Abstract
This paper presents a productive, coherent, and efficient approach to maximize the social welfare and minimize the system losses of an electrical system by incorporating power pool model in a fully deregulated power environment. Generation-side bidding and demand-side bidding both are considered in this work with the help of three evolutionary algorithms like particle swarm optimization (PSO) algorithm, artificial bee colony (ABC) algorithm, and BAT algorithm (BA) to check the potential and effectiveness of the presented approach. Investigation of the presented work clearly reveals that the increment in the demand-side bidding reduces the system losses and improves the voltage profile. Modified IEEE 14 bus and modified IEEE 30 bus test systems are considered for analyzing and validating the presented approach.
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Dawn, S., Gope, S. (2019). Maximization of Social Welfare by Enhancement of Demand-Side Bidding in a Deregulated Power Market. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 816. Springer, Singapore. https://doi.org/10.1007/978-981-13-1592-3_39
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DOI: https://doi.org/10.1007/978-981-13-1592-3_39
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