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Day-ahead load forecasting using improved grey Verhulst model
Ariel Mutegi Mbae
,
Nnamdi I. Nwulu
Electrical and Electronic Engineering Science
University of Johannesburg
Research output
:
Contribution to journal
›
Article
›
peer-review
8
Citations (Scopus)
Overview
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Dive into the research topics of 'Day-ahead load forecasting using improved grey Verhulst model'. Together they form a unique fingerprint.
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Keyphrases
Power System
100%
Grey Verhulst Model
100%
Day-ahead Load Forecasting
100%
Market Players
75%
Grey Verhulst
75%
Financial Planning
50%
Forecasting Model
50%
Maintenance Scheduling
50%
Economic Dispatch
50%
Service Management
50%
Generating Unit
50%
System Maintenance
50%
Demand-Side Management Systems
50%
Unit Commitment
50%
Assessment Services
50%
Short-term Load Forecasting
50%
Spot Market
50%
Ancillary Services
50%
Energy Dispatch
50%
Dispatch System
50%
Daily Energy
50%
System Stability Assessment
50%
Management Reserve
50%
Optimal Generators
50%
System Security Assessment
50%
Design Methodology
25%
Natural Logarithm
25%
Prediction Accuracy
25%
Economic Policy
25%
Electricity Price
25%
Economically Viable
25%
Strategic Plan
25%
Economic Planning
25%
Mean Absolute Percentage Error
25%
Power Utility
25%
Model Use
25%
Data Demand
25%
Load Forecasting
25%
Load Demand
25%
Power Shortage
25%
Load Forecasting Models
25%
Exponential Weighted Moving Average
25%
Generation Investment
25%
Transmission Investment
25%
Policy Matters
25%
Short-term Power Load Prediction
25%
Forecast Studies
25%
Extreme Scenarios
25%
Electricity Load Forecasting
25%
Utility Data
25%
Engineering
Load Forecasting
100%
Power Engineering
80%
Market Player
60%
Economic Dispatch
40%
Energy Demand Management
40%
Generator Unit
40%
Unit Commitment
40%
Spot Market
40%
Ancillaries
40%
Electricity Price
20%
Power Utility
20%
Load Forecast
20%
Moving Average
20%
Natural Logarithm
20%
Social Sciences
Financial Planning
100%
Services Management
100%
Economic Planning
50%
Design Methodology
50%
Strategic Plan
50%
forecasting accuracy
50%