Novel Role of Rural Official Organization in the Biomass-Based Power Supply Chain in China: A Combined Game Theory and Agent-Based Simulation Approach

Developing biomass-based power generation is helpful for China to reduce the dependence on fossil fuels and to release the targets of carbon emission peak. The decentralized farming method leads to Chinese farmers’ weak willingness to collect and sell crop residues to biomass-based power plants. The purpose of this paper is to solve the issue by proposing a novel biomass feedstock supply model with China’s rural official organization—villagers’ committee, which has great influence on villagers’ decision making. Introducing it into the biomass-based power supply chain is beneficial to motivating farmers’ supplying enthusiasm. A combined game theory and agent-based simulation approach is applied to study the effectiveness of this new supply model. Multiple simulation scenarios are built to study impacts of different simulation parameters, and results show that farmers tend to supply more biomass material for electricity production in the proposed villagers’ committee model, compared with the two conventional supply models, direct-deal and broker models. The supply model incorporating the rural official organization can ensure the feedstock sufficiency for plants. A proper model design depends on the feed-in tariff subsidy for biomass-based electricity, feedstock shipping distance, performance appraisal system of the villagers’ committee, as well as farmers’ utility weights on net income and public service improvement

A Co-Opetition Straw Supply Strategy Integrating Rural Official Organizations and Farmers’ Behavior in China

China has a huge potential of biomass power generation since it is a big agricultural producer and abundant in agriculture straw. However, the current straw supply system cannot guarantee the feedstock sufficiency for biomass power plants. The main reason is the high costs of straw collection and transportation because farmers are scattered across the country and farming in a small-scaled method for self-support. This study aims at solving the issue with the introduction of China’s rural official organizations to collect agriculture straw in a centralized way and to share benefits with farmers. We apply the approach of multi-agent modeling and simulation to analyze the farmer’s participation behavior within a co-opetition supply strategy after the rural official organizations are incorporated. The results demonstrate that farmers’ participation is positively affected by the cooperative enthusiasm of rural official organizations. In addition to those basic factors, such as straw price, transportation cost, and shipping distance, the benefit sharing policy has a significant impact on the equilibrium percentage of the cooperative farmers. We recommend that the Chinese central government encourage and support rural official organizations to participate in the agriculture straw supply chain, and the benefit sharing policy should be implemented with the precaution against free rides

Information Extraction and Prediction of Rocky Desertification Based on Remote Sensing Data

Rock desertification has become the third most serious ecological problem in western China after desertification and soil erosion. It is also the primary environmental problem to be solved in the karst region of southwest China. Karst landscapes in China are mainly distributed in southwest China, and the area centered on the Guizhou plateau is the center of karst landscape development in southern China. It has a fragile ecological environment, and natural factors and human activities have influenced the development of stone desertification in the karst areas to different degrees. In this paper, Dafang County, Guizhou Province, was selected as the study area to analyze the effect of the decision tree and multiple linear regression model on stone desertification and to analyze the evolution characteristics of stone desertification in Dafang County from 2005 to 2020. The FLUS model was applied to predict and validate the stone desertification information. The results show that the overall accuracy of multiple linear regression extraction of stone desertification is 70%, and the Kappa coefficient is 0.69; the overall accuracy of decision tree extraction of stone desertification is 60%, and the Kappa coefficient is 0.521. The multiple linear regression stone desertification extraction model is more accurate than the traditional decision tree classification. The overlay analysis of stone desertification and slope, elevation, slope direction and vegetation cover showed that stone desertification was more distributed between 1300–1900 m in elevation; stone desertification decreased gradually with the increase in slope; each grade of stone desertification was mainly distributed in the range of 5 to 25° in slope, which might be related to human activities. The FLUS model was used to predict the accuracy of 2015 data in the region and project the changes in stone desertification area in 2035 under a conventional scenario and an ecological protection scenario in the region to provide a new reference for predicting stone desertification

A Systematical Framework of Schedule Risk Management for Power Grid Engineering Projects’ Sustainable Development

Schedule risks are the main threat for high efficiency of schedule management in power grid engineering projects (PGEP). This paper aims to build a systematical framework for schedule risk management, which consists of three dimensions, including the personnel dimension, method dimension and time dimension, namely supervisory personnel, management methods and the construction process, respectively. Responsibilities of staff with varied functions are discussed in the supervisory personnel part, and six stages and their corresponding 40 key works are ensured as the time dimension. Risk identification, analysis, evaluation and prevention together formed the method dimension. Based on this framework, 222 schedule risks occur in the whole process of PGEPs are identified via questionnaires and expert interviews. Then, the relationship among each risk is figured out based on the Interpretative Structure Model (ISM) method and the impact of each risk is quantitatively assessed by establishing evaluation system. The actual practice of the proposed framework is verified through the analysis of the first stage of a PGEP. Finally, the results show that this framework of schedule risk management is meaningful for improving the efficiency of project management. It provides managers with a clearer procedure with which to conduct risk management, helps them to timely detect risks and prevent risks from occurring. It is also easy for managers to judge the influence level of each risk, so they can take actions based on the level of each risk’s severity. Overall, it is beneficial for power grid enterprises to achieve a sustainable management

The Cultivation of Electric Vehicles Market in China: Dilemma and Solution

Global warming has been increasingly concerning, and international society has been taking various measures to mitigate this issue. Since the electric vehicle has important and generally beneficial impacts on environment protection, grid construction, and operation economical efficiency improvement, many countries have stressed the status of electric vehicle promotion in future planning. As China is the world’s largest carbon dioxide emitter, the Chinese government has taken various acts to reduce emissions, of which promoting electric vehicle is an effective one. This paper attempts to present a critical review of the current EV situations including the market sales, charging infrastructure, battery performances and policies in China. The survey of customer preferences and acceptance to electric vehicle indicate that purchasing behaviors are affected by four factors: charge inconvenience, short battery range, cost and psychological factors. According to the China’s situation, recommendations including diversified energy supplement approaches, time-of-use charging price mechanism, vehicle-to-grid technology and enlarge price subsidy scope are proposed to accelerate the development of the electric vehicle industry

Effect of metformin treatment during pregnancy on women with PCOS: a systematic review and meta-analysis

Purpose: Some previous studies have found that continued metformin use is beneficial in the management of polycystic ovary syndrome (PCOS) in pregnant women. A systemic review and meta-analysis were needed to more fully assess the effects of metformin on pregnant PCOS patients. Methods: The literature was fully searched using MEDLINE, EMBASE, SCOPUS, and COCHRANE for continued metformin use during pregnancy in women with PCOS. A systematic review and meta-analysis were performed to evaluate the comprehensive effects of continued metformin treatment on pregnancy-related outcomes in these women. Results: Eleven eligible studies out of 127 relevant publications were included in meta-analysis. The rates of early pregnancy loss and preterm delivery were found to be significantly decreased in metformin-treated PCOS women. A non-significant difference was found in fetal abnormality and fetal birth weight between the metformin-treated and the non-treated groups. The incidence of gestational diabetes mellitus (GDM) and hypertension/preeclampsia were not significantly different in the two groups, probably because of inconsistent results in the subgroup analysis. Conclusions: Our results showed that continued use during of metformin, during pregnancy in women with PCOS, had no effect on incidence of fetal abnormalities or fetal birth weight. The effects of metformin on GDM and hypertension/preeclampsia should be determined through high-quality randomized controlled trials