Abstract
The main objective of short-term hydrothermal scheduling is the optimal allocation of the hydro and thermal generating units, so that the total cost of thermal plants can be minimized. The time of operation of the functioning units are considered to be 24 h. To achieve this objective, the hybrid algorithm combination of Artificial Bee Colony (ABC) and the BAT algorithm were applied. The swarming behavior of the algorithm searches the food source for which the objective function of the cost is to be considered; here, we have used two search algorithms, one to optimize the cost function, and another to improve the performance of the system. In the present work, the optimum scheduling of hydro and thermal units is proposed, where these units are acting as a relay unit. The short term hydrothermal scheduling problem was tested in a Chilean system, and confirmed by comparison with other hybrid techniques such as Artificial Bee Colony–Quantum Evolutionary and Artificial Bee Colony–Particle Swarm Optimization. The efficiency of the proposed hybrid algorithm is established by comparing it to these two hybrid algorithms.
Highlights
The optimal short-term hydrothermal scheduling (STHTS) problem is a challenging task in power systems
The proposed system for STHTS using the hybrid Artificial Bee Colony (ABC)-BAT process was implemented in the working platform of MATLAB (MathWords, Natick, MA, USA), with the system configuration of a Windows 8.1 operating system with 8 GB RAM and 3.19 GHz
Future cost function (FCF), which calculates the future cost of water of any hydro unit, has the input information from the reservoir inflows, and comprehensive data on hourly weight requests, water losses, current making elements, and primary constraints
Summary
The optimal short-term hydrothermal scheduling (STHTS) problem is a challenging task in power systems. The primary target of this scheduling problem is to reduce the operating cost of thermal units over a certain time period (a day or a week) by satisfying various technical conditions [1]. A number of equality constraints determine the scheduling operation, including the power balance constraint, water availability constraints, and initial and final reservoir storage constraints. The inequality constraints considered are hydro discharge constraints, generation constraints, and prohibited discharge zones [2]. The problem considered is non-linear [3]. The optimal scheduling of hydrothermal power system is more complex as it holds the nonlinear objective function and a fusion of equality and inequality constraints.
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