Abstract
This paper proposes an efficient Cuckoo-Inspired Meta-Heuristic Algorithm (CIMHA) for solving multi-objective short-term hydrothermal scheduling (ST-HTS) problem. The objective is to simultaneously minimize the total cost and emission of thermal units while all constraints such as power balance, water discharge, and generation limitations must be satisfied. The proposed CIMHA is a newly developed meta-heuristic algorithm inspired by the intelligent reproduction strategy of the cuckoo bird. It is efficient for solving optimization problems with complicated objective and constraints because the method has few control parameters. The proposed method has been tested on different systems with various numbers of objective functions, and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is more efficient than many other methods for the test systems in terms of total cost, total emission, and computational time. Therefore, the proposed CIMHA can be a favorable method for solving the multi-objective ST-HTS problems.
Highlights
The main task of the short-term hydro-thermal scheduling (ST-HTS) problem is to determine the optimal power generation of the available thermal and hydro power plants so as the total fuel cost of thermal units over a schedule time is minimized satisfying both equality and inequality constraints such as the quantity of available water, power balance, and upper and lower limits on generations
The solution obtained after several iterations is still the same and it cannot be used as stopping criteria since it may lead to the termination of the algorithm with non-optimal solution
The advantage of the CuckooInspired Meta-Heuristic Algorithm (CIMHA) method is that it is effective for finding the optimal solution with few control parameters
Summary
The main task of the short-term hydro-thermal scheduling (ST-HTS) problem is to determine the optimal power generation of the available thermal and hydro power plants so as the total fuel cost of thermal units over a schedule time is minimized satisfying both equality and inequality constraints such as the quantity of available water, power balance, and upper and lower limits on generations. A large amount of the electric power in the world is mainly generated by thermal plants using oil, coal or natural gasses Several contaminants such as nitrogen oxides (NOx), sulfur dioxide (SO2), and carbon dioxide (CO2) have been released into the atmosphere due to the process of electricity generation from the thermal units [1]. In addition to the fuel cost objective, the gaseous emission is another important objective which needs to be considered in the ST-HTS problem. The multi-objective ST-HTS problem is more complex than the conventional one since it needs to find a set of non-dominated solutions for determining the best compromise solution, which is considered as the most reasonable one for the acceptable trade-off between fuel cost and emission objectives
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