Total views : 153
Cost Effective Hydrothermal Scheduling with Practical Constraint using Artificial Bee Colony Algorithm
Objective: Rapidly increasing economic development as well as energy consumption has raised great concern on resourceconservation. This focuses on finding cost effective dispatch to hydrothermal power systems. Method/Approach: The hydrothermal scheduling is formulated as a non-convex optimization problem subjected to the prohibited discharge zone of hydro reservoir, ramp rate limit of the thermal unit along with usual equality and inequality constraints. The Artificial Bee Colony algorithm is adopted as an optimization tool in which four different selection processes is employed that carry out exploration and exploitation process together in search space. Findings: The proposed methodology is implemented on the standard test system that comprises four cascaded hydro and three thermal units. As, hydro discharge and thermal real power generation are the decision variables a solution repair mechanism is adopted to handle water continuity and power balance constraints. Thus, the proposed ABC algorithm ascertains newfangled cost effective dispatch with practical constraint which is better than the previous reports in term of solution quality improvement. The proposed method seems to be a promising optimization tool for the utilities, thereby modifying their operating strategies to generate an electrical energy at minimum energy cost. Thus a strategic balance is derived among economic development, energy cost and environmental sustainability. Originality/Improvements: The system parameters are nicely incorporated in the proposed algorithm and strategic balance between exploration and exploitation is obtained perfectly. Hence, the ABC algorithm has converged fast and discovered best cost effective generation schedule. The effects of prohibited discharge zone and ramp rate limit are analyzed and also the values seem to be considered as practical value.
Artificial Bee Colony, Cost Effective Dispatch, Hydrothermal Generation Schedule, Prohibited Discharge Zone, Ramp-Rate.
- Kothari DP, Dhillon JS. Power system optimization. 2nd ed. New Delhi, India: PHI Learning Private Limited; 2011.
- Blum C, Roli A. Meta-heuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys. 2003 Sep; 35(3):268–308. Crossref
- Wong KP, Wong YW. Short-term hydrothermal scheduling. Part 1: Simulated annealing approach. Proceeding of Generation Transmission Distribution. 1994 Sept; 141(5):497– 501. Crossref
- Orero SO, Irving MR. A Genetic Algorithm modeling framework and solution technique for short term optimal hydrothermal scheduling. IEEE Transactions on Power Systems. 1998 May; 13(2):501–18. Crossref
- Hota PK, Chakrabarti R, Chattopadhyay PK. Short-term hydrothermal scheduling through evolutionary programming technique. Electric Power System Research. 1999 Nov; 52(2):189–96. Crossref
- Mandal KK, Basu M, Chakraborty N. Particle Swarm Optimization technique based short-term hydrothermal scheduling. Applied Soft Computing. 2008 Sep; 8(4):1392–9. Crossref
- Mandal KK, Chakraborty N. Differential Evolution technique based short term economic generation scheduling of hydrothermal systems. Electric Power System Research. 2008 Nov; 78(11):1972–9. Crossref
- Nguyen TT, Vo DA, Truong AV. Cuckoo search algorithm for short-term hydrothermal scheduling. Applied Energy. 2014 Nov; 132(1):276–87. Crossref
- Wong SYW. Hybrid simulated annealing/Genetic Algorithm approach to short-term hydrothermal scheduling with multiple thermal plants. Electric Power and Energy System. 2001 Oct; 23(7):566–75.
- Sivasubramani S, Shanti Swarup K. Hybrid DE–SQP algorithm for non-convex short term hydrothermal scheduling problem. Energy Conversion and Management. 2011 Jan; 52(1):757–61. Crossref
- Fua X, Li A, Wang L, Ji C. Short-term scheduling of cascade reservoirs using an immune algorithm-based Particle Swarm Optimization. Computers and Mathematics with Applications. 2011 Sep; 62(6):2463–71. Crossref
- Dubey HM, Pandit M, Panigrahi BK. Cuckoo search algorithm for short term hydrothermal scheduling. Power Electronics and Renewable Energy Systems. 2014 Nov; 326:573–89.
- Basu M. Improved Differential Evolution for short-term hydrothermal scheduling. Electric Power and Energy System. 2014 Jun; 58:91–100. Crossref
- Malik TN, Zafar S, Haroon S. An improved chaotic hybrid Differential Evolution for the short-term hydrothermal scheduling problem considering practical constraints. Frontiers Information Technology and Electronic Engineering. 2015 May; 16(5):404–17.
- Rasoulzadeh-akhijahani A, Mohammadi-ivatloo B. Shortterm hydrothermal generation scheduling by a modified dynamic neighborhood learning based Particle Swarm Optimization. Electric Power and Energy System. 2015 May; 67:350–67. Crossref
- Karaboga D. An idea based on honey bee swarm for numerical optimization. Technical Report-06. 2005; 39(3):1228– 37.
- Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: Artificial Bee Colony (ABC) algorithm. Journal of Global Optimization. 2007 Nov; 39(3):459–71. Crossref
- Moorthy V, Sangameswararaju P, Viswanatharao J, Ganesan S, Subramanian S. Cost/environmentally compromised dispatch for cascaded hydrothermal system using Artificial Bee Colony algorithm. IEEJ Trans on Elect and Electron Eng. 2015 Oct; 10:S42–54.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.