Renewable energy can help to tackle energy poverty issues of the availability of modern energy services and the sustainability of energy supply. Based on the concept of the Energy Development Index, published by International Energy Agency, this paper builds the clean energy development index and applies the Grey incidence decision method to analyze regional energy poverty issues in China. A model using panel data investigates the influencing factors that are governing energy poverty alleviation and the relationship between energy poverty and social development. The improved index system not only considers the access to modern energy services, but also addresses the cleanliness of energy supply and the transition to clean energy consumption for cooking. The results indicate that due to insufficient clean energy development, China’s Northeast and West regions have experienced increasing energy poverty problems, while energy poverty in the Southwest region has improved considerably because of its renewable energy development. Urbanization, affordability, and renewable energy development can increase access to modern energy services, contributing to energy poverty alleviation. However, the role of rural household consumption levels in energy poverty alleviation should be considered in rural energy policy.

Combined Cooling, Heating and Power (CCHP) systems have been widely used in different kinds of buildings to make better use of fuels because of their high overall efficiency. This paper presents a mathematical analysis of a CCHP system in comparison to a Heating, Ventilation and Air Conditioning (HVAC) system. The operation strategies following electric load (FEL), thermal load (FTL) and a hybrid electric-thermal load (FHL) are proposed and investigated in this study. Criteria, namely primary energy saving (PES), exergy efficiency (η_exergy), and CO₂ emission reduction (CER) are defined to evaluate the performances of CCHP systems for a hypothetical building located in Dalian (China). The results indicate that: (1) a new mathematical foundation is established to find whether the recovered thermal energy and the amount of electricity generated by the power generation unit (PGU) are enough to provide the energy required; (2) the CCHP system does not always perform better than a HVAC system from an instantaneous perspective, especially in FTL mode; (3) the CCHP system in FEL operation mode can be seen as a suitable energy system in Dalian from the annual performance perspective. Furthermore, a sensitivity analysis is presented in order to show how the performances vary due to the changes of various technical variables.

As agricultural mechanization accelerates the development of agriculture in China, to control the growth of the resulting energy consumption of mechanized agriculture without negatively affecting economic development has become a major challenge. A systematic analysis of the factors (total power, unit diesel consumption, etc.) influencing diesel consumption using the SECA model, combined with simulations on agricultural diesel flows in China between 1996 and 2010 is performed in this work. Seven agricultural subsectors, fifteen categories of agricultural machinery and five farm operations are considered. The results show that farming and transportation are the two largest diesel consumers, accounting for 86.23% of the total diesel consumption in agriculture in 2010. Technological progress has led to a decrease in the unit diesel consumption and an increase in the unit productivity of all machinery, and there is still much potential for future progress. Additionally, the annual average working hours have decreased rapidly for most agricultural machinery, thereby influencing the development of mechanized agriculture.

Recently, China is enhancing the agricultural mechanization. Meanwhile, the agricultural energy consumption is rising along with it. So many scholars are paying their attention on the energy consumption of Chinese agriculture sector. This paper is based on the data of the energy consumption of Chinese agriculture in 1991-2008. First, the present situation about the energy consumption of Chinese agriculture is analyzed. Then the DoseResp growth curve is used for the energy scenario analysis of the future trend about the energy consumption of Chinese agriculture. The results of the research indicate that firstly the energy consumption of Chinese agriculture conforms to the DoseResp growth curve. Secondly, according to the energy scenario A, the peak value of the energy consumption of Chinese agriculture is 148.73948 million-tons TCE in 2065. Thirdly, according to the energy scenario B, the peak value of the energy consumption of Chinese agriculture is 205.52559 million-tons TCE in 2067.