1. Long-term load forecasting based on gravitational search algorithm
- Author
-
Soheil Derafshi Beigvand and Hamdi Abdi
- Subjects
Statistics and Probability ,Mathematical optimization ,Heuristic (computer science) ,020209 energy ,Load forecasting ,Gravitational search algorithm ,General Engineering ,Particle swarm optimization ,02 engineering and technology ,Function (mathematics) ,Least squares ,Term (time) ,Artificial Intelligence ,0202 electrical engineering, electronic engineering, information engineering ,Algorithm ,Mathematics - Abstract
This paper presents a novel Long-Term Load Forecasting (LTLF) technique based on the new heuristic method, namely Gravitational Search Algorithm (GSA). The objective of the suggested approach is establishing a more accurate LTLF model to minimize the average error of modeling. In order to estimate different fitting functions based on the proposed algorithm, two different case studies include Egyptian and Kuwaiti grids are selected. Also, the results are compared with a conventional approach, namely Least Squares (LS) method, and Particle Swarm Optimization (PSO) as a heuristic algorithm, to select the best LF model. Finally, based on the average and maximum errors arise from the estimations as a decision condition; the best function is selected for the LTLF problem.
- Published
- 2016
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