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Energies 2012, 5(11), 4430-4445; doi:10.3390/en5114430
Article

Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm

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Received: 14 September 2012; in revised form: 18 October 2012 / Accepted: 2 November 2012 / Published: 8 November 2012
(This article belongs to the Special Issue Hybrid Advanced Techniques for Forecasting in Energy Sector)
Download PDF [361 KB, uploaded 8 November 2012]
Abstract: The accuracy of annual electric load forecasting plays an important role in the economic and social benefits of electric power systems. The least squares support vector machine (LSSVM) has been proven to offer strong potential in forecasting issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. As a novel meta-heuristic and evolutionary algorithm, the fruit fly optimization algorithm (FOA) has the advantages of being easy to understand and fast convergence to the global optimal solution. Therefore, to improve the forecasting performance, this paper proposes a LSSVM-based annual electric load forecasting model that uses FOA to automatically determine the appropriate values of the two parameters for the LSSVM model. By taking the annual electricity consumption of China as an instance, the computational result shows that the LSSVM combined with FOA (LSSVM-FOA) outperforms other alternative methods, namely single LSSVM, LSSVM combined with coupled simulated annealing algorithm (LSSVM-CSA), generalized regression neural network (GRNN) and regression model.
Keywords: annual electric load forecasting; least squares support vector machine (LSSVM); fruit fly optimization algorithm (FOA); optimization problem annual electric load forecasting; least squares support vector machine (LSSVM); fruit fly optimization algorithm (FOA); optimization problem
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Li, H.; Guo, S.; Zhao, H.; Su, C.; Wang, B. Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm. Energies 2012, 5, 4430-4445.

AMA Style

Li H, Guo S, Zhao H, Su C, Wang B. Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm. Energies. 2012; 5(11):4430-4445.

Chicago/Turabian Style

Li, Hongze; Guo, Sen; Zhao, Huiru; Su, Chenbo; Wang, Bao. 2012. "Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm." Energies 5, no. 11: 4430-4445.


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