Impact of wind speed modelling on the predictive reliability assessment of wind‐based microgrids

Abstract

Power utilities have shown great interest in utilising renewable energy resources for various environmental and economic reasons. However, the modelling and integration of conventional and renewable resources into electric microgrids will increase the complexity of microgrid reliability analyses. Therefore, an accurate reliability assessment of power distribution systems is expected to become a major challenge in the future. More extensive research must be conducted to improve system reliability assessment techniques and determine the impact of increased penetration of renewable resources. In this work, the reliability of wind-based electric microgrids was evaluated using a Markov model, taking the intermittent nature of wind speed into account. The effects of different wind speed modelling techniques based on the auto-regressive moving average method, Markov model, and probability distribution function on the reliability analysis of electric microgrids were assessed. The Roy Billinton test system was used to illustrate the analysis and evaluate the different load and system indices.

Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty

“…The uncertainty of wind and solar power needs to be modeled to use for the current power generation system [13,14]. There are many models proposed to deal with the uncertainty of wind power generation so that the UC of all the generating units becomes possible.…”

A Technical Review on Reliability and Economic Assessment Framework of Hybrid Power System with Solar and Wind Based Distributed Generators

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