The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON POWER SYSTEMS
Transactions ID Number: 54-171
Full Name: Surekha Paneerselvam
Position: Ph.D. Candidate
Age: ON
Sex: Female
Address: Department of EEE, PSG College of Technology, Coimbatore, Tamilnadu
Country: INDIA
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E-mail address: surekha_3000@yahoo.com
Other E-mails: surekha3000@gmail.com
Title of the Paper: Unit Commitment and Economic Load Dispatch using Self Adaptive Differential Evolution
Authors as they appear in the Paper: Surekha P, Archana N, Sumathi S
Email addresses of all the authors: surekha_3000@yahoo.com, ss.author@gmail.com
Number of paper pages: 11
Abstract: Unit Commitment (UC) and Economic load dispatch (ELD) are the most significant research areas in power systems that optimize the total production cost of the predicted load demand. The UC problem determines a turn-on and turn-off schedule for a given combination of generating units, thus satisfying a set of dynamic operational constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the load demands of customers. The first phase in this project is to economically schedule the distribution of generating units using Genetic Algorithm (GA) and the second phase is to determine optimal load distribution for the scheduled units using Self Adaptive Differential Evolution (SADE) algorithm. GA is applied to select and choose the combination of generating units that commit and de-commit during each hour. These pre-committed schedules are optimized by SADE thus producing a global optimum solution with feasible and effective solution qua!
lity, minimal cost and time and higher precision. The effectiveness of the proposed techniques is investigated on two test systems consisting of six and ten generating units and the experiments are carried out using MATLAB R2008b software. Experimental results prove that the proposed method is capable of yielding higher quality solution including mathematical simplicity, fast convergence, diversity maintenance, robustness and scalability for the complex UC-ELD problem.
Keywords: Unit commitment, Economic load dispatch, Genetic algorithm, Self adaptive differential evolution, Computational time, IEEE 30 bus system
EXTENSION of the file: .doc
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