Optimal self-scheduling of hydro producer in the electricity market

This paper proposes an efficient method to solve the profit-based optimal self-scheduling of a hydroelectric company in the pool-based day-ahead electricity market by integrating cultural algorithm (CA) with feasible sequential quadratic programming (SQP). The proposed method is developed in such a...

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Bibliographic Details
Published in:Energy conversion and management Vol. 51; no. 12; pp. 2523 - 2530
Main Authors: Yuan, Xiaohui, Wang, Yunyan, Xie, Jun, Qi, Xiwen, Nie, Hao, Su, Anjun
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.12.2010
Elsevier
Subjects:
Algorithms
Applied sciences
Cultural algorithm
Economic data
Electric energy
Electricity
Energy
Energy economics
Exact sciences and technology
Freshwater
General, economic and professional studies
Hydro producer
Markets
Methodology. Modelling
Natural energy
Optimal self-scheduling
Optimization
Power plants
Quadratic programming
River basins
Searching
Sequential quadratic programming
Optimal self-scheduling
Sequential quadratic programming
Hydro producer
Cultural algorithm
ISSN:0196-8904, 1879-2227
Online Access:Get full text
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Summary:This paper proposes an efficient method to solve the profit-based optimal self-scheduling of a hydroelectric company in the pool-based day-ahead electricity market by integrating cultural algorithm (CA) with feasible sequential quadratic programming (SQP). The proposed method is developed in such a way that CA is applied as a based level search, which can give a good direction to the optimal global region, and a local search SQP is used as a fine-tuning to determine the optimal solution at the final. Finally, optimal self-scheduling of hydro company with several cascaded hydro plants along a river basin is used to illustrate the effectiveness of the proposed method. Results from the proposed method are compared with those obtained by other optimization methods in terms of solution precision. It is shown that the proposed method is capable of yielding higher quality solutions.
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ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2010.05.017