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With the development of the economy and society, the problems of resources and the environment are becoming more and more prominent. As an environmentally friendly and clean energy, wind energy is developing rapidly with the support of relevant policies and technologies. At the same time, the development of the wind power industry is also faced with some problems, as the "abandoning wind" phenomenon of wind farms is still relatively common; the continuous decline of wind turbine prices and the sharp rise in operation and maintenance costs have further reduced the profit space of wind power manufacturers. The fundamental reason for the series of difficulties in the development of the wind power industry is the imbalance between the various links in the wind power industry chain. There is an urgent need to evaluate the performance of the wind power industry chain to improve the weak links. In this paper, by using the three-stage data envelopment analysis (DEA) model, the input-oriented BCC model is used in the first stage, and the stochastic Frontier analysis method is used to analyze the input relaxation variables in the second stage to eliminate two exogenous factors. In the third stage, the adjusted input variables are recalculated in the first stage, and the chain performance value of the wind power industry excluding environmental factors and random errors is obtained in the performance evaluation. This paper takes China's wind power industry as an example and makes an overall analysis of the upstream, middle, and downstream of the wind power industry chain from three aspects: technology performance, scale performance, and pure technology performance. The results show that under the support of policy and economy, the technical performance of the upper and lower reaches of China's wind power industry chain is higher, while the performance of the wind power industry chain is underestimated by environmental factors. The three-stage DEA model can eliminate the influence of environmental and random errors, which makes the evaluation of the wind power industry chain more objective. In addition, according to the evaluation results, the optimization direction of each structure of the industrial chain is put forward. [ABSTRACT FROM AUTHOR]

Green growth has become an increasingly important paradigm for sustainable economic growth, resource development, and environmental protection. As the main focus in energy led green growth is a move away from fossil energy to clean energy, sustainable green growth resource development needs to measure both energy and environmental efficiencies. As the largest global energy consumer and carbon emitter, China has had to deal with serious energy and environmental issues in recent years, with its regional green growth performances being poorly assessed. Therefore, green growth clean energy-environmental efficiency assessments were examined in this paper, for which an integrated principal component analysis-data envelopment analysis based analysis approach was developed. It was found that while China's green growth has had a significant increasing trend in recent years, overall it was still at a low level, with the imbalances in China's regional economic development being reflected in its green growth. However, the excellent development and utilization of clean energy in most regions have significantly promoted a continuous improvement in China's green growth and the move toward sustainable resource development and utilization is contributing to long-term green growth. Green growth has also placed new demands on sustainable resource development in China. Therefore, underdeveloped regions that have sustainable resource endowments need to develop industrial systems that have clean energy as the main axis, and developed regions need to develop high-end industries that have low energy consumption and encourage mutual support systems between regions to ensure optimal sustainable resource, green growth development patterns. [ABSTRACT FROM AUTHOR]

Dynamic optimization is likely to play an important role in the reliability, quality, and efficiency of future power system, specifically for microgrid with renewable generation. This paper presents an improved hybrid optimization algorithm, called information exchange particle swarm optimization (IEPSO), to deal with the problem of dynamic optimal control in a microgrid with multiple distributed generations (DGs), such as wind power, small hydro, and energy storage. Based on the actual application of DG in Southwest China, we propose an optimization model for grid-connected microgrid that introduces a contribution rate of energy storage into the model and incorporates practical engineering constraints. The performance of different optimization control strategies for active and reactive power is investigated, and the results indicate that the IEPSO algorithm is efficient for dynamic optimization, and the dynamic contribution rate control strategy for energy storage is more effective than static strategy. [ABSTRACT FROM AUTHOR]

Southeast Tibet in China is rich in clean energy such as water energy, light energy, and wind energy. As the key means of large-scale clean energy transmission in southeast Tibet, the ultra-high voltage (UHV) power transmission projects will be constructed at an altitude of nearly 4000 m. To accurately acquire the external insulation strength of electrical equipment operating at different altitudes, the standard positive switching impulse voltages were applied to a rod electrode and a 1.1 m diameter shielding sphere at the altitude of 3400, 2100, and 80 m. The switching impulse discharge characterization and altitude correction factors of the 1.1 m diameter shielding sphere-plate gap under different clearances at different altitudes were obtained. The discharge voltage of the rod-plate gap at the altitude of 80 m was corrected to the altitude of 3400 m using altitude correction methods recommended by GB 311.1, GB/T 16927.1, and DL/T 2305. Further comparison was made between the calculation results using the three altitude correction methods mentioned above and the test results at an altitude of 3400 m. The discharge characterization and the minimum clearance of the end fittings of the electrical equipment in the valve hall at the altitude of 3800 and 4500 m were obtained by fitting and extrapolating the test data. The research results provide important reference significance for the external insulation configuration of UHV converter stations constructed in areas with an altitude of 3000 m and above. [ABSTRACT FROM AUTHOR]

We address the problem of setting realistic regional carbon reduction targets in China. Scenario analysis, combined with a regional carbon emission model, was used to evaluate whether the current government goals are realistic. We first set reasonable scenarios for factors in the model that have important effects on carbon emissions, and then forecast the carbon emissions for a given region. Reasonable regional carbon reduction goals were obtained based on these forecasts. In Beijing, eleven kinds of development scenarios were considered, and their effects on carbon reduction goals were analyzed. Results showed that future CO2 emissions in Beijing will rise markedly, whereas carbon intensity will reduce gradually, causing the rate of carbon reduction to slow over the long term. We found that an 18% reduction in carbon intensity for Beijing during the 12th Five-Year Plan is a reasonable goal, whereas a 45%-50% reduction from 2005 to 2020 is also realistic. Moreover, the carbon intensity in Beijing could be reduced by 12%-16% during the 13th Five-Year Plan and by a further 12% during the 14th Five-Year Plan. Rapid economic growth, stable urban development, and a rising proportion of tertiary industries in Beijing all contribute to achieving its carbon reduction target. [ABSTRACT FROM AUTHOR]