Electricity Substitution Potential Prediction Based on Tent-CSO-CG-SSA-Improved SVM—A Case Study of China

Nowadays, fossil energy continues to dominate China’s energy usage; its inefficient use and large crude emissions of coal and fuel oil in its end-consumption have brought about great pressure to reduce emissions. Electrical power substitution as a development strategy is an important step toward achieving sustainable development, the transformation of the end-use energy consumption structure, and double carbon goals. To better guide the broad promotion of electrical power substitution, and to offer theoretical support for its development, this paper quantifies the amount of electrical power substitution and the influencing factors that affect the potential of electrical energy substitution. This paper proposes a hybrid model, combining Tent chaos mapping (Tent), chicken swarm optimization (CSO), Cauchy–Gaussian mutation (CG), the sparrow search algorithm (SSA), and a support vector machine (SVM), as a Tent-CSO-CG-SSA-SVM model, which first uses the method of Tent chaos mapping to initialize the sparrow population in order to increase population diversity and improve the search ability of the algorithm. Then, the CSO is introduced to update the positions of sparrows, and the CG method is introduced to make the algorithm jump out of the local optimum, in order to improve the global search ability of the SSA. Finally, the final electrical power substitution potential prediction model is obtained by optimizing the SVM through a multi-algorithm combination approach. To verify the validity of the model, two regions in China were used as case studies for the prediction analysis of electrical energy substitution potential, and the prediction results were compared with multiple models. The results of the study show that Tent-CSO-CG-SSA-SVM offers a good improvement in prediction accuracy, and that Tent-CSO-CG-SSA-SVM is a promising method for the prediction of electrical power substitution potential.

Coupling and Coordination Analysis of Thermal Power Carbon Emission Efficiency under the Background of Clean Energy Substitution

With the proposed goals of reaching its “carbon peak” by 2030 and becoming “carbon neutral” by 2060, China will comprehensively build a diversified, efficient and clean energy system. The differences in China’s resource endowments have made the development of carbon emission reduction in the thermal power industry uncoordinated in various regions. Therefore, it is necessary to optimize the method for measuring thermal power carbon emission efficiency and determine the impact of regional development imbalances on the carbon emission efficiency of thermal power. For this article, we used the stochastic frontier analysis method and selected a variety of influencing factors as technical inefficiency items. After that, we measured the thermal power carbon emission efficiency in 30 provinces and municipalities (autonomous regions) in China in the past 10 years, and it was found that the efficiency was increasing yearly and showed obvious spatial differences. The impact of the clean energy substitution effect on the thermal power carbon emission efficiency cannot be ignored. After performing a coupled and coordinated analysis on the efficiency of thermal carbon emission in various regions and its influencing factors, the three indicators of power consumption intensity, urbanization level and clean energy substitution effect were selected. The weight of the indicator subsystem was determined in view of the estimation of the technical inefficiency. The results of the coupling and coordination analysis show that the degree of coupling and coordination of thermal power carbon emission efficiency is increasing yearly and presents a distribution of “high in the eastern region and low in the western region”. Therefore, all provinces need to vigorously carry out clean replacement work to enhance the coordinated development of carbon emission reduction in the thermal power industry and the level of regional economic development.

Analysis of the Efficiency of Provincial Electricity Substitution in China Based on a Three-Stage DEA Model

An electricity substitution strategy that replaces fossil fuels such as coal and oil with electricity in end-use energy consumption, can effectively contribute to an energy transition and the early achievement of carbon peaking and carbon neutrality targets. As the benefits of electricity substitution are not synchronized across China’s regions, this paper uses a three-stage data envelopment analysis (DEA) model to measure the efficiency of electric energy substitution in 30 provinces of China in 2017. The results show that both environmental factors and random errors have significant effects on energy efficiency. After eliminating these influences, the efficiency of electrical energy substitution among regions presented the following pattern: “high in the east and low in the west”. According to the evaluation results, this paper proposes corresponding suggestions for the development of electrical energy substitution.

Evaluation of Existing And Future Zero Waste Approach in Municipal Solid Waste Management Utilizing the Zero Waste Index: Bali Province, Indonesia

The World Bank reported that around 1.3 billion tonnes of municipal waste were generated in 2011, and this amount is expected to increase to 2.2 billion tonnes by 2025. Zero Waste Index (ZWI) is a breakthrough for measuring and evaluating waste management's performance based on the concept of zero waste, where recycling is the key to determining this value. This study was conducted in a province in a developing country, namely Bali Province, Indonesia. The calculation of ZWI and energy substitution from waste management is carried out on two schemes, an optimistic scheme (basic data and percentage of waste management targets referring to the regional policy and strategy documents) and a pessimistic scheme (basic data refers to material flow analysis of waste with no increase in the percentage of waste management) from 2020 to 2025. Energy substitution is calculated on two conditions of use, namely through incinerator technology (listed in Indonesia Presidential Regulation No. 35 of 2018) and without incinerators at the Sarbagita Regional Landfill. Analysis indicated that the pessimistic scheme provides a higher ZWI value of Bali Province in 2020 than the optimistic scheme, but there is no increase in the ZWI value until 2025 (the ZWI value ranges from 0.02 to 0.2) due to no increase in the percentage of solid waste management. Meanwhile, the optimistic scheme provides a lower ZWI value for Bali's Province in 2020 than the pessimistic scheme, but there is an increase in the ZWI value every year until 2025 (the ZWI value ranges from 0.004 to 0.22). In terms of energy substitution, an optimistic scheme provides energy substitution values ​​2-5 times greater than pessimistic schemes, with and without incinerators. However, in terms of the incinerator efficiency, the pessimistic scheme provides greater efficiency (2-6% efficiency when using an incinerator) than the optimistic scheme (1-2% efficiency when using an incinerator). The 3R (Reuse, Reduce, Recycle)-based waste management and high energy substitution potential in Bali Province can be an effective waste management solution if the stakeholders are committed to achieve the Jakstrada targets by 2025.