Optimum Bidding Strategy for Power Industry with Inelastic Demand using Water Cycle Algorithm

In a restructuring power industry, the essential principle of every generation company is to find the optimum bidding at any trading period. For an ISO, bidding strategy is a very interesting job. It is a complicated challenge as demand and generation uncertainty to maximize the profit of the partic...

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Bibliographic Details
Published in:Journal of the Institution of Engineers (India). Series B, Electrical Engineering, Electronics and telecommunication engineering, Computer engineering Electrical Engineering, Electronics and telecommunication engineering, Computer engineering, 2022, Vol.103 (3), p.929-937
Main Authors: Datta, Monalisa, Sarkar, Dipu
Format: Article
Language:English
Subjects:
Algorithms
Communications Engineering
Electric industries
Engineering
Hydrologic cycle
Networks
Optimization
Original Contribution
Power consumption
Statistical analysis
System effectiveness
Citations: Items that this one cites
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Summary:In a restructuring power industry, the essential principle of every generation company is to find the optimum bidding at any trading period. For an ISO, bidding strategy is a very interesting job. It is a complicated challenge as demand and generation uncertainty to maximize the profit of the participant in the market. This paper suggests an efficient data bidding technique for the maximization of benefit using Water Cycle Algorithm (WCA). This paper establishes the bidding model with the proper bidding coefficient for the IEEE-30 test bus, which seems to be gaining a reasonable profit. In addition, it evaluates the effectiveness of the proposed model on the IEEE-30 bus systems by assessing total profit, consumed bidding power, cost statistics and Market Clearing Price. To validate the efficacy of the suggested Water Cycle Algorithm model, the results from this study are compared with the bidding models of GWO, SFLA, FAGSA, and PSO. In order to demonstrate statistical analysis between different models, an ANOVA test is also conducted. The results reveal that the profit of the proposed model is higher with lesser iterations than that of the above said model and therefore achieves optimum efficiency.
ISSN:2250-2106
2250-2114
DOI:10.1007/s40031-021-00706-2