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- W2614772210 abstract "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." @default.
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- W2614772210 date "2017-04-01" @default.
- W2614772210 modified "2023-09-30" @default.
- W2614772210 title "Cost Effective Hydrothermal Scheduling with Practical Constraint using Artificial Bee Colony Algorithm" @default.
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- W2614772210 doi "https://doi.org/10.17485/ijst/2017/v10i16/109055" @default.
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