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To achieve the goal of achieving carbon-neutral by 2060, the government of China has put forward higher requirements for energy conservation and consumption reduction in the energy industry. Therefore, it is necessary to reduce energy consumption in the process of transporting oil. In this paper, an optimization model that minimizes the total energy consumption of the entire pipeline system is proposed and the squirrel search algorithm (SSA) is used to solve the optimization model. Meanwhile, to improve the performance of the SSA, two strategies are proposed. One is the adaptive inertia weight strategy, and the other is the multi-group co-evolution strategy. The adaptive inertia weight can adjust the step size of the flying squirrels according to the difference of the objective function value and multi-group co-evolution is introduced to improve population diversity. The improved SSA is named multigroup coevolution-adaptive inertia weight SSA (MASSA). A total of 20 benchmark functions are used to test the performance of MASSA, including unimodal functions and multimodal functions. Compared with the other four algorithms, MASSA has better performance and convergence capabilities. In the case study experiment, an optimization model of the oil pipeline is built, which takes the minimum energy consumption of the whole pipeline as the objective function. Compared with the actual operating conditions, the electricity consumption optimized by MASSA decreases by 399,018.94 kgce, and the thermal energy dissipation decreases by 113,759.25 kgce. The total energy consumption is reduced by 512,778.19 kgce, which is 9.62%. These results indicate that the two improvement strategies are significant, and optimizing the operating parameters can reduce energy consumption. [ABSTRACT FROM AUTHOR]

The credible sources of fossil energy efficiently are a vital cause of economic growth and considerable influence on adequate security. Whereas radiant energy positively enhances or ostensibly promotes socio-economic stability and the controlled environment. The fossil energy sources supply has become progressively stern in China and reconnoitering the beta decoupling relationships between CO2 emissions, GDP, energy consumption, electricity consumption, value-added industries, and population. The results will be favorable for illustrative the security of the valuable resources. This study adopts the extended stochastic model (STIRPAT) with Beta Decoupling Techniques (BDT). This modern technique merely employs the decoupling situation by the alpha and beta effects from 1989 to 2018 and calculates the % change in CO2 emissions by GDP growth and energy consumption. The estimated results represent negative and economic growth depends on coal and natural gas. First, CO2 emissions annually increasing cause of rapid growth, energy consumption, and electricity production, and the structural contradiction of energy remained static. Second, the Value-added industries estimated that CO2 emissions reduce by primary industries. Third, the decoupling states of CO2 emissions and population show an inverse relationship. This paper tentatively suggests China is sustainable, naturally strengthens energy output, transmutes the energy consumption structure, and advances development policies under environmental circumstances. [ABSTRACT FROM AUTHOR]

Regional energy development and approaches are significant for China's overall economic and social development. The GDP in Zhejiang province surpassed 6 trillion yuan in 2019, and its energy consumption reached 200 million tons of standard coal (tce), both of which are at the forefront of China. In order to explore the main factors of the increase in energy consumption in Zhejiang and provide essential references for energy saving and other provinces, this paper analyzes the total energy consumption and industrial sectors on the basis of the logarithmic mean divisia index (LMDI) model. Study results show that the economy's scale is the most crucial factor affecting Zhejiang's energy consumption, with a significant growth effect. In 2015, the scale effect increased energy consumption to the highest value of 14 million tce and then reduced it to 13 million tce in 2019. The impact of the population on energy consumption increased by 10 million tce from 2010 to 2019. Energy intensity reduces energy consumption by between 0.05 and 0.15 billion tce per year, which is the main factor in reducing energy consumption. The energy structure generally plays a weak positive role due to the different energy types. The decomposition of the energy consumption per unit of value added in the industrial sector showed that the intensity and structural effect primarily reduce energy consumption, for example, the metal smelting and rolling, textile printing and paper, electric power, heating, and other industries. According to the results, enterprises should enhance the intelligence and efficiency of dispatch management and emergency responses. Zhejiang should also accelerate an international oil and gas trading center and resource allocation base to reach its carbon-neutrality goal. [ABSTRACT FROM AUTHOR]

Under the downward pressure of the economy, China's extensive economic growth that relies on factor input is difficult to sustain. Scientific analysis of the industrial restructuring and energy consumption has become the key to realizing China's economic growth from high-speed to high-quality. Based on the fully-modified least square method and panel vector error correction model, this paper explores the equilibrium relationship and Granger causality among the industrial restructuring, energy consumption and economic growth at aggregated and disaggregated levels. The results show that: (1) The effect of industrial structure rationalization on economic growth is higher than that of industrial structure upgrading. When emphasizing industrial structure upgrade, the more reliable industrial policy to achieve China's sustainable economic growth is to pay attention to the industrial structure rationalization, especially in western China. (2) The impacts of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption; more energy policies should be designed to encourage clean energy development. • The industrial structure rationalization has highest contribution to the economic growth of eastern China, followed by central and western China. • There exists unidirectional causality from industrial structure upgrading to structure rationalizing in western China and bidirectional causality between them in central China. • Effects of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption. • Unidirectional long-term causality from renewable energy to economic growth exist in each sub-region. [ABSTRACT FROM AUTHOR]

• A data envelopment analysis model was built to assess the operation energy efficiency. • Wastewater treatment plants' distances from effective level were compared. • Disparities of results among regions and treatment processes adopted are evident. The energy use intensity of wastewater treatment facilities has been increasing in recent decades in China. In this paper, data envelopment analysis is used to evaluate the energy efficiency of municipal wastewater treatment plants (WWTPs) in China. In the DEA model, the six input indicators were load rate, design scale, unit electricity consumption, sludge generation, actual treatment volume and accumulated electricity consumption, and the six outputs were COD, BOD, SS, NH 3 -N, TN and TP pollutant removals per amount of electricity consumption. A total of 4100 plants were assessed in China in 2018. The relative efficiencies of 14 plants at 1.0, with an average electricity consumption of 0.091 kWh/m3 compared to the national average consumption of 0.38 kWh/m3, served as a benchmark for the remaining inefficient plants. According to the Malmquist index results, during 2014–2018, on average, 40.54% of the WWTPs experienced productivity improvements, 71.24% of the plants increased their technical efficiency relative to the frontier, and 27.21% of the plants showed progress on the production frontier. Western areas in China consume a large proportion of renewable energy with higher energy efficiency levels, while central and eastern areas had lower energy efficiency trends and high pollutant emissions levels. The oxidation pond method has the highest comprehensive technical efficiency of 0.446, nearly eight times the average efficiency level. It is suggested that wastewater treatment industries should not only consider technical efficiency increases but also match their pollutant burdens and implementation of discharge standards with energy-saving targets. [ABSTRACT FROM AUTHOR]