Abstract
This paper presents an efficient and optimization proficiency for minimization of fuel cost and losses of an electrical system in a completely deregulated power system. Single-side bidding and double-side bidding both cases are considered in this paper with the help of sequential quadratic programming (SQP) and evolutionary algorithm like firefly algorithm (FA) and cuckoo search algorithm (CSA) for checking the effectiveness of the presented approach. Modified IEEE 14 bus test system and modified IEEE 30 bus test system are considered for validating and analyzing the impact of proposed approach.
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Appendix
Appendix
Parameters of firefly and cuckoo search algorithm:
Sl. no. | Firefly algorithm | Sl. no. | Cuckoo search algorithm | ||
---|---|---|---|---|---|
Parameter | Value | Parameter | Value | ||
1 | No of firefly | 20 | 1 | No of nest | 25 |
2 | Randomness | 0.25 | 2 | Discovery rate | 0.25 |
3 | Firefly attractiveness | 0.20 | 3 | No of iteration | 300 |
4 | Absorption co-efficient | 1 | |||
5 | No of iteration | 300 |
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Subhojit Dawn, Sadhan Gope, Tiwari, P.K., Goswami, A.K. (2016). Optimal Demand-Side Bidding Using Evolutionary Algorithm in Deregulated Environment. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_38
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DOI: https://doi.org/10.1007/978-981-10-0448-3_38
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