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This paper proposes a novel method to find the optimal location of the shunt connected Flexible AC Transmission Systems (FACTS) such as Static Var Compensator (SVC) or Static Synchronous Compensator (STATCOM) to the power system for regulating voltage levels of all buses. Three indices include Voltage Drop Index (VDI), Total Voltage Drop Index (TVDI), and Total Voltage Drop of Network Index (TVDNI) are presented to find the location of the SVC. Also, to minimize the solution space, a ranking list will be established. For the case studies, the IEEE 14-bus test system is selected, and an SVC is located in the system. Simulations are done in two cases: network loads increase with constant coefficient and randomly. According to simulation results in both cases, the proposed method can identify the optimal placement of SVC, and the voltage drop due to increasing the load will be compensated. For the IEEE 14-bus test system, the optimal location of the SVC is bus 9. Variable loads are considered for 24 h, and SVC is installed at bus 9 to validate the introduced method. Results show the voltage level for all buses is compensated so that the voltage levels are higher than the minimum voltage level, i.e. 95%. [ABSTRACT FROM AUTHOR]

Flexible Alternating Current Transmission Systems (FACTS) play a very prominent role in enhancing the performance of power system networks and in the quality up-gradation of power system by stabilizing the system parameters like voltage deviation, system security, power loss and system load-ability being a few to name. This work therefore handles two of the important performance parameters of a power system network namely power flow which is modeled as the System Load-ability (SL) and voltage profile which is represented as Voltage Stability Index (VSI). In this paper the maximization of VSI and SL of IEEE 30 Bus and 57 Bus networks have been exploited through the optimal placement of Thyristor Controlled Series Capacitor (TCSC), Static VAR Compensator (SVC) and Unified Power Flow Controller (UPFC) in the networks using the proposed and enhanced form of a recently developed meta-heuristic technique named as Salp Swarm Optimization (SSO). The outcomes of the simulations have been scrutinized with an established swarm-based optimization procedure. [ABSTRACT FROM AUTHOR]

Aiming at the deficiencies and shortcomings of traditional reactive power compensation devices in controlling and improving voltage quality, a bilevel programming model for the coordinated optimal allocation of active and reactive power capacity of photovoltaic power generation systems, wind-driven generators, shunt capacitors and static var compensators is established based on chance-constrained programming. In the optimization model, the randomness and intermittence of the output power of the distributed generation and the reactive power regulation ability of the distributed generation are considered. The correlation of illumination, wind speed and load fluctuation is considered and affected by seasonal variation. Latin hypercube sampling method is used to deal with the correlation of random variables. Monte Carlo probabilistic power flow method is used to calculate the power flow of distribution network with intermittent distributed generation systems. The location and capacity of active and reactive power sources in outer programming are optimized by adaptive artificial fish swarm algorithm, and the allocation scheme of active and reactive power sources determined by outer programming is optimized by inner adaptive artificial fish swarm algorithm. The two-layer nested adaptive artificial fish swarm algorithm is used to solve the optimal allocation problem constructed in this paper, and the optimal allocation scheme of active and reactive power supply capacity is determined. Taking IEEE33 distribution system as an example, the feasibility and applicability of the proposed model and algorithm are verified. [ABSTRACT FROM AUTHOR]

In this article, the optimal allocation of compensation devices in power systems is determined using Improved Moth-flame Optimization (IMFO) algorithm. The main objective of this study is to maximize power system loadability, reduce total power system losses and enhance the voltage profile through finding the optimal locations and sizes of Static VAR Compensator (SVC) and Thyristor Controlled Compensator (TCSC). The methodology of this article is based on Continuation Power Flow (CPF) which is merged with IMFO in Optimum Power Flow (OPF) problem restricted by equality and inequality constraints. The proposed algorithm is implemented to regulate the required control variables. Both of single and multi-objective functions are applied on 57-IEEE bus test system to prove the performance of the proposed algorithm. The acquired simulation results by IMFO are compared with Moth Flame Optimization technique (MFO) and Multi Verse Optimizer (MVO) to emphasize the robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This article presents the design of an improved smart grid model with an improved optimal VAr strategy using a bio-inspired approach. The integration of an artificial neural network technique with bio-inspired algorithms is the novelty of this research work. The objective of the work is attained by integrating the artificial neural network with three different evolving techniques like the Big Bang-Big Crunch algorithm, the gravitational search algorithm, and bacterial foraging algorithm. The three different layers of artificial neural network reconcile with the power grid for enhancing the voltage profile generated by bio-inspired techniques. The effectiveness and reliability of the algorithms are examined on the standard IEEE 30 bus system. The sample test bus system comprises six Generators, four Transformer tap changers, and 2 Static Shunt VAr Compensator. Artificial intelligence technology is applied for enhancing the voltage profile by managing reactive power across the power system network. The results produced by artificial intelligence technique are more competent and outstanding than any other conservative optimization techniques. It is found that the real power loss across the network has been reduced from 5.744 MW to 4.234 MW, while the bus voltage deviation has been minimized from 1.475 p.u. to 0.0918 p.u. and the voltage profile has been improved from 0.968 to 1.0985 p.u. after integration of the artificial neural network. The optimal values of objective functions are attained by evaluating the training and testing performance of artificial neural network criteria such as coefficient of determination, mean absolute error, root mean square error, and mean absolute percentage error. The obtained results show the remarkable improvement in voltage profile after integrating artificial intelligence technology with a power grid system. [ABSTRACT FROM AUTHOR]

This paper presents a sliding mode dynamic surface control strategy for multi-machine power systems with static var compensator (SVC) to design the controller of the generator excitation system. Firstly, compared with the existing control methods, the combination of sliding mode control and dynamic surface control improves the robustness of the system and avoids the "explosion of complexity" problems. Subsequently, the fuzzy logic system is introduced to estimate the unknown continuous function in power system, and the norm of the weight vector is used to replace the estimation of the entire weight vector. In this way, computational burden will be reduced. In addition, the influences of unknown time delays and dead-zones are considered. Finite cover lemma is introduced to deal with unknown time delays, which enables arbitrarily small L ∞ tracking performance. The unknown dead-zone is converted into the sum of linear dead zone and bounded nonlinear dead zone. Finally, the simulation results are provided to validate the feasibility and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article presents a novel comprehensive learning bat algorithm (CLBAT) for the optimal coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC) for damping electromechanical oscillations in multi-machine power systems considering a wide range of operating conditions. The CLBAT incorporates a new comprehensive learning strategy (CLS) to improve microbat cooperation; location updating is also improved to maintain the bats' diversity and to prevent premature convergence through a novel adaptive search strategy based on relative travelled distance. In addition, the proposed elitist learning strategy speeds up convergence during the optimization process and drives the global best solution towards promising regions. The superiority of the CLBAT over other algorithms is demonstrated via several experiments and comparisons through benchmark functions. The developed algorithm ensures convergence speed, credibility, computational resources and optimal tuning of PSSs and SVCs of multi-machine systems under different operating conditions through eigenanalysis, nonlinear simulation and performance indices. [ABSTRACT FROM AUTHOR]

A valid damping of oscillations is an upcoming extensive challenge while maintaining the stability of the power system. This oscillation generally occurs due to the fluctuation raised, when two systems are interconnected. This paper addresses the oscillation occurred in the power system as the main challenge, which thus performs an effective simulation in 68-bus system. Here, it promotes a sufficient CC with two FACTS devices such as TCSC and UPFC, which are connected with PSS. Further, it adopts firefly algorithm to enable the CC among the FACTS devices. To the next of the simulation, this paper compares the performance of the FF- CC with conventional optimisations include GSO, PSO, GA and ABC algorithms to enable CC. Further, it provides a detailed analysis of the impact of PSS and loading effects on CC. As a result, the performance of FF-CC hands over the stable power system with powerful damping of oscillations, after comparing it with the existing methods. Abbreviations: ABC, Artificial Bee Colony; ICA, Imperialist Competitive Algorithm; AVR, Automatic Voltage Regulators; NETS, New England test system; BFOA, Bacteria Foraging Optimization Algorithm; NYPS, New York power system; BSO, Bacterial Swarm Optimization; PSO, Particle Swarm Optimization; CC, Coordinated Control; PSS, Power System Stabilizers; COA, Chaotic Optimization Algorithm; STATCOM, Static Synchronous Compensator; CS, Cuckoo Search; SSSC, Static Synchronous Series Compensator; FACTS, Flexible Alternating Current Transmission System; SVC, Static Var Compensator; GA, Genetic Algorithm; TCSC, Thyristor Controlled Series Capacitor; GSO, Gravitational Search Algorithm; UPFC, Unified Power Flow Controller [ABSTRACT FROM AUTHOR]

Disconnection of large wind turbine generators (WTGs) in renewable-integrated power systems has been well-recognized as one of the main origins of system instability. The ongoing study aims at establishing a three-stage fuzzy coordinator (TSFC) intended to enhance the power system stability encountering with major outages of large WTGs. The new TSFC employs wide area measurement system (WAMS) for a global coordination in multi-machine power system. The proposed TSFC founds a fuzzy logic coordination basis for tuning the interactions of multiple control devices. To this end, the WAMS-based TSFC is devised to end in performance harmonization of multiple control devices including automatic voltage regulator (AVR), power system stabilizer (PSS), and static var compensator (SVC). The TSFC receives the normalized voltage and rotor angle deviations of all machines and also the penetration level of wind farms as the input signals. The penetration level as the input signal determines the coordination strategy in three stages. In the sequel, based on the expert knowledge and analyzing the established rules, the TSFC generates output control signals broadcasted to the AVR, PSS, and SVC concurrently. Considering different penetration levels of WTGs, extensive numerical studies have been conducted to evaluate performance of the new coordinator. [ABSTRACT FROM AUTHOR]

Wind power penetration affects the dynamics and operational performance of a conventional power system. This article investigates the stability issues of a power system with the penetration of wind power from a doubly fed induction generator and direct drive synchronous generator. An approach to utilize an existing shunt flexible AC transmission system controller, static VAR compensator, for enhancing the small signal stability of a wind connected power system is discussed here. Supplementary stabilizing control for damping oscillatory modes is applied to static VAR compensator and suitable control input has been selected for the best damping performance of the proposed controller. [ABSTRACT FROM AUTHOR]

Under a restructuring atmosphere, energy customers and producers generally create various bilateral real power markets. The transmission company usually carries out these bilateral power markets contained by the restrictions allowed through the power network design and working situation. The market operator can misuse the “power markets” and earn additional revenue. Flexible Alternate Current Transmission System devices are considered to be one such technology that helps in improving the bilateral real power markets. In this work, a new methodology for correct placement of Flexible Alternate Current Transmission System devices in the restructured power markets is proposed. A generalized evolutionary programming technique is projected to find out the optimal bilateral real power markets with and without Flexible Alternate Current Transmission System devices under a restructuring atmosphere. Flexible Alternate Current Transmission System devices, such as the Thyristor-Controlled Series Compensator, Static VAR Compensator, and Unified Power Flow Controller, are employed. Utilization of these devices helps in minimizing the cost and also helps in reducing the total overloads, excess power flow, and severity of overloading. A sample 4-bus system and 24-bus extra high-voltage Indian system are presented as examples to exemplify the use of this formulation to reduce the price of the bilateral power market. [ABSTRACT FROM PUBLISHER]

Switching function optimization for minimum source harmonic injection for a static VAR compensator is presented. The static VAR compensator is configured with a fixed capacitor and insulated-gate bipolar transistor controlled reactor. The switching function is optimized for minimum source harmonic injection considering the desired fundamental voltage across load terminals. A gravitational search algorithm is employed for this purpose. It is observed that the proposed switching scheme with two different switching angles per half-cycle provides lower source harmonic injection compared to conventional switching, hence improving the source current harmonics. The switching angles are computed off-line using the gravitational search algorithm for varying modulation indices considering the minimum total harmonic distortion of the reactor voltage. The switching angles are stored in a processor as a function of the modulation index for on-line application using a piecewise mixed model approximation technique for low memory usage. It is observed that the proposed switching improves the source current total harmonic distortion on an average of 4 to 5% over most of the operating range compared to conventional switching without optimization. Various simulation and experimental results are presented on different loads to validate the proposed concept. [ABSTRACT FROM PUBLISHER]

Wind generation connection to power system affects steady-state and transient stability. Furthermore, this effect increases with the increase of wind penetration in generation capacity. In this article, optimal location of flexible AC transmission system devices is carried out to solve the steady-state problems of wind penetration using a genetic algorithm. Case study is carried out on modified IEEE 39-bus system with wind penetration increases by 50%; the system suffers from outage of one generator with load decrease in one of system buses by 15%. The system suffers from minimum voltage reduction, total loss increase, and violation of power and power angle limits. Series and shunt flexible AC transmission system devices are used in this article. Results showed that series flexible AC transmission system devices in certain range are able to solve these problems associated with wind penetration in power systems with acceptable cost saving. [ABSTRACT FROM PUBLISHER]

A new optimization technique known as the flower pollination algorithm is suggested in this article for robust tuning of a static VAR compensator to mitigate power system oscillations. The flower pollination algorithm is based on the properties of flowering plants. The tuning of a static VAR compensator controller is established as an optimization process. The flower pollination algorithm is applied to find out the optimal parameters of a static VAR compensator by diminishing certain performance index. The behavior of the suggested algorithm has been appreciated with the behavior of the genetic algorithm and bacteria foraging to certify the notability of the suggested flower pollination algorithm in designing a static VAR compensator. Simulation results of the flower pollination algorithm based static VAR compensator provide greater attenuation for various loading conditions than the optimized static VAR compensator by genetic algorithm and the optimized static VAR compensator by bacteria foraging. The results of the developed flower pollination algorithm based static VAR compensator are observed via time-domain analysis, eigenvalues, and various indices. Also, the economic value of this work is confirmed. [ABSTRACT FROM PUBLISHER]

There have been a variety of studies developed to design static Var compensator (SVC) to enhance damping of electromechanical oscillations in power systems. This paper presents a novel method towards an optimal designing of SVC damping controller using shuffled frog-leaping algorithm (SFLA). The optimal parameters of the SVC controller are obtained using SFLA considering different loading conditions. A time-domain objective function is minimized using SFLA to find the optimum controller parameters. The proposed algorithm is implemented on a test system with different loading conditions. The damping characteristics of the presented technique are compared with genetic algorithm (GA) and bacteria foraging optimization algorithm (BFOA) in tuning SVC controller. The comparative analysis demonstrates the superiority of the proposed method on a wide range of operating conditions. [ABSTRACT FROM PUBLISHER]

This paper aims to select the optimal location, size, and setting parameters of SVC (Static Var Compensator) controller using MOPSO (multi-objective particle swarm optimization) to improve the power system stability in a multi-machine power system. Though power system stabilizers are mandatory requirements for damping of oscillations, its performance still gets affected by changes in network configurations, load variations, etc. Hence, installations of SVC have been suggested in this paper to achieve appreciable damping of system oscillations. However, the performance of SVC highly depends upon its parameters, suitable location, and sizes in the power network. In order to find the solution, this problem is formulated as a multi-objective function. Then, MOPSO is used to find the best answers. In this paper, two objectives are considered to improve both the transient stability of the system and the SVC investment cost. The proposed method was tested on the 10-machine 39-busbar New England test system. The results of the nonlinear simulation show that the optimum sizing, siting, and parameter setting of SVC can improve greatly the transient stability of the multi-machine power system. [ABSTRACT FROM PUBLISHER]