{'fraction_non_alphanumeric': 0.01745877788554801, 'fraction_numerical': 0.0, 'mean_word_length': 5.254545454545455, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Forecasting Turkey's Natural Gas Consumption by Using Time Series Methods

Strategic energy planning processes, which include natural gas demand, are commonly used as a tool to design the regional and local energy system and encourage renewable energy development. The oil and natural gas market plays a very important role in the strategic energy planning process in a country. In recent years, natural gas consumption has become the fastest growing primary energy source in Turkey. In this study, natural gas consumptions of Turkey in different time periods are forecasted by using various time series methods such as exponential smoothing, winters' forecasting and Box-Jenkins methods. These methods are compared with each other in terms of the superiority in forecasting performance. The findings reveal that in the yearly data set, double exponential smoothing model outperforms the other alternative forecasting models. On the other hand, in term of monthly data set, SARIMA model provides the better results than the others.