FCM Clustering-ANFIS-based PV and wind generation forecasting agent for energy management in a smart microgrid

FCM Clustering-ANFIS-based PV and wind generation forecasting agent for energy management in a smart microgrid

This paper proposes a PV and wind output power generation forecasting agent for a multi-agent-based energy management system (EMS) in a smart microgrid. The microgrid EMS requires both generation forecast and load forecast to provide effective dispatch strategies. The efficiency of the EMS significa...

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Bibliographic Details
Main Authors: A Sujil, Rajesh Kumar, Ramesh C Bansal
Format: Article
Language:English
Published: Wiley 2019-06-01
Series:The Journal of Engineering
Subjects:
fuzzy logic
optimisation
inference mechanisms
distributed power generation
load forecasting
fuzzy reasoning
neural nets
pattern clustering
energy management systems
adaptive systems
fuzzy set theory
photovoltaic power systems
wind power plants
power engineering computing
learning (artificial intelligence)
multi-agent systems
smart microgrid
wind output power generation forecasting agent
multiagent-based energy management system
microgrid ems
load forecast
effective dispatch strategies
forecasting accuracy
adaptive neuro-fuzzy inference system
pv generation forecasting agent
microgrid energy management
fuzzy logic inference
pv historical data
historical wind data
hybrid optimisation algorithm-based anfis model
fcm clustering-anfis
neural network
linguistic expression function
fuzzy c means clustering
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9323

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https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9323

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