Proposing an Efficient Wind Forecasting Agent Using Adaptive MFDFA

Ebrahim Farjah

Abstract


High penetration by distributed energy sources (DERs) such as wind turbines (WT) and various types of consumer have
triggered a need for new approach to coordination and control strategy to meet the stochastic wind speed of the environment.
Here, a Multi Agent System is used to deliver strengthened, distributed, self-governing energy management of a multiple
micro-grid to adapt to changes in the environment. Prediction of wind speed is crucial for various aspects, such as control
and planning of wind turbine operation and guaranteeing stable performance of multiple micro-grids. The main purpose of the
proposed system is to account for wind variability in the energy management of a multiple micro-grid based on a hierarchical
multi-factor system. In this study, the prediction is based on adaptive multifractal detrended fluctuation analysis (Adaptive
MFDFA). A genetic algorithm is used to solve the optimization problem. Eventually, the proposed strategy is applied to a
typical MG which consists of micro turbine (MT), wind turbine (WT) and energy storage system (ESS). Evaluation of the
results show that the proposed strategy works well and can adapt the level of confidence interval in various situations.


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