Electrical energy consumption optimization for fuel and energy complex facilities based on the fuzzy logic model and artificial neural networks
Keywords:
fuel and energy complex, electric energy consumption, optimization, active power losses, fuzzy neuron networks, simulation modeling, energy efficiencyAbstract
The model of electric power consumption dynamic at the fuel and energy complex has been suggested which possesses properties of forecasting and generation of control actions. The model operation is based on the combined fuzzy neuron networks. The model allows to increase the accuracy of indexes in estimating of future periods for optimization problems solution in comparison to the existing realizations based on regression models. The paper has determined the objective function of optimization on minimum losses of active power together with limitations typical for fuel and energy complex facilities; suggested modified Newton-Raphson algorithm based on fuzzy neuron networks; obtained efficiency assessment of the developed algorithms applied to the simulation models of FECF functioning for short-, medium- and long-term forecasting.
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DOI: https://doi.org/10.26782/jmcms.spl.8/2020.04.00019
5. Rutskov A.L., Burkovsky V.L., Sidorenko E.V. Optimization of electric power systems using fuzzy neural network algorithms // Journal of mechanics of continua and mathematical sciences. 2020. Vol. spl8(1). P. 264-276.
DOI: https://doi.org/10.26782/jmcms.spl.8/2020.04.00020
6. Çevik H.H., Çunkaş M. Short-term load forecasting using fuzzy logic and ANFIS // Neural Computing and Applications. 2015. Vol. 26(6). P.1355–1367.
DOI: https://doi.org/10.1007/s00521-014-1809-4
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Copyright (c) 2020 A.L. Rutskov, Ya.P. Fedorov and L.V. Volkov
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
