# International Journal of Power and Energy Research

### Application and Comparison of Evolutionary Techniques for Forecasting the Hellenic Grid Electricity Load

Download PDF (1184.1 KB) PP. 139 - 149 Pub. Date: October 12, 2017

### Author(s)

**Stylianos. Sp. Pappas**^{*}

Department of Electrical and Electronic Engineering Educators, ASPETE – School of Pedagogical and Technological Education, N. Heraklion, 141 21 Athens, Greece

### Abstract

### Keywords

### References

[1] S. Sp. Pappas, L. Ekonomou, P. Karampelas, S. K. Katsikas and P. Liatsis, “Modeling of the grounding resistance variation using ARMA models,” Simulation Modelling Practice and Theory, vol. 16, no. 5, pp. 560-570, 2008.

[2] S. Sp. Pappas, V. C. Moussas and S. K. Katsikas, “Application of the multi-model partitioning theory for simultaneous order and parameter estimation of multivariate ARMA models,” International Journal of Modelling, Identification and Control (IJMIC), vol. 4, no. 3, pp. 242-249, 2008.

[3] S. Sp. Pappas, L. Ekonomou, D. Ch. Karamousantas, G. E. Chatzarakis, S. K. Katsikas and P. Liatsis, “Electricity demand loads modeling using autoregressive moving average (ARMA) models,” Energy, vol. 33, no. 9, pp. 1353-1360, 2008.

[4] S. Sp. Pappas, L. Ekonomou, V. C. Moussas, P. Karampelas and S. K. Katsikas, “Adaptive load forecasting of the Hellenic electric grid,” Journal of Zhejiang University SCIENCE A, pp. 1724-1730, 2008.

[5] S. Sp. Pappas, L. Ekonomou, P. Karampelas, D. C. Karamousantas, S. K. Katsikas, G. E. Chatzarakis and P. D. Skafidas, “Electricity demand load forecasting of the Hellenic power system using an ARMA model,” Electric Power Systems Research, vol. 80, issue 3, pp. 256-266, 2010.

[6] A. Tarsitano and I. L. Amerise, “Short-term load forecasting using a two-stage sarimax model,” Energy, vol 133, pp. 108-114, 2017.

[7] E. Erdem and J. Shi, “ARMA based approaches for forecasting the tuple of wind speed and direction,” Applied Energy, vol. 88, no. 4, pp. 1405-1414, 2011.

[8] M. H. Amini, A. Kargarian and O. Karabasoglu, “ARIMA-based decoupled time series forecasting of electric vehicle charging demand for stochastic power system operation,” Electric Power Systems Research, vol. 140, pp. 378-390, 2016.

[9] C. Yuan, S. Liu and Z. Fang, “Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model,” Energy, vol. 100, pp. 384-390, 2016.

[10] S-J. Huang and K-R. Shih, “Short-term load forecasting via ARMA model identification including non-Gaussian process considerations,” IEEE Trans on Power Systems, vol. 18, no. 2, pp. 673-679, 2003.

[11] N. Singh, S. R. Mohanty and R. D. Shukla, “Short term electricity price forecast based on environmentally adapted generalized neuron,” Energy, vol. 125, pp. 127-139, 2017.

[12] A. Badri, Z. Ameli and A. M. Birjandi, “Application of artificial neural networks and fuzzy logic methods for short term load forecasting,” Energy Procedia, vol. 14, pp. 1883-1888, 2012.

[13] X. Zhang, J. Wang and K. Zhang, “Short-term electric load forecasting based on singular spectrum analysis and support vector machine optimized by Cuckoo search algorithm,” Electric Power Systems Research, vol. 146, pp. 270-285, 2017.

[14] Y. Yaslan and B. Bican, “Empirical mode decomposition based denoising method with support vector regression for time series prediction: A case study for electricity load forecasting,” Measurement, vol. 103, pp. 52-61, 2017.

[15] S. Brodowski, A. Bielecki and M. Filocha, “A hybrid system for forecasting 24-h power load profile for Polish electric grid,” Applied Soft Computing, vol. 58, pp. 527-539, 2017.

[16] M. Q. Raza, M. Nadarajah, D. Q. Hung and Z. Baharudin, “An intelligent hybrid short-term load forecasting model for smart power grids,” Sustainable Cities and Society, vol. 31, pp. 264-275, 2017.

[17] Guo-Feng Fan, Li-Ling Peng, Wei-Chiang Hong and Fan Sun, “Electric load forecasting by the SVR model with differential empirical mode decomposition and auto regression,” Neurocomputing, vol. 173, part 3, pp. 958-970, 2016.

[18] D. G. Lainiotis, “Optimal adaptive estimation: Structure and parameter adaptation,” IEEE Trans on Automatic Control, AC-16, pp. 160-170, 1971.

[19] D. G. Lainiotis, “Partitioning: A unifying framework for adaptive systems I: Estimation,” Proc. of the IEEE, vol. 64, no. 8, 1976, pp. 1126-1143.

[20] D. G. Lainiotis, “Partitioning: A unifying framework for adaptive systems II: Control,” Proc. of the IEEE, vol. 64, no. 8, 1976, pp.1182-1198.

[21] S. Sp. Pappas, G. E. Chatzarakis, C. C. Pappas and V. C. Moussas, “A Hybrid model for wind speed forecasting using arma models and support vector macines (svm),” 5th International Conference on Experiments/Process/System Modeling/Simulation/Optimization, 2013.

[22] G. Beligiannis, L. Skarlas and S. Likothanassis, “A generic applied evolutionary hybrid technique,” IEEE Signal Processing Magazine, vol. 21, no. 3, pp. 28-38, 2004.

[23] D. G. Lainiotis, S. K. Katsikas and S. D. Likothanassis, “Adaptive deconvolution of seismic signals: performance, computational analysis, parallelism,” IEEE Trans on Acoustics, Speech, and Signal Processing, vol. 36, no. 11, pp. 1715-1734, 1988.

[24] L. Ekonomou and D. S. Oikonomou , “Application and comparison of several artificial neural networks for forecasting the Hellenic daily electricity demand load,” Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases, 2008, pp. 67-71.

[25] P. Karampelas, V. Vita, C. Pavlatos, V. Mladenov and L. Ekonomou, “Design of artificial neural network models for the prediction of the Hellenic energy consumption,” 10th Symposium on Neural Network Applications in Electrical Engineering (NEUREL 2010), Belgrade, Serbia, 2010, pp. 41-44.

[26] Hellenic Ministry of Economy and Finance, available at www.mnec.gr.

[27] Eurostat, available at http://ec.europa.eu/eurostat/statistics-explained/index.php/Consumption_of_energy.

[28] PPC S.A., Annual electrical energy's statistical and economical data. Hellenic Public Power Corporation S.A., Athens, Greece, 2017.