Y. del Valle

Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems

Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. Also, it provides a comprehensive survey on the power system applications that have benefited from the powerful nature of PSO as an optimization technique. For each application, technical details that are required for applying PSO, such as its type, particle formulation (solution representation), and the most efficient fitness functions are also discussed.

Multiple STATCOM Allocation and Sizing Using Particle Swarm Optimization

This study shows step by step the application of the particle swarm optimization (PSO) method to solve the problem of optimal allocation and sizing of multiple static compensators (STATCOM) in a medium size power network (45 bus system, part of the Brazilian power network). The PSO is proposed as an alternative methodology for traditional heuristic approaches and complicated mixed integer linear and non linear programming methods. Simulation results show the suitability of the PSO technique in finding multiple optimal solutions to the problem (Pareto front) with reasonable computational effort. As a part of this study, the optimal setting of PSO parameters is investigated and different power system load conditions are tested to determine the impact over the location and size of each STATCOM unit

Optimal STATCOM Sizing and Placement Using Particle Swarn Optimization

Heuristic approaches are traditionally applied to find the size and location of flexible AC transmission systems (FACTS) devices in a small power system. Nevertheless, more sophisticated methods are required for placing them in a large power network. Recently, the particle swarm optimization (PSO) technique has been applied to solve power engineering optimization problems giving better results than classical methods. This paper shows the application of PSO for optimal sizing and allocation of a static compensator (STATCOM) in a power system. A 45 bus system (part of the Brazilian power network) is used as an example to illustrate the technique. Results show that the PSO is able to find the best solution with statistical significance and a high degree of convergence. A detailed description of the method, results and conclusions are also presented

A full compensating system for general loads, based on a combination of thyristor binary compensator, and a PWM-IGBT active power filter

A full compensating system for distribution networks which is able to eliminate harmonics, correct unbalanced loads and generate or absorb reactive power is presented. The system is based on a combination of a thyristor binary compensator (TBC), and a PWM-IGBT active power filter (APF) connected in cascade. The TBC compensates the fundamental reactive power and balances the load connected to the system. The APF eliminates the harmonics and compensates the small amounts of load unbalances or power factor that the TBC cannot eliminate due to its binary condition. The TBC is based on a chain of binary-scaled capacitors and one inductor per phase. This topology allows, with an adequate number of capacitors, a soft variation of reactive power compensation and a negligible generation of harmonics. The capacitors are switched on when the line voltage reaches its peak value, avoiding inrush currents generation. The inductor helps to balance the load, and absorbs reactive power when required. The APF works by measuring the source currents, forcing them to be sinusoidal. The two converters (TBC and APF) work independently, making the control of the system simpler and more reliable. The system is able to respond to many kinds of transient perturbations in no more than a couple of cycles. The paper analyzes the circuit proposed, the way it works and the results obtained under operation with different types of loads.