A novel power-driven fractional accumulated grey model and its application in forecasting wind energy consumption of China


Autoři: Peng Zhang aff001;  Xin Ma aff002;  Kun She aff001
Působiště autorů: School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China aff001;  School of Science, Southwest University of Science and Technology, Mianyang, China aff002;  State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, China aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0225362

Souhrn

Wind energy is one of the most important renewable resources and plays a vital role in reducing carbon emission and solving global warming problem. Every country has made a corresponding energy policy to stimulate wind energy industry development based on wind energy production, consumption, and distribution. In this paper, we focus on forecasting wind energy consumption from a macro perspective. A novel power-driven fractional accumulated grey model (PFAGM) is proposed to solve the wind energy consumption prediction problem with historic annual consumption of the past ten years. PFAGM model optimizes the grey input of the classic fractional grey model with an exponential term of time. For boosting prediction performance, a heuristic intelligent algorithm WOA is used to search the optimal order of PFAGM model. Its linear parameters are estimated by using the least-square method. Then validation experiments on real-life data sets have been conducted to verify the superior prediction accuracy of PFAGM model compared with other three well-known grey models. Finally, the PFAGM model is applied to predict China’s wind energy consumption in the next three years.

Klíčová slova:

Alternative energy – Differential equations – Humpback whales – Oils – Optimization – Wind – Wind power


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2019 Číslo 12