Distributed computing approach to solve unbalanced three-phase DOPFs

Distribution systems have been gradually improved with new technologies. They have been upgraded from the traditional system with low-level control to a smart-grid system with high-level control. In the present work, a mathematical model of an unbalanced three-phase distribution system, including ZIP loads and other components of distribution systems is used, and a Genetic Algorithm (GA) -based Distribution Optimal Power Flow (DOPF) model is applied to find the optimal integer solutions for discrete system control elements such as Load Tap Changers (LTCs) and Switched Capacitors (SCs) in a practical feeder. In order to reduce the computational burden and consequently the run-time, a communication Middleware System for smart grids is used to solve the GA-based DOPF problem on a decentralized computer system using a parallel computing approach. This system is responsible for running the model, managing all communication between the nodes, and transferring the results between various parts of the parallel system. Comparing with heuristic methods with faster sub-optimal solutions in a centralized computer system, the present work is expected to yield better optimal solution within acceptable practical run-times.