Optimal Localization and Sizing of UPFC to Solve the Reactive Power Dispatch Problem Under Unbalanced Conditions

Kapse, Shilpa S. Shrawane; Daigavane, M. B.; Daigavane, Prema

doi:10.1080/03772063.2018.1491808

Cited by 16 publications

(5 citation statements)

References 33 publications

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“…The uncertain power demands in a power system are commonly modeled by the normal distribution. The probability density function (PDF) of this distribution is according to (11). 20…”

Section: Power Demand Modelingmentioning

confidence: 99%

“…The optimal location and capacity of UPFC are proposed to improve the dynamic stability of the power system considering power losses and voltage deviation improvement in Reference 10. In Reference 11 a method is presented to determine the optimal location and UPFC sizing in the multi‐objective optimal reactive power dispatch (ORPD) problem considering unbalanced conditions. The Load‐ability maximization, voltage profile improvement, losses minimization, and available transfer capability (ATC) enhancement are the components of the proposed objective function.…”

Section: Introductionmentioning

confidence: 99%

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Data clustering based probabilistic UPFC allocation for improving power system reliability considering correlated uncertain variables

Rezaeian‐Marjani

Nazarpour

Galvani

2021

Int Trans Electr Energ Syst

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Summary Flexible alternating‐current transmission system (FACTS) devices as power electronic‐based technologies have been developed to improve the performance of power systems. This paper proposes a probabilistic framework for optimal allocation of unified power flow controller (UPFC) as one of the most beneficial FACTS devices to increase the reliability of the power system. For this purpose, the expected power not served (EPNS) is considered as a reliability index that is obtained based on the summation of required load shedding in all buses during single contingencies, including transmission lines and generators outage. Power demands and wind speed are considered as uncertain input variables. In addition, the correlations among these variables are included in the proposed study method. The well‐known particle swarm optimization (PSO) algorithm is used to optimize the proposed objective function. Also, the firefly algorithm (FA) is implemented to determine the total amount of load shedding for the calculation of EPNS, considering each possible generated solution by the PSO. The k‐means based data clustering method (DCM) is used for probabilistic evaluation of the problem, for the first time. Also, the correlations among uncertain input variables are modeled with the Cholesky decomposition method. Extraction of statistical information of UPFC parameters for improving power system reliability in a probabilistic framework is one of the most important achievements of the proposed method. This information is very important in deciding on the UPFC sizing. In order to evaluate the effectiveness of the proposed method, the IEEE 14‐bus and 30‐bus test systems have been used.

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“…The uncertain power demands in a power system are commonly modeled by the normal distribution. The probability density function (PDF) of this distribution is according to (11). 20…”

Section: Power Demand Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data clustering based probabilistic UPFC allocation for improving power system reliability considering correlated uncertain variables

Rezaeian‐Marjani

Nazarpour

Galvani

2021

Int Trans Electr Energ Syst

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“…Many researchers have presented sensitivity-based methods in the literature. Fractional Levy light-BatAlgorithm [20], Hybrid Cuckoo-Search-Algorithm [21], Modified-Differential evolution [22], Combined pso-based CPF [23], numerous-sensitivity-based-approaches [24], genetic algorithm [25][26][27][28][29][30][31][32], refined-power-flow-algorithm [33], multiverse optimizer [34], reactive power dispatch problem [35], adaptive grass hooper optimization [36], Heuristic-Techniques [37], MILP-based-OPF [38], AWO-optimization [39], Gravitational-search-assisted algorithm [40][41][42], whale-optimization-algorithm [43,44], novel-lightning search-algorithm [45], PSO-adaptive-G.S.A. hybrid-algorithm [46], self-adaptive-DE-algorithm [47], fuzzy-harmony search algorithm [48], imperialisticcompetitive-algorithm [49], quasi-oppositional-chemical reaction optimization [50], brain-storm-optimization-algorithm [51], hybrid immune algorithm [52], teachinglearning-based-optimization [53], marine-vessels-analysis [54], optimal-power-flowproblem [55], evolutionary-particle swarm optimization [56], blended-moth flame optimization [57], population-based-evolutionary-optimization [58], MOPSO-algorithm…”

Section: Introductionmentioning

confidence: 99%

A review of FACTS device implementation in power systems using optimization techniques

Chethan,

Kuppan

2024

J. Eng. Appl. Sci.

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In electrical power systems, FACTS devices effectively control power flow and change bus voltages, leading to lower system losses and excellent system stability. The article discusses the research from the last decade that evaluated various methods for placing FACTS devices using the meta-heuristic approach to address the positioning of FACTS devices to maintain proper bus voltages and control line flow and improve the overall system efficiency. The need for more efficient electricity systems management has given rise to innovative technologies in power generation and transmission. The combined cycle power station is a good example of a new development in power generation and flexible AC transmission systems, generally known as FACTS, are controllers that improve transmission systems. Worldwide transmission systems are undergoing continuous changes and restructuring. They are becoming more heavily loaded and are being operated in ways not originally envisioned. Transmission systems must be flexible to react to more diverse generation and load patterns. In addition, the economical utilization of transmission system assets is of vital importance to enable utilities in industrialized countries to remain competitive and to survive. In developing countries, the optimized use of transmission systems investments is also important to support industry, create employment and utilize efficiently scarce economic resources. FACTS controller is a technology that responds to these needs. It significantly alters the way transmission systems are developed and controlled together with improvements in asset utilization, system flexibility and system performance. Several models and techniques suggest that devices can be placed in a particular location with different parameter settings. Finally, the optimization problem improved system performance by decreasing power loss, improving the voltage profile and power angle at each bus, raising the L-index, and minimizing generating costs. FACTS devices can increase the transmission line’s capacity for transferring power by increasing the voltage at its terminals at both ends and reducing line reactance. The FACTS controller must be installed in the distribution and transmission lines to maximize the power flow. Various techniques are used for the best placement of FACTS controllers, including analytical methods, arithmetic programming approaches, meta-heuristic optimization approaches, and hybrid approaches—this paper analyses numerous analytical and meta-heuristic optimization techniques to place FACTS controllers in the most advantageous locations. The fundamental problems in intelligent power systems, such as improving stability, power quality, and managing congestion, are discussed in this study, along with several applications of FACTS devices. The cutting-edge power systems of today provide users with constant, high-quality power through smart grids and smart meters.

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“…In some other articles, criteria weights determined by the decision maker were used [22]- [31]. In some publications, weights were used both equally and at the values determined by the decision maker and in different combinations according to different scenarios [32]- [36]. In all these studies, decision makers determined criteria weights according to their own importance levels, but did not control their consistency.…”

Section: Introductionmentioning

confidence: 99%

Determining Optimal SVC Location for Voltage Stability Using Multi-Criteria Decision Making Based Solution: Analytic Hierarchy Process (AHP) Approach

Aydin¹,

Gümüş²

2021

IEEE Access

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Due to latest blackouts in the world, voltage instability and voltage collapse have become the main issues studied in electrical power systems. For this purpose, various Flexible AC Transmission Systems (FACTS) devices have been utilized for many years, increasing voltage stability while at the same time improving system performance, reliability, supply quality and providing environmental benefits. These devices location for enhancing voltage stability is a significant problem for actual power networks. When determining the best location of the controller, an optimal solution should be found to increase the loading margin and also reduce voltage deviation and power losses. In the literature, the weight coefficients of the criteria were chosen equally or approximate values were obtained by trial and error method and Multi-Criteria Decision Making (MCDM) techniques have never been used in finding the optimal location of FACTS devices. This article presents a novel technique for optimal location of Static Var Compensator (SVC) devices in power systems using MCDM. The simulation was conducted on Power System Analysis Toolbox (PSAT) in MATLAB. In the proposed approach, IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test systems were used and the optimal location was found out with Analytic Hierarchy Process (AHP), an MCDM technique. The consistency of the results has been checked and the reliability has been increased, and the results of the application are promising. In addition, the optimal location of the SVC for different contingencies was found, and the effects of the overloaded lines and Phase-Shifting Transformer (PST) on the network were analyzed.

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Optimal Localization and Sizing of UPFC to Solve the Reactive Power Dispatch Problem Under Unbalanced Conditions

Cited by 16 publications

References 33 publications

Data clustering based probabilistic UPFC allocation for improving power system reliability considering correlated uncertain variables

Data clustering based probabilistic UPFC allocation for improving power system reliability considering correlated uncertain variables

A review of FACTS device implementation in power systems using optimization techniques

Determining Optimal SVC Location for Voltage Stability Using Multi-Criteria Decision Making Based Solution: Analytic Hierarchy Process (AHP) Approach

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