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From the survey about the use of classical algorithms, it may be observed that there are evident drawbacks in these classical algorithms such as insecure convergence, continuity limit, and excessive numerical iterations. ORPD problems have dealt with various decisions by using a large number of classical algorithms like linear programming, interior point methods, and Lagrange decomposition method. Therefore, proper distribution and efficient management of reactive power are the major issues which need to be solved urgently in our days. In recent research on the power system, ORPD has attained more attention in order to fulfill the needs of system security and operation as well as social economy. In general, it is challenging work to find an efficient and convenient approach to operate a modern power system, because we must consider the necessity to compensate the system for continually changing load demand and provide energy of a high quality. The objective function involves voltage deviation, reactive power production cost, network active loss, and comprehensive cost of equipment adjustment. The control variables of the ORPD problems include the generators, transformers tapings, shunt reactors, and other reactive power sources. It is a large-scale, nonlinear, discrete, and optimization problem and refers to the reasonable regulation of reactive power through various technologies under the condition of sufficient reactive power, so as to achieve the optimal distribution of reactive power and the reasonable compensation of reactive power for various loads. The optimal reactive power dispatch (ORPD) problem can be considered as an essential part of the optimal power flow (OPF) problem. The obtained results demonstrated that the proposed IDE can successfully be used to deal with the ORPD problem. The results achieved by using the proposed IDE, compared with other optimization algorithms, are discussed and analyzed in detail. Numerical applications of different cases are carried out on several benchmark functions and two standard IEEE systems, i.e., 14-bus and 30-bus test systems.
WHAT IS THE OBJEVTIVE IN BUS SIMULATOR 18 UPDATE
In addition, to enhance the convergence characteristic of the original DE, two kinds of self-adaptive adjustment strategies are employed to update the scaling factor and the crossover factor, respectively, in which the detailed information about the two factors can be exchanged for each generation dynamically.
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In the proposed IDE, a new initialization strategy is developed to construct the initial population for guaranteeing its quality and simultaneously maintaining its diversity. The aim of this study is to discover the best vector of control variables to minimize power loss, under the premise of considering the constraints system. The constraints involved are generators, transformers tapings, shunt reactors, and other reactive power sources. Minimization of the total active power loss is usually considered as the objective function of the ORPD problem. This paper presents a novel differential evolution (DE) algorithm, with its improved version (IDE) for the benchmark functions and the optimal reactive power dispatch (ORPD) problem.