This paper presents a model that can be used to estimate the annual peak demand in electricity consumption for small sized electric utilities. The developed model was used to investigate the influence of econometric variables on the power demand of N. Cyprus. Utilizing historical annual databases, analysis of variance (ANOVA), and the statistical methods, it was found that number of customers, price of electricity, number of tourists, population, as well as heating degree days correlate with the annual peak demand with R-2 = 0.995. The performance of the model was measured using mean absolute scaled error (MASE) and mean absolute percentage error (MAPE) for in-sample (1992-2010) and out-of-sample (2011-2013) data. Also, to ensure the validity of the outcomes, models were regenerated by decreasing the in-sample data (i.e. increasing the out of sample data) back to five consecutive years and MAPE and MASE calculations were repeated. The results indicated that the model, using the above-mentioned parameters as regressors, has very strong predictive ability and can be used to estimate the annual peak demand. The combination of peak demand, base demand and energy consumption models can be utilized as a useful technique for the purpose of resource planning for small sized utilities. (C) 2015 Elsevier Ltd. All rights reserved.