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Rajesh, V.
- Locational Marginal Pricing of GENCOs in a Deregulated Energy Market
Abstract Views :237 |
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Authors
Affiliations
1 Department of Electrical and Electronics Engineering, SRM University, SRM Nagar, Kattankulathur − 603 203, Kancheepuram, Chennai, Tamil Nadu, IN
1 Department of Electrical and Electronics Engineering, SRM University, SRM Nagar, Kattankulathur − 603 203, Kancheepuram, Chennai, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 44 (2016), Pagination:Abstract
Background/Objectives: In this paper a clear focus on pricing of the GENeration COmpanies (GENCO) has been dealt with. GENCO participate in day-ahead power pool trading to maximize their profit in the energy market. Methods/Statistical Analysis: Since the self-scheduling problem is a highly non-linear, non-convex mixed-integer optimization problem, conventional methods for optimizing may suffer excessive computational burden. This paper incorporates the method for determining the Locational Marginal Pricing with and without congestion due to over load and gives an observation of the ways to overcome this critical situation in the deregulated energy market using Power World Simulator (PWS) software for 3-bus system and IEEE 9-bus system Findings: In the case of Locational Marginal Pricing (LMP) forecasting, the main challenge is to forecast the volatile prices accurately in a day-ahead market. The PWS software used for test cases considered indicates that the output information is obtained at the short time frame which ultimately reduces the computation burden existed earlier in the conventional method Applications: The proposed methodology will be helpful for the generating company to forecast the Locational Marginal Pricing for both with and without congestion due to over load and rescheduling of generators will be carried out accordingly in the deregulated energy market within a very short time frame.Keywords
Congestion, Deregulated Market, GENeration COmpanies (GENCO), Locational Marginal Pricing (LMP).- A New Pixel Level Image Fusion Method based on Genetic Algorithm
Abstract Views :194 |
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Authors
D. Bhavana
1,
V. Rajesh
1
Affiliations
1 Department of Electronics and Communications Engineering, K L University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
1 Department of Electronics and Communications Engineering, K L University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 9, No 45 (2016), Pagination:Abstract
Background/Objectives: To propose a new fusion technique for combining optical and IR images and validate the proposed technique with the existing techniques using entropy as an evaluating measure. Methods/Statistical Analysis: In this paper we propose a new pixel level fusion method using Continuous Genetic Algorithm (CGA) using Heuristiccrossover for reproduction. Findings: Pixel level Fusion methods are computationally less complex and converge quickly. The proposed approach is applied on multispectral images which are used in applications like multispectral face recognition, Medical imaging, Remote Sensing etc. The proposed algorithm requires less memory space and has less computational complexity. Conclusion/Improvements: An increase in the entropy of the fused image indicates that there is an increase in the overall information content. The proposed technique is implemented on a set of visual and thermal images and an increase in the entropy value of the fused image is observed.Keywords
Continuous Genetic Algorithm, Entropy, Heuristic Crossover, Image Fusion, Pixel Level Fusion.- Implementation of Plateau Histogram Equalization Technique on Thermal Images
Abstract Views :161 |
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Authors
Affiliations
1 Department of ECE, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of Mechanical Engineering, KL University, Guntur - 522502, Andhra Pradesh, IN
1 Department of ECE, KL University, Guntur - 522502, Andhra Pradesh, IN
2 Department of Mechanical Engineering, KL University, Guntur - 522502, Andhra Pradesh, IN