A load predictive energy management system for supercapacitor-battery hybrid energy storage system in solar application using the Support Vector Machine

Applied Energy

Volumn 137, Issue , 2015, Pages 588-602

  Chia, Yen Yee ^a   Lee, Lam Hong ^b   Shafiabady, Niusha ^a   Isa, Dino ^a  

^a UNIVERSITY OF NOTTINGHAM MALAYSIA CAMPUS   (Malaysia)

^b QUEST INTERNATIONAL UNIVERSITY PERAK   (Malaysia)

Author keywords

Battery; Load prediction; Solar application; Supercapacitor; Support Vector Machine (SVM)

Indexed keywords

CAPACITORS; COST REDUCTION; ELECTRIC BATTERIES; ENERGY STORAGE; FORECASTING; HYBRID SYSTEMS; MATHEMATICAL MODELS; MEAN SQUARE ERROR; POWER ELECTRONICS; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; SECONDARY BATTERIES; SOLAR ENERGY; SOLAR POWER GENERATION; STORAGE MANAGEMENT; SUPPORT VECTOR MACHINES; VECTORS;

BATTERY; COMPLEMENTARY CHARACTERISTICS; HYBRID ENERGY STORAGE SYSTEMS; LOAD PREDICTIONS; SOLAR APPLICATIONS; SQUARED CORRELATION COEFFICIENTS; SUPER CAPACITOR; SUPPORT VECTOR CLASSIFICATION;

ENERGY MANAGEMENT SYSTEMS;

CLASSIFICATION; COST ANALYSIS; ENERGY PLANNING; ENERGY RESOURCE; MANAGEMENT PRACTICE; NUMERICAL MODEL; RENEWABLE RESOURCE; SOLAR POWER;

EID: 84912117174     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2014.09.026     Document Type: Article

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