimal solution sets by using a radial basis function approximation model. The results show that the optimal performance indicators can be classified into unsteady and quasi-steady states, in which the dominant factors for heat transfer include the heat transfer area and the thickness of the finned plate, respectively. Further, the optimal solution sets for different convection and heating conditions obtained through an optimization process are used to design a fin layout based on actual temperature control demands and cooling storage.

Abstract Energy-conservation potential in the air-condition water system for subway stations is huge due to its conservative design method. Also, for operation strategy of such systems, the operation modes are formulated with the fixed schedule. This paper presents a data-based optimization method to obtain optimal parameters of the system for feedforward control . The data mining models are established by using the data from energy consumption platform of the refrigerating system. The study utilized the box-plot method, kNN algorithm and k-means algorithm to process and repair original data. Then Artificial Neural Network (ANN) model is adopted to developed the forecasting model to assess load, performance and energy consumption of the system. The input features of the models are determined by the existed models and clustering analysis. The optimal parameters under the conditions of different load-ratio range and ambient thermal environments are calculated via Genetic Algorithm and trained equipment models. And the optimal parameters are applied to establish operation schedule based on feedforward control and response time. The optimal feedforward control method is verified by a validated TRNSYS model. When the parameters are optimized, the water system energy consumption can be save by 9.5% in a cooling season.

Abstract In order to reduce air and soil pollution caused by open-field burning of stover and improve energy utilization efficiency in rural areas, Chinese government has provided many incentives for bio-energy utilization. But the amount of subsidy was not pegged to the actual environmental benefits of different energy utilization ways of agricultural waste. In this study, processed based life cycle assessment (LCA) method is used to investigate and compare the environmental impacts of three most common stover utilization ways, including biogas, stover pellets and stover gasification. The inventory analysis results are assessed by ReCiPe mid-point (H) method and end-point (H) damage evaluation, respectively. Based on the uncertainty analysis with Monte Carlo method, the compared results are expressed in probability and discussed, which shows the stover gasification utilization has more damage on the environment. Compared with the utilization of stover biogas, the utilization of stover pellets has less damage on resource depletion, but it is more harmful to human health and ecosystem. The materials used, transportation, equipment operation energy consumption, and stover utilization efficiency are found as the main parameters that affect the LCA results.