A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Orike, S.
- Design of Fuzzy Logic Load Intelligent Frequency Controller for Interconnected Power System Network
Authors
1 University of Port Harcourt, NG
2 Scientific Equipment Development Institute (SEDI), Enugu, NG
3 Department of Computer Engineering, Rivers State University, Port Harcourt, NG
Source
Fuzzy Systems, Vol 10, No 10 (2018), Pagination: 230-236Abstract
The problem of controlling the frequency of a system under load has been an issue in electrical power systems. Considering the inter-connected network arrangement, a change in load causes variations on the line frequency together with tie line power as well. This work is aimed at bringing to minimum the frequency variations and the power of the tie line and also make sure that the errors due to the steady state of the network are brought to nearly zero. This investigation attempted to design a fuzzy logic load frequency intelligent controller for inter-connected power system that will achieve the above aim. Simulations of this design was carried out in MATLAB Simulink environment. The best result from simulations was analyzed based on inclusion of all the components required. The results showed that the fuzzy logic intelligent controller exhibited the best frequency settling time of 3.5s.
Keywords
Area Control Error, Fuzzy Logic Controllers, Load Frequency Control, Inter-connected Power System, Tie Line Power.
References
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- A Pricing Model for the Nigerian Electricity Transmission Using Artificial Neural Network
Authors
1 Department of Electrical Engineering, Rivers State University, Nkpolu-Oroworukwo, Port Harcourt, NG
Source
Artificial Intelligent Systems and Machine Learning, Vol 11, No 12 (2019), Pagination: 225-233Abstract
For the restructuring of Nigeria’s power sector to be effective, efforts must be made to evolve an excellent pricing methodology that will economically be able to accommodate disintegrated units like generating, transmitting and distributing/retailing units. This work is aimed at developing an improved electricity transmission pricing scheme for the Nigerian Network using Artificial Neural Network. A model based on artificial neural network for improved electricity transmission pricing for the Nigerian Network was developed in order to forecast the transmission price for a longer period of time. The performance of the neural network model was evaluated by applying the actual transmission pricing data from Transmission Company of Nigeria to predict the prices. Raw data was collected from Transmission Company of Nigeria, Port-Harcourt district. The data was trained, tested and validated on the MATLAB/Simulink environment. Forecast results revealed that the model performed very well with a mean absolute percentage error of 0.09%, an average mean error of 0.5 and a regression value of 0.99. It was concluded that the improved and modified transmission use of system pricing is the best pricing method which will be acceptable to consumers and also ensure recovery of transmission cost in Nigeria. It was recommended that Artificial Intelligent-based techniques (ANN) in particular, must be implemented for long-term improved electricity transmission pricing forecast for the Transmission Company of Nigeria.