Profit based Unit Commitment using Improved Pre-Prepared Demand (IPPD) Table and Memory Management Algorithm (MMA)
S. F. Syed Vasiyullah1, M. Gopalakrishnan2
1S. F. Syed Vasiyullah, Asst. Prof., EEE, A.M.S College of Engineering, Chennai,Tamil Nadu, India.
2Dr. M. Gopalakrishnan, Professor, Department of EEE, Sri Venteshwara College of Engineering, Sriperumbudur, Tamil Nadu, India.
Manuscript received on 30 January 2015 | Revised Manuscript received on 12 February 2015 | Manuscript Published on 28 February 2015 | PP: 29-34 | Volume-4 Issue-9, February 2015 | Retrieval Number: I1974024915/15©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, Improved Pre-prepared Power Demand (IPPD) table and Memory management algorithm is used to solve Profit Based Unit Commitment (PBUC) problem. In conventional market, Unit commitment (UC) is the process of determining the On/Off status of the generating unit to meet forecasted load by satisfying certain operating constraints that minimize the operating cost. In restructured power market, unit commitment involves commitment of generating unit of an Individual Generation company (GENCO) for maximization of his profit rather than satisfying the power demand of its consumer. In this proposed method, PBUC problem is solved in two steps. In first step unit commitment scheduling is done by IPPD table and then the problem of fuel cost and revenue function is done by Memory Management Algorithm. The IPPD table gives the information of committed unit for any predicted power demand and information about forecasted price to reduce complexity in the problem during calculation. Memory management algorithm uses Best fit and Worst bit allocation for scheduling the generator in order to receive maximum profit by considering power and reserve generation. This approach has been tested on a 3 unit system using MATLAB and the simulation result is compared with the result of previous published method obtained by other optimizing technique.
Keywords: Deregulation Improved Pre-Prepared Power demand (IPPD) table, Generation Company (GENCO), Memory Management Algorithm (MMA), and Profit Based Unit Commitment (PBUC).
Scope of the Article: Management Algorithm