Planning Of Passive Filters Research Articles

Multi criteria simultaneous planning of passive filters and distributed generation simultaneously in distribution system considering nonlinear loads with adaptive bacterial foraging optimization approach

This paper presents adaptive bacterial foraging optimization (ABFO) algorithm to optimize the planning of passive power filters (PPFs) and distributed generations (DGs) in distribution system with presence of heavy nonlinear load simultaneously. The amount of nonlinear load is assumed to be serious which enforced the system planner to utilize the PPFS. Also the power loss minimization, reliability and voltage profile improvement, and other benefits encouraged the planner to employ the DGs.Some of DG technologies, such as wind generators and solar cells are based on power electronic devices and inverter implementation. Connection of this type of DGs to system produces harmonic. Therefore the utilization of PPFs among existent capacitor busses for harmonic compensation is inevitable. The objective is to minimize the power loss, the total harmonic distortion (THD) and the investment cost of PPFs and DGs simultaneously. Constraints include the voltage limits and the limit candidate buses for PPFs and DGs installation. The harmonic levels of system are obtained by current injections method and the load flow is solved by the iterative method of power sum, which is suitable for the accuracy requirements of this type of study. It is shown that through an economical planning of PPFs and DGs, the total voltage harmonic distortion and active power loss could be minimized simultaneously.

Multi-scenario passive filter planning in factory distribution system by using Markov model and probabilistic Sugeno fuzzy reasoning

Power quality may degrade owing to increasing harmonics from nonlinear loads in a power system. Harmonics are time-varying and non-stationary power quality problems in the power system. This article addresses that the passive filter planning considers multiple scenarios, including different load levels and harmonic currents in a factory distribution system. Based on the above factors and use of the Markov model, this work attempts to gain multiple scenarios, each with its own probability and duration. A novel method based on probabilistic Sugeno fuzzy reasoning is also developed by using individual optimal solutions of all scenarios. Moreover, the final optimal solution is obtained using the center-of-gravity approach. The proposed method is validated using simulation results of a 2-busbar factory distribution system and an 18-busbar factory distribution system.

A graph search algorithm: Optimal placement of passive harmonic filters in a power system

The harmonic in distribution systems becomes an important problem due to an increase in nonlinear loads. This paper presents a new approach based on a graph algorithm for optimum placement of passive harmonic filters in a multi-bus system, which suffers from harmonic current sources. The objective of this paper is to minimize the network loss, the cost of the filter and the total harmonic distortion of voltage, and also enhances voltage profile at each bus effectively. Four types of sub-graph have been used for search space of optimization. The method handles standard capacitor sizes in planning filters and associated costs. In this paper, objective function is not differential but eases solving process. The IEEE 30 bus test system is used for the placement of passive filter. The simulation has been done to show applicability of the proposed method. Simulation results prove that the method is effective and suitable for the passive filter planning in a power system.

Optimal planning of passive harmonic filters using hybrid differential evolution considering variation of system parameters

SUMMARY This paper presents an optimal planning of passive harmonic filter using the hybrid differential evolution method considering variation of system impedance, harmonic current sources and filter tuning points. The proposed method minimizes an objective composed of the total harmonic distortion of current and voltage, selects different filters topologies, and determines their optimal parameters and tuned points under a constant cost. The harmonic currents and voltages in a power system are expressed as probabilistic models which are obtained using the statistical simulation method. Monte-Carlo simulation is employed to verify the accuracy of the obtained probabilistic models. The method proposed is applied to solve the harmonic problems in a practical chemical plant, and the results show that the proposed method is effective for passive filter planning in industrial distribution systems. Copyright © 2012 John Wiley & Sons, Ltd.

A New Method of Passive Harmonic Filter Planning for Controlling Voltage Distortion in a Power System

This paper presents a new method for planning single-tuned passive harmonic filters to control harmonic voltage and voltage distortion throughout a power system. Several alternative objective functions are considered as performance indices in the filter planning problem while the IEEE-519 individual and total harmonic voltage distortion limits at each network bus, as well as filter component limits, are modeled as constraints. The tuned frequency deviation of the filter caused by component manufacturing errors and environmental changes is also taken into account. To solve the problem, a two-step procedure is first proposed to place the filters. Next, the planning problem is formulated as a constrained optimization problem for minimizing the defined network objective function and is then solved by a genetic algorithm-based optimizer to obtain the optimal size of each filter component. The usefulness of the proposed method is tested with an actual distribution network. Results show that the method is effective, computationally robust, and is suitable for the passive filter planning in a power system.

Strategic Placement and Sizing of Passive Filters in a Power System for Controlling Voltage Distortion

This paper presents an approach for determining optimal or near-optimal locations and sizes of single-tuned passive harmonic filters among existent capacitor busses in a power system. The objective of the harmonic filter planning is to control the system-wide voltage distortion, while individual/total harmonic voltage distortion limits at each network bus, and the filter component limits are considered as constraints. The tuned frequency deviation of the filter caused by component manufacturing errors and environment is also taken into account in the problem. The proposed two-phase planning procedure is first to formulate an unconstrained optimization problem for placement of the filters based on sensitivity analysis. Next, a constrained problem is formulated and is solved by a genetic algorithm-based optimizer. The proposed method is tested with an actual distribution system. Test results show that the method is effective, computationally robust, and suitable for passive filter planning in a power system.

Interactive multiobjective passive filter planning with fuzzy parameters in distribution systems using genetic algorithms

The power quality in distribution systems becomes deteriorated due to an increase in nonlinear loads. This paper presents a new method, based on interactive multiobjective nonlinear programming (MONLP), using genetic algorithms (GAs) to study passive filter planning. The short-circuit capacity of the point of common coupling (PCC) and the individual bus loads are modeled with the fuzzy sets. The harmonic voltages and the filter cost are minimized while satisfying the harmonic standard and harmonic power flow equations with the harmonic Y-matrix. An 18-bus system is used as a test system for showing the applicability of the proposed method.