Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices |
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| Affiliation: | 1. Departamento de Estudios Urbanos y del Medio Ambiente, El Colegio de la Frontera Norte, Baja California, Mexico;2. Facultad de Ciencia Marinas, Universidad Autónoma de Baja California, Baja california, Mexico;1. Department of Computer Science and Engineering, SRM University AP, Amaravati, Andhra Pradesh-522502, India;2. Image and Video Processing Laboratory, Department of Computer Science and Engineering, International Institute of Information Technology, Bhubaneswar, Odisha-751003, India;3. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology (VSSUT), Burla, Sambalpur, Odisha- 768018, India;4. Department of Electrical and Computer Engineering, Concordia University, Montreal, QC H3G 1M8, Canada;1. Department of Energy Policy, Graduate School of Convergence Science, Seoul National University of Science & Technology, 232 Gongreung-Ro, Nowon-Gu, Seoul, 01811, Republic of Korea;2. Department of Future Energy Convergence, College of Creativity and Convergence, Seoul National University of Science & Technology, 232 Gongreung-Ro, Nowon-Gu, Seoul, 01811, Republic of Korea |
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| Abstract: | Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms. |
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| Keywords: | Influencer and defaulter mutation Optimization algorithms Price prediction |
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