Planning Of Passive Harmonic Filters Research Articles

Multi‐criteria decision‐making approach for optimal and probabilistic planning of passive harmonic filters in harmonically polluted industrial network with photovoltaic resources

AbstractNowadays, nonlinear loads are widely employed within the industrial applications that cause harmonic distortions in the network. Passive harmonic filters stand out as the preeminent and cost‐efficient remedy for mitigating the impact of harmonic distortions. Any changes in power system conditions such as load variability and photovoltaic resources uncertainty have a significant impact on the harmonic conditions which can affect the quantity and positioning of passive harmonic filters. Hence, in this paper, a method including an innovative optimization problem is proposed for probabilistic planning of passive harmonic filters considering system conditions variability, which is solved by heuristic methods and multi‐criteria decision‐making techniques. By doing this, a solution is obtained where grid losses and the passive harmonic filter costs are minimized and the power factor and frequency response are improved on selected buses. Also, in this paper, the index that gauges the severity of total harmonic distortion is proposed to determine the worst case of the network in terms of harmonic distortions which is so vital for system operators, especially the systematic approach to designing passive harmonic filters. To indicate the efficiency of the proposed approach, the electrical system of an actual Iranian copper mine of significant scale is employed, featuring the integration of non‐linear loads.

Optimal probabilistic planning of passive harmonic filters in distribution networks with high penetration of photovoltaic generation

In recent years, distribution networks have been increasingly affected by the random nature of harmonic sources introduced by nonlinear load and renewable energy sources (RES) such as photovoltaic (PV) systems. This paper presents an approach based on Genetic Algorithm (GA) and Monte-Carlo Simulation (MCS) for the optimal planning of single-tuned passive harmonic filters (PHFs) in a distribution network. The resistance and inductance of the lines within the network are modeled by frequency dependent characteristics. The probabilistic characteristics of the load and PV system currents are also considered for optimal planning of PHFs. In our optimization model, the objective function minimizes the total PHF installation cost and the energy losses, by considering the total harmonic distortion (THD) of bus voltages and maximum capacity of PHF as constraints. The proposed method is validated by a simulation study using an unbalanced three-phase real distribution system. An advantage of this method over most of the conventional approaches is that both harmonic current magnitude and phase angle of real PV systems are taken into account. Numerical results show the applicability and effectiveness of the proposed method.

Passive harmonic filter planning considering daily load variations and distribution system reconfiguration

Although distribution system reconfiguration is usually implemented for grid loss reduction, it can affect many other indices of the grid such as voltage profile and power quality indices. Therefore, harmonic filter planning studies which ignore different configurations of the system cannot achieve optimal solutions. In other words, when the filter planning study is carried out with respect to a single grid topology, power quality constraints satisfaction isn’t guaranteed while the real-world loss-reduction-based reconfigurations are applied to the system. In order to incorporate different configurations of the grid in planning study, this paper proposes an aggregate model for passive harmonic filter planning and loss-reduction-based reconfigurations in primary distribution systems. In this method, in order to incorporate distribution system operator decisions, reconfiguration for loss minimization is carried out as a lower level problem in pre-determined hours of each day type. The passive harmonic filter planning (as the higher level problem) is then studied with respect to the daily load profiles and different system configurations. Two separate Genetic-Algorithm (GA) cores are implemented to solve the main passive harmonic filter planning problem and reconfigurations. The proposed method is then applied to a modified 33-bus system with high penetration of nonlinear loads. The simulation results verified that ignoring the system reconfigurations in planning process may result in power quality constraints violation in some specified hours during the planning horizon. On the other hand, incorporating different system topologies in the planning study guarantees to maintain the system Total Harmonic Distortion (THD) levels within the standard limits and results in lower energy loss, capacity occupation and filter investment cost.

Bacterial foraging optimization and adaptive version for economically optimum sitting, sizing and harmonic tuning orders setting of LC harmonic passive power filters in radial distribution systems with linear and nonlinear loads

This paper presents bacterial foraging optimization (BFO) algorithm and its adaptive version to optimize the planning of passive harmonic filters (PHFs).The important problem of using PHFs is determining location, size and harmonic tuning orders of them, which is reach standard levels of harmonic distortion with applying minimum cost of passive filters.In this study to optimize the PHFs location, size and setting the harmonic tuning orders in the distribution system, considered objective function includes the reduction of power loss and investment cost of PHFs. At the same time, constraints include voltage limits, number/size of installed PHFs, limit candidate buses for PHFs installation and the voltage total harmonic distortion (THDv) in all buses. 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 placement and sizing of PHFs the total voltage harmonic distortion and active power loss could be minimized simultaneously.The considered objective function is of highly non-convex manner, and also has several constraints. On the other hand due to significant computational time reduction and faster convergence of BFO in comparison with other intelligent optimization approach such as genetic algorithm (GA), particle swarm optimization (PSO) and artificial bee colony (ABC) the simple version of BFO has been implemented. Of course other versions of BFO such as Adaptive BFO and combination of BFO with other method due to complexity of harmonic optimization problem have not considered in this research.The simulation results for small scale test system with 10 buses, showed the significant computational time reduction and faster convergence of BFO in comparison with GA, PSO and ABC. Therefore in large scale radial system with 34 buses, the proposed method is solved using BFO.The simulation results for a 10-bus system as a small scale and 34-bus radial system as a large scale show that the proposed method is efficient for solving the presented problem.

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.

Passive Harmonic Filter Planning in a Power System With Considering Probabilistic Constraints

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper presents a new method for planning single-tuned passive harmonic filters to control harmonic voltage distortion throughout a power system. In the problem, the probabilistic characteristics of the harmonic source currents and network harmonic impedances in the filter planning are taken into account. The objective is to minimize the total filter installation cost, while the harmonic voltage limits and filter component constraints are satisfied with predetermined confidence levels. To obtain the optimal size of each filter component of the planning problem, the proposed procedure is first to find the candidate filter buses based on the sensitivity analysis. Next, the formulated probability-constrained problem is transformed into a deterministic nonlinear programming problem and is solved by a genetic-algorithm-based optimizer. The proposed solution procedure is tested with an actual distribution network and is verified by the conventional deterministic approach and by the Monte Carlo simulation. Numerical experiences show that the proposed method yields favorable results compared with the other two approaches. </para>

A Probabilistic Approach for Optimal Passive Harmonic Filter Planning

This paper presents a new approach based on the linear approximation method and chance-constrained programming model for the optimal planning of single-tuned harmonic passive filters in an industrial power system. In the problem, the effects of the probabilistic characteristics of the nonlinear load currents and harmonic impedances of the system and linear loads are considered in the filter planning. The objective is to minimize the total filter installation cost, while the harmonic currents limits and filter component constraints are satisfied with predetermined confidence levels. The formulated probability-constrained problem is then transformed into a deterministic nonlinear programming problem and is solved by a sequential quadratic programming (SQP) solver. The proposed solution procedure is tested with an actual industrial power system and is verified by the conventional deterministic approach and by the Monte Carlo simulation. Numerical experiences show that the proposed method yields favorable results for the filter planning.

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.