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In order to achieve the goal of carbon peaking and carbon neutralization, we must vigorously develop renewable energy. As one of the important renewable energy sources, the development and utilization of biomass energy has a high cost, and it is difficult to compete with traditional fossil energy in the early stage of development. Therefore, it is necessary for the government to escort the development of the biomass energy industry through legal means. First of all, on the basis of fully analyzing the development prospects of China's biomass energy, the article sorts out the laws and regulations related to biomass energy in China, and finds the shortcomings. Secondly, this paper draws on the institutional experience of the United States, Brazil, Sweden and other countries with relatively developed biomass energy industry, and provides suggestions for improvement from three aspects: law, policy and administrative system, with a view to supporting China's development of biomass energy industry and realizing the "dual carbon target" theoretically. [ABSTRACT FROM AUTHOR]

This paper proposes the network data envelopment analysis (DEA) model accounting for negative externalities and applies it for decomposition of profit inefficiency in the biomass-agriculture circular system (Bio-AG system). A circular structure of the Bio-AG system which is different from the previously applied network structures is assumed. Since the negative externalities (i.e., pollutant emissions from the biomass industry) occur in the Bio-AG system, the property rights are taken into consideration to model the externalities-adjusted profits. Therefore, the changes in profits due to changes in the property rights (assuming no property rights, allocating property rights to agricultural sector, and allocating property rights to biomass power generation sector) are quantified. Further, the decomposition shows that the biomass power generation sector is less affected by technical inefficiency if contrasted to allocative inefficiency in terms of the profit loss. The findings suggest that the biomass power generation technology influences the profits of the biomass industry. What is more, the inefficient allocation of resources is now the key factor undermining performance of the biomass industry. Therefore, the government should adopt measures to improve the allocation of resources and prevent excessive investments or development of less efficient technologies. [ABSTRACT FROM AUTHOR]

In this paper we develop an agent-based model to explore a feasible way of simultaneously providing sufficient food and bioenergy feedstocks in China. Concerns over the competition for agricultural land resources between food and bioenergy supply hinder the further development of bioenergy, especially in China, the country that needs tofeed the world's largest population. Prior research has suggested the introduction of energy crops and reviewed the resulting agricultural land use change in China. However, there is a lack of quantitative studies which estimate the value, contribution, and impact of bioenergy for specific conditions at the county level and provide adequate information to guide local practices. Tofill this gap, we choose the Jiangsu Province in China as a case study, build up a spatial-agent dynamic model of agricultural land use, and perform a sensitivity analysis for important parameters. The simulation results show that straw from conventional crops generally dominates Jiangsu's biomass supply with a contribution above 85%. The sensitivity analyses reveal severe consequences of bioenergy targets for local land use. For Jiangsu Province, reclaimed mudflats, an alternative to arable lands for energy crop plantation, help to secure the local biomass supply and to alleviate the land use conflict between food and biomass production. [ABSTRACT FROM AUTHOR]

As a major technical route to utilize biomass energy, biomass combustion power generation (BCPG) has been shown to be of environmental and economic significance. According to the operating experience, the installed capacity has a decisive impact on the operation and economic return of BCPG projects. In China, an installed capacity of either 30 MW or 12 MW is often chosen for constructing a BCPG project. To explore which one is more suitable for China, this paper uses actual operating data to compare the operation performance and techno-economics of two representative BCPG projects with an installed capacity of 30 MW and 12 MW. The results show that the operation situation and electricity production of the 30 MW project are better than those of the 12 MW project. The 30 MW project has a lower biomass consumption than the 12 MW project to produce per unit of electricity. The Internal Rate of Return (IRR) of the 30 MW project is greater than the industry benchmark in China and is almost three times the IRR of the 12 MW project. Therefore, it is recommended to construct BCPG projects with installed capacity of 30 MW in China. [ABSTRACT FROM AUTHOR]

Small-scale bio-energy projects have been launched in rural areas of China and are considered as alternatives to fossil-fuel energy. However, energetic and environmental evaluation of these projects has rarely been carried out, though it is necessary for their long-term development. A village-level biomass gasification project provides an example. A hybrid life-cycle assessment (LCA) of its total nonrenewable energy (NE) cost and associated greenhouse gas (GHG) emissions is presented in this paper. The results show that the total energy cost for one joule of biomass gas output from the project is 2.93 J, of which 0.89 J is from nonrenewable energy, and the related GHG emission cost is 1.17 × 10-4 g CO2-eq over its designed life cycle of 20 years. To provide equivalent effective calorific value for cooking work, the utilization of one joule of biomass gas will lead to more life cycle NE cost by 0.07 J and more GHG emissions by 8.92 × 10-5 g CO2-eq compared to natural gas taking into consideration of the difference in combustion efficiency and calorific value. The small-scale bio-energy project has fallen into dilemma, i.e., struggling for survival, and for a more successful future development of village-level gasification projects, much effort is needed to tide over the plight of its development, such as high cost and low efficiency caused by decentralized construction, technical shortcomings and low utilization rate of by-products. [ABSTRACT FROM AUTHOR]

Microalgal biofuel research in China has made noticeable progress, and algae cultivation for biofuel production is considered to be an important contribution to Greenhouse Gas (GHG) mitigation and energy security. In this paper, the algal biofuel potentiality in China was reviewed from the points of view of algal biodiversity, algal culture collection, GHGs (especially CO2) mitigation, and the availability of the required sunlight, wastewater and land resources. The cultivation of microalgae utilizing power plants gas with large amounts of CO2 and wastewaters from urban households, industry and animal husbandry are suitable for large scale production in China. Land is hardly a limitation for algae cultivation. [ABSTRACT FROM AUTHOR]

With the rapid progress of socio-economic development and urbanization in China, a wide variety of literature has focused on the phenomenon of energy-consumption disparity, which in turn could be related to numerous fundamental energy dilemmas that China must deal with now or soon, including energy use inefficiency, regional energy shortage, insufficient use of green energy, etc. However, in most cases, only a tendency scenario is discussed, while identifying which factors are more likely to affect the improvement of energy supply/use has not yet been fully explored. Therefore, this paper attempts to explore differences in energy consumption in specific, household-level aspects. Based on the information provided by Chinese General Social Survey (CGSS2015), the Gini coefficient and the Lorentz asymmetry coefficient are used to measure the difference among various categories of energy type and end use within and between different geographical sub-groups. The findings show that: (1) household energy-consumption behaviors exhibit a complicated effect on the overall level of energy-consumption difference; (2) from the supply side, energy users show the most significant difference in biomass energy consumption, while from the demand side, the contribution of space heating to the difference in total energy consumption is the highest; (3) a great urban–rural difference in energy consumption is generally observed with its difference within rural areas being much greater than in urban areas; (4) the eastern, middle and western regions weight differently in explaining the overall difference of energy consumption. These findings provide meaningful materials and references for policymakers in China to understand the overall situation of individual energy consumption to a great extent, and to locate key points to reform the current energy policy framework. [ABSTRACT FROM AUTHOR]

Biomass is the fourth largest energy source in the world; it is easy to store and can be converted into various kinds of renewable energies. The biomass cogeneration system is an important way to utilize biomass energy, especially in northern China. At present, there are many problems in biomass power plants in China, such as high latent heat loss of chimney and cooling towers, low power generation efficiency, and thermal efficiency. In order to solve this problem, this paper introduces low vacuum circulating water heating technology in the biomass cogeneration system, and expounds the differences between China and Western countries in biomass power plants. Based on this background, the technology is redesigned and reformed to make it more suitable for the biomass fuel varieties in the power plant location, and realize the localization of technology and the expansion of scale. The application of this improved technology in China's biomass cogeneration project is analyzed. Based on the biomass cogeneration project in the DC County of China, the analysis confirms that the designed low vacuum circulating water heating technology is suitable for biomass power generation projects with agricultural and forestry wastes as raw materials, and its application can greatly improve the heat utilization efficiency of the whole cogeneration system. At the same time, in order to estimate the possibility of profitable investment when the key financial parameters change, the financial risk is analyzed. The results show that the probability of 90% net present value (NPV) in 15 years is between 355.28 million RMB and 623.96 million RMB, and the internal rate of return can reach 17.7%. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei region has abundant biomass resources, which are difficult to collect and thus are underutilized. However, the potential estimation of biomass energy can result in a comprehensive understanding of bioenergy resources in order to establish a technology roadmap for the region's bioenergy development. Therefore, it is essential to estimate the potential of Beijing-Tianjin-Hebei biomass resources and bioenergy utilization. In this paper, the amount of main biomass resources for possible energy use and bioenergy utilization are calculated based on a statistical data estimation method for crop residues; human, poultry, and livestock manure; and municipal solid wastes. On the basis of biomass resources and bioenergy utilization potential, the technology roadmap is established. The results show that the amount for available biomass energy use is unevenly distributed in the Beijing-Tianjin-Hebei region, and the largest amount of resources is crop residues (36.52 million tons or 18.26 million tons coal equivalent). The biogas from human, poultry, and livestock manure and densified solids from crop residue technology roadmap is suitable for the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Given the abundant straw resources in Northeast China and the huge external costs associated with fossil fuels, straw-based biomass power plants have emerged as a popular alternative to coal-fired power plants. The sustainability of these green alternatives depends on straw supply from farmers, yet little is known about their perceptions regarding such supply because of a lack of cooperation in the supply chain. To better understand farmers' opinions on supplying straw, this study examined their trust in middlemen, perceptions regarding risk in straw supply, the possibility of reducing transaction costs, and their willingness to supply straw. Data were collected from 275 farmers in the national bioenergy industry area inWangkui County, Northeast China. We investigated the theoretical and empirical connections between trust and risk perception, trust and the possibility of reducing transaction costs, and trust and willingness to supply straw. The results indicated that education, income, and trust factors explained farmers' risk perceptions, the possibility that they will reduce transaction costs, and their willingness to supply straw. On the basis of the analysis, a model of the influence of trust on straw supply was established. The overall findings indicated that biomass power plants and middlemen must build trusting relationships with farmers to ensure sustainable biomass supply. [ABSTRACT FROM AUTHOR]

Biofuel production in China suffers from many uncertainties due to concerns about the government's support policy and supply of biofuel raw material. Predicting biofuel production is critical to the development of this energy industry. Depending on the biofuel's characteristics, we improve the prediction precision of the conventional prediction method by creating a dynamic fuzzy grey-Markov prediction model. Our model divides random time series decomposition into a change trend sequence and a fluctuation sequence. It comprises two improvements. We overcome the problem of considering the status of future time from a static angle in the traditional grey model by using the grey equal dimension new information and equal dimension increasing models to create a dynamic grey prediction model. To resolve the influence of random fluctuation data and weak anti-interference ability in the Markov chain model, we improve the traditional grey-Markov model with classification of states using the fuzzy set theory. Finally, we use real data to test the dynamic fuzzy prediction model. The results prove that the model can effectively improve the accuracy of forecast data and can be applied to predict biofuel production. However, there are still some defects in our model. The modeling approach used here predicts biofuel production levels based upon past production levels dictated by economics, governmental policies, and technological developments but none of which can be forecast accurately based upon past events. [ABSTRACT FROM AUTHOR]

Biomass gasification to produce burnable gas now attracts an increasing interest for production flexibility in the renewable energy system. However, the biomass gasification technology using dual fluidized bed which is most suitable for burnable gas production still encounters problems of low production efficiency and high production cost. Here, we proposed a large-scale biomass gasification system to combine dual fluidized bed and high-temperature gas-cooled reactor (HTR) for co-production of hydrogen and synthetic natural gas (SNG). The design of high-temperature gas-cooled reactor biomass gasification (HTR-BiGas) consists of one steam supply module to heat inlet steam of the gasifier by HTR and ten biomass gasification modules to co-produce 2000 MWth hydrogen and SNG by gasifying the unpretreated biomass. Software for calculating the mass and energy balances of biomass gasification was developed and validated by the experiment results on the Gothenburg biomass gasification plant. The preliminary economic evaluation showed that HTR-BiGas and the other two designs, electric auxiliary heating and increasing recirculated product gas, are economically comparative with present mainstream production techniques and the imported natural gas in China. HTR-BiGas is the best, with production costs of hydrogen and SNG around 1.6 $/kg and 0.43 $/Nm3, respectively. These designs mainly benefit from proper production efficiencies with low fuel-related costs. Compared with HTR-BiGas, electric auxiliary heating is hurt by the higher electric charge and the shortcoming of increasing recirculated product gas is its lower total production. Future works to improve the efficiency and economy of HTR-BiGas and to construct related facilities are introduced. [ABSTRACT FROM AUTHOR]

Energy consumption issues are important factors concerning the achievement of sustainable social development and also have a significant impact on energy security, particularly for China whose energy structure is experiencing a transformation. Construction of an accurate and reliable prediction model for the volatility changes in energy consumption can provide valuable reference information for policy makers of the government and for the energy industry. In view of this, a novel improved model is developed in this article by integrating the modified state transition algorithm (MSTA) with the Gaussian processes regression (GPR) approach for non-fossil energy consumption predictions for China at the end of the 13th Five-Year Project, in which the MSTA is utilized for effective optimization of hyper-parameters in GPR. Aiming for validating the superiority of MSTA, several comparisons are conducted on two well-known functions and the optimization results show the effectiveness of modification in the state transition algorithm (STA). Then, based on the latest statistical renewable energy consumption data, the MSTA-GPR model is utilized to generate consumption predictions for overall renewable energy and each single renewable energy source, including hydropower, wind, solar, geothermal, biomass and other energies, respectively. The forecasting results reveal that the proposed improved GPR can promote the forecasting ability of basic GPR and obtain the best prediction effect among all the other comparison models. Finally, combined with the forecasting results, the trend of each renewable energy source is analyzed. [ABSTRACT FROM AUTHOR]