Abstract
Since 2013, a series of air pollution prevention and control (APPC) measures have been promulgated in China for reducing the level of air pollution, which can affect regional short-term electricity power demand by changing the behavior of power users electricity consumption. This paper analyzes the policy system of the APPC measures and its impact on regional short-term electricity demand, and determines the regional short-term load impact factors considering the impact of APPC measures. On this basis, this paper proposes a similar day selection method based on the best and worst method and grey relational analysis (BWM-GRA) in order to construct the training sample set, which considers the difference in the influence degree of characteristic indicators on daily power load. Further, a short-term load forecasting method based on least squares support vector machine (LSSVM) optimized by salp swarm algorithm (SSA) is developed. By forecasting the load of a city affected by air pollution in Northern China, and comparing the results with several selected models, it reveals that the impact of APPC measures on regional short-term load is significant. Moreover, by considering the influence of APPC measures and avoiding the subjectivity of model parameter settings, the proposed load forecasting model can improve the accuracy of, and provide an effective tool for short-term load forecasting. Finally, some limitations of this paper are discussed.
Highlights
With increasing economic development and rapid promotion of urbanization, the industrial development mode characterized by heavy chemical industry and the coal-based energy consumption structure has made China’s environmental pollution problems increasingly serious
Sun et al forecasted the potential of electric energy substitution in China employing the particle swarm optimization support vector machine method, whose results reflected the influence of electric energy substitution policy on regional electricity demand [12]
Considering the long-term changes in power demand caused by industrial restructuring and electric energy substitution is not obvious in the short term, when analyzing the impact of APPC measures on regional short-term load, this paper mainly considers the impact of temporary shutdowns measure
Summary
With increasing economic development and rapid promotion of urbanization, the industrial development mode characterized by heavy chemical industry and the coal-based energy consumption structure has made China’s environmental pollution problems increasingly serious. Relevant scholars explored the main contents of APPC measures [7,8], finding that APPC measures affecting regional power demand can be summarized as cutting overcapacity, electric energy substitution, industrial transfer and temporary shutdowns. The implementation of these measures will affect the electricity demand by affecting the electricity consumption behavior of the power users. Some scholars have adopted different methods and samples to explore the relationship between regional electricity demand and APPC measures like cutting overcapacity, industrial transfer, electric energy substitution, and achieved rich results [13,14,15,16]
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