Abstract
An accurate power system load forecasting (PSLF) tool is an indispensable part of modern day power systems planning, operation, control, and sustainable development. The consumer behaviors which eventually changes the demand in the electric power system is highly driven by thermal inertia caused by different climatic factors. Hence, the accuracy of a PSLF tool is highly reliant on the integrated climatic factors. This paper proposes an alike day data (ADD) improved fuzzy logic comptroller (FLC) model for week ahead power system load forecasting. Here, a new ADD is utilized to integrate different climatic factors in the forecasting process. Furthermore, the new ADD scheme also targeted to improve the forecasting abilities of the proposed FLC. The study is done in Assam, a Northeastern state of India and the proposed model is employed for the week ahead power load forecasting. The performance of the proposed model is compared with conventional FLC without ADD scheme. The empirical findings affirm the supremacy of the proposed model over conventional FLC.
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Acknowledgment
We the authors are very much grateful to SLDC, Guwahati, Assam (India) for sharing their data with us.
Authors would like to thank TEQIP III. NIT Silchar for all the supports for carrying out the presented work in this paper.
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Barman, M., Choudhury, N.B.D., Behera, S. (2020). An Alike Day Data Improved Fuzzy Logic Controller for Week Ahead Power System Load Forecasting. In: Dawn, S., Balas, V., Esposito, A., Gope, S. (eds) Intelligent Techniques and Applications in Science and Technology. ICIMSAT 2019. Learning and Analytics in Intelligent Systems, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-42363-6_63
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DOI: https://doi.org/10.1007/978-3-030-42363-6_63
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