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Due to expensive infrastructure and the difficulties in storage, supplyconditions of natural gas are different from those of other traditional energysources like petroleum or coal. To overcome these challenges, suppliercountries require take-or-pay agreements for requested natural gas quantities.These contracts have many pre-clauses; if they are not met due to low/highconsumption or other external factors, buyers must completely fulfill them. Asimilar contract is then imposed on distributors and wholesale consumers. It isthus important for all parties to forecast their daily, monthly, and annualnatural gas demand to minimize their risk. In this paper, a model consisting ofa modulated expansion in Fourier series, supplemented by deviations fromcomfortable temperatures as a regressor is proposed for the forecast of monthlyand weekly consumption over a one-year horizon. This model is supplemented by aday-ahead feedback mechanism for the forecast of daily consumption. The methodis applied to the study of natural gas consumption for major residential areasin Turkey, on a yearly, monthly, weekly, and daily basis. It is shown thatresidential heating dominates winter consumption and masks all othervariations. On the other hand, weekend and holiday effects are visible insummer consumption and provide an estimate for residential and industrial use.The advantage of the proposed method is the capability of long term projectionsand to outperform time series methods.

Forecasting Models for Daily Natural Gas Consumption Considering Periodic Variations and Demand Segregation