Load Voltage Deviation Research Articles

PSO-Based Voltage Control Strategy for Loadability Enhancement in Smart Power Grids

This paper proposes a new voltage control methodology using the particle swarm optimization (PSO) technique for smart grid loadability enhancement. The goal of this paper is to achieve reliable and efficient voltage profile/stability regulation in power grids. This methodology is based on the decouple power flow equations and the worst-case design technique. Specifically, the secondary voltage control (SVC) problem is formulated as an L-infinity norm minimization problem which considers overall load voltage deviations in electrical power systems as an objective model, and the PSO technique is employed to determine a robust control action which aims to improve voltage profile and to enlarge transmission grid loadability by optimal coordinated control of VAR sources. The methodology was successfully tested on several IEEE benchmark systems.

Comparison of BBO, WIPSO & PSO Techniques for the Optimal Placement of FACTS Devices to Enhance System Security

Nowadays power systems are heavily loaded and are being operated in ways not originally envisioned. Flexible AC Transmission System (FACTS) devices play a vital role in improving the static as well as dynamic performance of the power systems. FACTS devices are based on solid-state control and so the control actions at far higher speed is possible. However the location and rating of the FACTS devices play a major role in deciding the extent to which the objective of improving the system performance is achieved in a cost effective manner. In this work an objective function comprising of cost, line loadings and load voltage deviations is proposed to tap maximum benefits out of their installation and the weights assigned to them decide their relative importance. FACTS devices such as Thyristor Controlled Series Compensator (TCSC) and Static VAR Compensator (SVC) are considered. The optimization is carried out considering four parameters namely the number of FACTS device, location, type and rating of the device. In this work three cases (only TCSC, only SVC, TCSC & SVC) are considered forthe optimal placement of the devices, using PSO, WIPSO and BBO techniques.

Krill Herd Algorithm Based Real Power Generation Reallocation for Improvement of Voltage Profile

Present-day Electric Power Systems are driven under much stressed circumstances when compared to the past and creating a developing need for accuracy, flexibility, and reliability in the areas of Transmission, Distribution and Electric Power Generation. In all stages of power system, voltage stability problems are increasing more and more. So, the only alternate solution for these problems is proper placement and sizing of UPFC. The paper presents the Placement and Tuning of UPFC for a multi-objective function consisting of minimization of transmission losses, load voltage deviation. Here L-index is used to place the UPFC in a specified location i.e., weakest bus, critical line and the weak area of the system. In this paper, a newly developed meta-heuristic algorithm named Krill Herd (KH) is introduced to solve multi-objective problem of optimization. Simulation is carried on IEEE 14-bus system and the results have been compared with the Genetic algorithm with and without UPFC.

A new Optimal reactive power planning based on Differential Search Algorithm

Abstract This paper proposes a new multi-level methodology based on the optimal reactive power planning. The developed methodology is designed to solve the problem of the non-feasibility solution of the fuel cost minimization problem (for a given operating point) where the classical method such as interior point method (IPM) is applied. The proposed solution to solve this problem is based on the application of the optimal reactive power planning problem considering voltage stability as the initial solution of the fuel cost minimization problem. To improve the latter the load voltage deviation problem is applied to improve the system voltage profile. For a good result improvement, the reactive power planning problem and the load voltage deviation minimization problems are solved using a new optimization method namely the Differential Search Algorithm (DSA). Moreover, the fuel cost minimization problem is solved using IPM. To identify the candidate placements of compensation devices for the optimal reactive power planning problem, a new voltage stability index namely: The Fast Voltage Stability Index (FVSI) is used. The methodology has been tested with the equivalent Algerian power system network, and the simulation results show the effectiveness of the proposed approach to improve the reactive power planning problem and to minimize the system voltage deviation.

Enhancement of Voltage Stability by optimal location of UPFC using MPSO and Power Flow Analysis using ECI Algorithm

Voltage instability and voltage collapse have been considered as a major threat to present power system networks due to their stressed operation. It is very important to do the power system analysis with respect to voltage stability. Flexible AC Transmission System (FACTS) is an alternating current transmission system incorporating power electronic-based and other static controllers to enhance controllability and increase power transfer capability. A FACTS device in a power system improves the voltage stability, reduces the power loss and also improves the load ability of the system. FACTS have made the power systems operation more flexible and secure. Amongst the several FACTS controllers, the Unified Power Flow Controller (UPFC) is most effective to improve the enhancement of voltage stability and reduces the power loss. This study investigates the application of Particle Swarm Optimization (PSO) to find sizing of Unified Power Flow Controller (UPFC) device to minimize the voltage stability index, total power loss, load voltage deviation, and cost of FACTS devices to improve voltage stability in the power system. A new model is proposed in this thesis to improve existing power-based model by using the Norton Equivalent Theorem. The proposed model can be integrated with the Equivalent Current Injection (ECI) power flow model easily. By ECI algorithm, it is much quickly and precisely to implement power flow calculations. Finally It is observed from the results that the voltage stability margin is improved, the voltage profile of the power system is increased and real power losses also reduced by optimally sizing UPFC device in the power system. Index Terms: Voltage stability, Unified Power Flow Controller (UPFC), Equivalent -Current Injection (ECI), Modified particle swarm optimization (MPSO)

Optimal Location of SVC Considering Critical Contingency and Varying Load

The flexible Alternating Current transmission system (FACTS) may play a vital role in solving various problems of modern restructured power system networks, which have to operate under highly stressed conditions because of ever increasing demand of electric power. However, due to huge capital investment, an intensive investigation is required at planning stage to select optimal location and size of these devices to acquire maximum benefit of it. In this paper, Continuous Genetic Algorithm (CGA) based method is proposed for placement of Static Var Compensator (SVC) for minimizing real power loss, load bus voltage deviations and size of SVC. As a first step, contingency ranking is performed to determine the most severe line outages by evaluating voltage performance index (VPI) for both cases i.e. for base load condition and when load is varied randomly. Thereafter, Continuous Genetic Algorithm (CGA) has been applied to solve mixed continuous-discrete optimization problem. The optimization is carried out to find optimal location and size of SVC to minimize real power loss, load voltage deviation and rating SVC. The effectiveness of the proposed methodology is demonstrated on a standard IEEE 30-bus system.

An Adaptive PMU-Based Secondary Voltage Control Scheme

This paper presents a new adaptive control approach to power system secondary voltage control (SVC) problem using synchronized phasor measurements as control feedback. The objective is to improve overall system voltage profile by appropriate management of reactive power sources against any unexpected load disturbances. The proposed method is adaptive in the sense that load disturbances are estimated on-line for computing the feasible control inputs for the minimization of the worst case load voltage deviation. That is, the resulting worst load voltage change can precisely remain within the range of predefined constraint using the feasible control inputs. Moreover, the computational burden of the proposed method is low such that it is suitable for on-line applications. Extensive simulation studies on the IEEE 14-bus and the IEEE 30-bus systems have been conducted to demonstrate the advantages of the proposed method over the traditional robust method.

APPLICATION OF HYBRID PSOGA FOR OPTIMAL LOCATION OF SVC TO IMPROVE VOLTAGE STABILITY OF POWER SYSTEM

Due to huge increase in power demand, modern power system networks are being operated under highly stressed conditions. This has resulted into the difficulty in meeting reactive power requirement and maintaining the bus voltage within acceptable limits. Voltage instability in the system occurs in the form of a progressive decay in voltage magnitude at some of the buses. The problems of voltage instability and voltage collapse are the major concerns in the operation of power system. It is very important to do the power system analysis with respect to voltage stability. Flexible AC Transmission System (FACTS) device in a power system improves the stability, enhances the voltage stability margin and reduces the power losses. Identification of location of FACTS device in the power system is very important task. Research is carried out to investigate application of Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and hybrid PSOGA to find optimal location and rated value of SVC device to minimize the voltage stability index, total power loss, load voltage deviation, cost of generation and cost of FACTS device to improve voltage stability in the power system. Optimal location and rated value of SVC device have been found for different loading scenario using PSO, GA and PSOGA. It is observed from the results that the voltages stability margin is improved, voltage profile of the power system is increased, load voltage deviation is reduced and real power losses also reduced by optimally locating SVC device in the power system. The proposed algorithm is verified with IEEE 14 bus and 30 bus power systems.

Enhancement of Voltage Stability by Optimal Location of Static Var Compensator Using Genetic Algorithm and Particle Swarm Optimization

Problem statement: Voltage instability and voltage collapse have been considered as a major threat to present power system networks due to their stressed operation. It is very important to do the power system analysis with respect to voltage stability. Approach: Flexible AC Transmission System (FACTS) is an alternating current transmission system incorporating power electronic-based and other static controllers to enhance controllability and increase power transfer capability. A FACTS device in a power system improves the voltage stability, reduces the power loss and also improves the load ability of the system. Results: This study investigates the application of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to find optimal location and rated value of Static Var Compensator (SVC) device to minimize the voltage stability index, total power loss, load voltage deviation, cost of generation and cost of FACTS devices to improve voltage stability in the power system. Optimal location and rated value of SVC device have been found in different loading scenario (115%, 125% and 150% of normal loading) using PSO and GA. Conclusion/Recommendations: It is observed from the results that the voltage stability margin is improved, the voltage profile of the power system is increased, load voltage deviation is reduced and real power losses also reduced by optimally locating SVC device in the power system. The proposed algorithm is verified with the IEEE 14 bus, IEEE 30 bus and IEEE 57 bus.

Optimal location and setting of SVC and TCSC devices using non-dominated sorting particle swarm optimization

In this paper, a new method for optimal locating multi-type FACTS devices in order to optimize multi-objective voltage stability problem is presented. The proposed methodology is based on a new variant of particle swarm optimization (PSO) specialized in multi-objective optimization problem known as non-dominated sorting particle swarm optimization (NSPSO). The crowding distance technique is used to maintain the Pareto front size at the chosen limit, without destroying its characteristics. To aid the decision maker choosing the best compromise solution from the Pareto front, the fuzzy-based mechanism is employed for this task. NSPSO is used to find the optimal location and setting of two types of FACTS namely: Thyristor controlled series compensator (TCSC) and static var compensator (SVC) that maximize static voltage stability margin (SVSM), reduce real power losses (RPL), and load voltage deviation (LVD). The optimization is carried out on two and three objective functions for various FACTS combinations considering. For ensure the robustness of the proposed method and gives a practical sense of our study, N − 1 contingency analysis and the stress of power system is considered in the optimization process. The thermal limits of lines and voltage limits of load buses are considered as the security constraints. The proposed method is validated on IEEE 30-bus and realistic Algerian 114-bus power system. The simulation results are compared with those obtained by particle swarm optimization (PSO) and non-dominated sorting genetic algorithms (NSGA-II). The comparisons show the effectiveness of the proposed NSPSO to solve the multi-objective optimization problem and capture Pareto optimal solutions with satisfactory diversity characteristics.

A steady state voltage monitoring and control algorithm using localized least square minimization of load voltage deviations

This paper describes recent work on the theoretical and algorithmic enhancements of the MIT method for power system steady-state voltage monitoring and control. Under the conditions that no dynamic voltage problems are present, the method is intended primarily: to monitor steady-state voltage and reactive power conditions; to identify potential problem situations; and to make decisions regarding their severity. The developed method utilizes various reactive power resources on the power system to remedy voltage violations. The corrective actions suggested are either in the order assigned by the operator or according to efficiency criteria, determined by this algorithm. The corrective actions ensure minimum possible voltage deviations from a given desired voltage profile. Corrective actions are considered to be optimal in this sense. The method has the unique feature of identifying minimum number of most effective corrective actions so that voltages are maintained within the given limits. The method does not solve the exact load flow equations, and therefore it avoids inversion of a full system size matrix. Reactive power scheduling is computed so that the resulting load voltages, are within pre-specified target values. The computational time does not increase significantly with increase of power system size, since no inversion of a system size matrix is needed. Numerical tests on a small and large scale electric power system (IEEE 39 and New England 1726) are presented and analyzed.