An oil imports dependence forecasting system based on fuzzy time series and multi-objective optimization algorithm: Case for China

Research of a combination system based on fuzzy sets and multi-objective marine predator algorithm for point and interval prediction of wind speed

Short-term wind speed forecasting is fundamental to improving the stability of power grid operation and enhancing its transmission efficiency; thus, it has long been a research hotspot. Nonetheless, quantities of literature in this field only used the single prediction model and overemphasized deterministic prediction, which resulted in deficient forecasting performance. To address these issues, a novel point and interval combination prediction system was developed in this paper. Specifically, wind speed time series were reconstructed by dividing windows and fuzzification to input highly effective data; next, four single prediction models and a multi-objective weight-determining mechanism were integrated to obtain the point prediction results; and their distributions were assessed to implement interval prediction under distinct confidence levels. In the meantime, this study demonstrated that the proposed system reached the Pareto optimal by the theoretical proof, and empirical research was conducted based on 10-min real wind speed data from the wind farm in China. Judging from the experimental results, the combination prediction system was always capable of providing the most satisfactory forecasting performance by contrast with the comparative models. Consequently, it has broad application prospects in guiding the operation of wind farms and optimizing the power grid dispatching.

Synergistic Effects of International Oil Price Fluctuations and Carbon Tax Policies on the Energy-Economy-Environment System in China

Catalyzed by COVID-19 and the Russia-Ukraine conflict, oil prices fluctuate dramatically on the worldwide market. Both international oil price changes and carbon tax policies have a direct impact on energy costs, thus influencing energy security and emission reduction impacts. Therefore, assessing the interaction effects of international oil price variations and carbon tax policies can assist in resolving the competing challenges of energy security and carbon emission reduction. The impact of international oil price fluctuations on China's energy-economic-environment system under the baseline scenario and carbon taxation scenario is analyzed by constructing a computable general equilibrium model comprising six modules: production, trade, institutions, price, environment, and equilibrium. The findings indicate that, in addition to reducing high-carbon energy consumption and increasing demand for clean electricity, rising international oil prices have a negative effect on real GDP, resulting in lower output in sectors other than construction, and a positive effect on the environmental system by driving carbon emission reductions. In contrast, decreasing international oil prices have the opposite effect. Nevertheless, the impact of rising and decreasing international oil prices is asymmetrical, with the positive shock effect being smaller than the negative. The carbon tax policy can effectively offset the increase in carbon emissions caused by the decline in international oil prices, which is conducive to promoting the development of clean energy, while simultaneously causing an increase in product prices and arousing a contraction in consumer demand, which has a limited negative impact on the macroeconomy.