Optimal reactive power dispatch using a novel optimization algorithm

The problem of optimal reactive power dispatch (ORPD) is one of the most popular and widely discussed problem in power system engineering all over the world. Optimal reactive power dispatch is one of the sub-problems of the optimal power flow which is complex and nonlinear problem, which can be formulated as both single- and multi-objective. In this paper, the problem has been formulated as a single-objective problem to minimize the active power losses in the transmission lines. A recently proposed powerful and reliable meta-heuristic algorithm known as the JAYA algorithm has been applied to solve the ORPD problem. The algorithm has been applied on the standard IEEE 14, 30, 57 and 118 bus systems. The simulation results using the proposed algorithm when compared with the results from other algorithms and few others reported in the literature prove that the JAYA algorithm is the most superior among all.

Optimal Power Dispatch of Dispersed Sources in Direct-Current Networks with Nonlinear Loads

The problem of the optimal power dispatch of dispersed generators in direct-current networks under the presence of nonlinear loads (constant power terminals) is addressed through a combinatorial optimization strategy by using a master-slave solution methodology. The optimal power generation in the dispersed is solved in the master optimization stage through the application of the vortex-search algorithm. Each combination of the power outputs at the dispersed generation sources is provided to a power flow methodology known as the hyperbolic power flow approach for direct current networks. The main advantage of the proposed optimization method corresponds to the possibility of solving a complex nonlinear programming problem via sequential quadratic programming, which can be easily implemented at any programming language with low computational effort and high-quality results. The computational tests of the master-slave optimization proposal are evaluated in a 21-bus system, and the numerical results are compared with the implementation of the exact nonlinear programming model in the General Algebraic Modeling System (i.e., GAMS). All the computational results are conducted through the MATLAB programming environment licensed by Universidad Tecnologica de Pereira for academic usage.

Optimal Reactive Power Dispatch Using Multistage Artificial Immune System

Most countries over the past few decades have modernized their economies and become more reliant on electricity to run, so the electrical power system has also expanded greatly. Optimal Reactive Power Dispatch (ORPD) has a big influence on the reliability, security, and economic operation of the power system. Another thing to note is that ORPD has a few major targets and objectives which are to reduce the active or real power losses, to improve the voltage profile, to reduce transmission costs, and to increase system stability. Non-convex, non-linear, and multimodal problems make the development of intelligent algorithms to solve the reactive power dispatch problem highly relevant. Some researchers chose to compare and contrast optimization techniques from the past with each other in order to answer some remaining uncertainties such as the effectiveness and complexity of the technique toward the chosen objective function(s). Thus, this paper proposed applying the Multistage Artificial Immune System (MAIS) optimization method for solving the ORPD problem with the objective of reducing the power system losses. This algorithm was made by modifying and upgrading the classical AIS optimization method. Instead of only going through the process one time in the classical AIS algorithm, this MAIS method going through the processes more than one time in multiple stages of the same processes. This process includes cloning and mutation as well as selection. These modifications also aid in the development of new and unique solutions, as opposed to the classical AIS optimization process. Therefore, these enhancements could lead to a rise in the accuracy of the results' because there have been increased comparisons. This study confirms that MAIS optimization can deliver superior results in less time than AIS. Keywords—Optimal reactive power dispatch, computational intelligence, multistage artificial immune system, loss minimization.