Analysing Effect of Solar Photovoltaic Production on Load Curves and their Forecasting B. Sinkovics, B. Hartmann 2018/04/20

Abstract

Increasing share of intermittent renewable energy sources has generated several issues for power system operators. One aspect of these is the unpredictability of volatile production, affecting day-ahead load forecasting on system level, which is a major challenge for transmission system operators to solve. The literature widely discusses the short- and medium-horizon forecasting methods for weather dependent renewable energy sources, and proposals have also been raised to solve the issue.
The aim of present paper is to estimate the effect of solar photovoltaic generation on the daily load curve of a national power system. To achieve this, current forecasting methods of transmission system operators are reviewed and evaluated. Then an own forecasting method is designed and implemented, based on historical load data from years where share of solar photovoltaics was neglectable. A learning algorithm is used for future predictions, using installed capacity and weather data. Finally, forecasted and actual load curves are compared, and effects of solar photovoltaic generation are estimated.

Authors and affiliations

B. Sinkovics1, B. Hartmann1
1 Centre for Energy Research. Hungarian Academy of Sciences. Budapest (Hungary)

Key words

Solar photovoltaic, load curve, forecasting, neural networks

References

[1] Annual report of Hungarian Energy and Public Utility Regulatory Authority (2008-2016), http://www.mekh.hu/download/7/15/40000/nem_engedelykoteles_es_hmke_%20beszamolo_2016.pdf (2017.09.22.)
[2] IRENA, Renewable Capacity Statistics, IRENA, 2017
[3] E. Almeshaiei, H. Soltan, A methodology for electric power load forecasting, Alexandria Engineering Journal, vol. 50., pp. 137-144., 2011
[4] M. Markou, E. Kyriakides, M. Polcarpou, 24-Hour Ahead Short Term Load Forecasting Using Multiple MLP, in Proc. DEMSEE 08, 2008
[5] H. Cho, Y. Goude, X. Brossat, Q. Yao, Modelling and Forecasting Daily Electricity Load via Curve Linear Regression, in Modeling and Stochatic Learning for Forecasting in High Dimensions, Springer, 2015
[6] B. Satish, K. S. Swarup, S. Srinivas és A. H. Rao, "Effect of temperature on short term load forecasting using an integrated ANN," Electric Power Systems Research, 2004.
[7] M. Abu-Et-Magd és R. Findlay, "A new approach using artificial neural network and time series models for short term load forecasting," 2003.
[8] K. Methaprayoon, W. J. Lee, S. Rasmiddatta, J. Liao és R. Ross, "Multi-Stage Artificial Neural Network Short-term Load Forecasting Engine with Front-End Weather Forecast," 2006.
[9] J. Bao, "Short-term Load Forecasting based on Neural network and Moving Average," 2002.
[10] L. Xu és W. J. Chen, "Short-Term Load Forecasting Techniques Using ANN," 2001.
[11] I. Erkmen és A. Topalli, "Four methods for short-term load forecasting using the benefits of artificial intelligence," Electrical Engineering, 2003.
[12] Y.-K. Wu, "Short-term forecasting for distribution feeder loads with consumer classification and weather dependent regression," 2006.
[13] L. Hernández, C. Baladrón, J. M. Aguiar, L. Calavia, B. Carro, A. Sánchez-Esguevillas, F. Pérez, Á. Fernández és J. Lloret, "Artificial Neural Network for Short-Term Load Forecasting in Distribution Systems," Energies, 2014.
[14] S. A. Ilic, S. M. Vukmirovic, A. M. Erdeljan és F. J. Kulic, "Hybrid artificial neural network system for short-term load forecasting," Thermal Science, 2012.
[15] A. Khwaja, M. Naeem, A. Anpalagan, A. Venetsanopoulos és B. Venkatesh, "Improved short-term load forecasting using bagged neural networks," Electric Power Systems Research, 2015.
[16] P. Ray, D. P. Mishra és R. K. Lenka, "Short-Term Load Forecasting by Artificial Neural Network," 2016.
[17] G. L. Prakash, K. Sambasivarao, P. Kirsali és V. Singh, "Short Term Load Forecasting for Uttarakhand using Neural Network and Time Series models," 2014.
[18] A. Bala, N. K. Yadav és N. Hooda, "Implementation of Artificial Neural Network for Short Term Load Forecasting," Current Trends in Technology and Science, 2014.
[19] N. Liu, V. Babushkin és A. Afshari, "Short-Term Forecasting of Temperature Driven Electricity Load Using Time Series and Neural Network Model," Journal of Clean Energy Technologies, 2014.
[20] F. Elakrmi1,N. Abu Shikhah "Electricity Load Forecasting - Science and Practices"
[21] A.K. Srivastava1, Ajay Shekhar Pandey and Devender Singh "Short-Term Load Forecasting Methods: A Review" International Conference on Emerging Trends in Electrical, Electronics and Sustainable Energy Systems (ICETEESES-16)
[22] Hao Yu, Bogdan M. ", LevenbergMarquardt Training Industrial Electronics Handbook" 2011