scholarly journals Generator scheduling under competitive environment using Memory Management Algorithm

2013 ◽  
Vol 52 (3) ◽  
pp. 337-346 ◽  
Author(s):  
A. Amudha ◽  
C. Christober Asir Rajan
2017 ◽  
Vol 66 ◽  
pp. 97-114 ◽  
Author(s):  
Abdelhak Mesbah ◽  
Jean-Louis Lanet ◽  
Mohamed Mezghiche

2011 ◽  
Vol 403-408 ◽  
pp. 3965-3972
Author(s):  
A. Amudha ◽  
C.Christober Asir Rajan

As the electrical industry restructures, many of the traditional algorithms for controlling generating units need modification or replacement. In the past, utilities had to produce power to satisfy their customers with the objective to minimize costs and actual demand/reserve were met. But it is not necessary in a restructured system. The main objective of restructured system is to maximize their own profit without the responsibility of satisfying the forecasted demand. The PBUC is a highly dimensional mixed-integer optimization problem, which might be very difficult to solve. Hence a new software tool is developed in java using Memory Management Algorithm (MMA) by Best Fit (BF) & Worst Fit (WF) allocation for web based application. The proposed method MMA using Best Fit & Worst Fit allocation for generator scheduling in order to receive the maximum profit by considering the softer demand. Also this method gives an idea regarding how much power and reserve should be sold in markets. The Madurai Power Grid Corporation in Tamil Nadu, India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different power systems consisting of 3, 10and 7 generating units. Simulations of the proposed are carried out for maximizing profit and computation time and results are compared with existing methods.


2013 ◽  
Vol 303-306 ◽  
pp. 2329-2332 ◽  
Author(s):  
Jun Yi Li ◽  
Jing Yu Chen ◽  
Anthony S. Fong

Java is a very popular Object-oriented programming (OOP) language because of its platform independent and automatic memory release mechanism (or garbage collection). However, garbage collection also speeds CPU time and should be done after careful consideration. In the paper, memory usage behavior and run-time object characteristics, including heap and object size, object age and access frequency, are studied using several commercial benchmarks. The profiler design method and experiment detail are represented in the paper. The runtime object characteristics are very important to guide the employment of different memory management algorithm.


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