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Load forecasting using Active Demand
In this project we will simulate AD (Active Demand) and add them to a numerical example in order to forecast the load for a period of one month. Active Demand is the participation of small business and individual consumers in the energy price market. AD is the fact that each aggregator sends KWH price range to each customer, so that he forces him to increase or decrease his consumption depending on the price. The main challenge of this project is that AD is a new concept that wasn't used before, so we need to simulate AD and come up with an algorithm that takes it into consideration based on the previous forecasting method available. The method is done by decomposing the load into two components, the base which depends on seasonal patterns and the residual term which depends on stochastic fluctuations and the AD term.