A hybrid ARMA-Legendre polynomial neural network and evolutionary H-infinity filter for the prediction of electricity market clearing price

2015 ◽  
Vol 6 (4) ◽  
pp. 359
Author(s):  
Sujit Kumar Dash
Keyword(s):  
Neural Network ◽  
Electricity Market ◽  
Legendre Polynomial ◽  
Market Clearing ◽  
H Infinity ◽  
Polynomial Neural Network ◽  
Market Clearing Price

Fuzzy Neural Network Market Clearing Power Price Forecasting Based on K-Means Clustering

2011 ◽  
Vol 121-126 ◽  
pp. 2035-2039 ◽  
Author(s):  
Xian Min Wei
Keyword(s):  
Neural Network ◽  
Prediction Accuracy ◽  
Fuzzy Neural Network ◽  
Fuzzy Inference ◽  
Complex Structure ◽  
Price Forecasting ◽  
Market Clearing ◽  
Market Clearing Price ◽  
Fuzzy Neural ◽  
Long Time

Normalized fuzzy neural network has complex structure, long-time study and other shortcomings. For these shortcomings, this paper applies an improved fuzzy neural network to predict market clearing price. The model is simple, just by k-means clustering to determine the number of fuzzy inference layer nodes, and with strong applicability, higher prediction accuracy.

scholarly journals Assessment Of Market Clearing Price And Social Welfare In A Competitive Electricity Market

2013 ◽  
pp. 74-82
Author(s):  
Prasanta Kumar Pany ◽  
Sakti Prasad Ghoshal
Keyword(s):  
Power Systems ◽  
Social Welfare ◽  
Electricity Market ◽  
Load Level ◽  
Operating Conditions ◽  
Energy Prices ◽  
Market Clearing ◽  
Transmission Investment ◽  
Number Of Factors ◽  
Market Clearing Price

In an open-access environment, transmission constraints can result in different energy prices throughout the network. These prices are dependent on a number of factors such as the system load level, generating unit bid, demand unit bid, network topology and security limits imposed on the transmission network due to thermal, voltage and stability considerations. Computing these energy prices at all buses in large networks under given system operating conditions can be time consuming. This paper describes some simple methodology based on the computer programs to calculate saving , worth of transmission transaction, market clearing price, social welfare, transaction cost, locational marginal pricing, transmission capacity cost at selected zones for a given period. These information for energy prices can be used not only to improve the efficient usage of power grid but also to design a reasonable pricing structure of power systems or to provide economic signals for generation or transmission investment.

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