Long term electricity demand forecasting using autoregressive integrated moving average model: Case study of Morocco

Abstract

Electricity demand forecasting is vitally important for power production companies. It has many applications, including energy production scheduling, maintenance and operation of electric network, elaboration of accurate investment and development plans for transmission and distribution networks, negotiation of PPAs (Power Purchase Agreements) and purchasing fuels at optimal costs. Over the last decades, a large variety of mathematical models have been developed for load forecasting, including short-term, medium-term and long term models. This article aims at developing a long term load forecasting model for Moroccan electric grid, using Auto-Regressive Moving Average model. The results are compared to official forecasts of ONEE (Office National de l'Eau et d'Electrcité). This model will be a useful tool for decision makers, to better design investment plans and strategies, aiming at reducing the impact of energy bill on Moroccan economy.