Particle Swarm Optimization-Based Feedback Controller for Unified Power-Quality Conditioner
TL;DR: In this article, a particle swarm optimization-based feedback controller is designed for UPQC. This feedback controller has optimal performance in various operating conditions and is robust to parametric uncertainties when compared to the conventional feedback controllers, such as the linear quadratic regulator.
Abstract: The unified power-quality conditioner (UPQC) is used to provide balanced and sinusoidal source currents and load voltages under unbalanced and distorted three-phase supply voltages and load currents in a power distribution network. In this paper, a particle swarm optimization-based feedback controller is designed for UPQC. This feedback controller has optimal performance in various operating conditions and is robust to parametric uncertainties when compared to the conventional feedback controllers, such as the linear quadratic regulator. The proposed method is implemented on a distribution system and detailed simulation and experimental results are presented.
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TL;DR: In this article, a comprehensive review on the unified power quality conditioner (UPQC) to enhance the electric power quality at distribution levels is presented, which is intended to present a broad overview on the different possible UPQC system configurations for single-phase and three-phase (threewire and four-wire) networks, different compensation approaches, and recent developments in the field.
Abstract: This paper presents a comprehensive review on the unified power quality conditioner (UPQC) to enhance the electric power quality at distribution levels. This is intended to present a broad overview on the different possible UPQC system configurations for single-phase (two-wire) and three-phase (three-wire and four-wire) networks, different compensation approaches, and recent developments in the field. It is noticed that several researchers have used different names for the UPQC based on the unique function, task, application, or topology under consideration. Therefore, an acronymic list is developed and presented to highlight the distinguishing feature offered by a particular UPQC. In all 12 acronyms are listed, namely, UPQC-D, UPQC-DG, UPQC-I, UPQC-L, UPQC-MC, UPQC-MD, UPQC-ML, UPQC-P, UPQC-Q, UPQC-R, UPQC-S, and UPQC-VA. More than 150 papers on the topic are rigorously studied and meticulously classified to form these acronyms and are discussed in the paper.
620 citations
Cites background or methods from "Particle Swarm Optimization-Based F..."
...ries inverters are realized as 3HB units (total 24 semiconductor switches) is also possible [43], [78], [129]....
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...[33], [40], [42], [51], [52], [56], [57], [60], [63], [75], [80], [81], [89], [94], [97], [107], [109], [114], [116]–[118], [120], [129], [143]–[145], [147], [150], [155]–[157], [159], [161], [163],...
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...[7]–[20], [22], [23], [25], [26], [28]–[40], [42], [44]–[56], [58]–[84], [86]–[97], [99]–[127], [129]–[144], [153]–[168] or left (hence the name left shunt UPQC (UPQC-L)) [7], [21], [24],...
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...Particle swarm optimization technique has also been utilized to develop the controller for UPQC [99], [129], [165]....
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TL;DR: A comprehensive review on the status of topological aspects of techniques used to improve the power quality in distribution network for the researchers, designers and engineers working in this area is provided.
Abstract: Recently utilities are continuously seeking cost-effective and accurate power quality (PQ) improvement techniques in order to achieve customer satisfaction. This paper intends to provide a comprehensive review on the status of topological aspects of techniques used to improve the power quality in distribution network for the researchers, designers and engineers working in this area. This review helps to select a PQ improvement technique that suits a specific application in terms of technical and economical aspects. More than 300 research publications on the state of the art of PQ improvement techniques have been rigorously analyzed, classified and listed for quick reference.
124 citations
TL;DR: In this paper, a new topology for distribution static compensator (DSTATCOM) applications with nonstiff source is proposed, which enables DSTATCOM to have a reduced dc-link voltage without compromising the compensation capability.
Abstract: The distribution static compensator (DSTATCOM) is used for load compensation in power distribution network. In this paper, a new topology for DSTATCOM applications with nonstiff source is proposed. The proposed topology enables DSTATCOM to have a reduced dc-link voltage without compromising the compensation capability. It uses a series capacitor along with the interfacing inductor and a shunt filter capacitor. With the reduction in dc-link voltage, the average switching frequency of the insulated gate bipolar transistor switches of the DSTATCOM is also reduced. Consequently, the switching losses in the inverter are reduced. Detailed design aspects of the series and shunt capacitors are discussed in this paper. A simulation study of the proposed topology has been carried out using power systems computer-aided design simulator and the results are presented. Experimental studies are carried out to verify the proposed topology.
117 citations
TL;DR: In this paper, a particle swarm optimization (PSO)-based multi-objective planning algorithm for reactive power compensation of radial distribution networks with unified power quality conditioner (UPQC) allocation is presented.
Abstract: This paper presents a particle swarm optimization (PSO)-based multi-objective planning algorithm for reactive power compensation of radial distribution networks with unified power quality conditioner (UPQC) allocation. A UPQC consists of a series and a shunt inverter. The UPQC model based on phase angle control (UPQC-PAC) is used. In UPQC-PAC, the series inverter injects a voltage with controllable phase angle in such a way that the voltage magnitude at load end remains unchanged. Due to the phase angle shift, the series inverter participates in load reactive power compensation along with the shunt inverter during healthy operating condition. In the proposed approach, the optimal location, the optimal reactive power compensation required at the location, and the optimal design parameters of UPQC are determined by minimizing three objective functions: 1) the rating of UPQC, 2) network power loss, and 3) percentage of nodes with undervoltage problem. These objectives are simultaneously minimized to obtain a set of non-dominated solutions using multi-objective PSO (MOPSO). The performances of two MOPSO variants are compared and the better one is used in all subsequent studies. A load flow algorithm including the UPQC-PAC model is devised. The performance of the proposed algorithm is validated with different case studies.
110 citations
Cites methods from "Particle Swarm Optimization-Based F..."
..., OPEN UPQC [14]; • development of new control strategy for UPQC, for example phase angle control [15], simultaneous voltage and current compensation scheme [16], and particle swarm optimization based feedback controller [17]; • minimization of the cost/VA rating of UPQC [11], [18]; • combined operation with DG [19], [20]....
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TL;DR: In this article, the authors investigate negative impacts of photovoltaic (PV) grid-tied system to the power networks, and study on performance of artificial intelligence (AI) and conventional methods in mitigating power quality event.
Abstract: Integration of renewable energy resources into power networks is the trend in power distribution system. It is to reduce burden of centralized power plant and global emissions, increase usage of renewable energy, and diverse energy supply market. However, solar photovoltaic which is a type of renewable energy resource, is found to generate peak capacity for a short duration only. Next, its output is intermittent and randomness. In addition, it changes behavior of power distribution system from unidirectional to bidirectional. As a result, it causes different types of power quality events to the power networks. Therefore, these power quality events are urged to be mitigated to further explore the potential of solar photovoltaic system. This paper aims to investigate negative impacts of photovoltaic (PV) grid-tied system to the power networks, and study on performance of artificial intelligence (AI) and conventional methods in mitigating power quality event. According to the surveys, power system monitoring, inverter, dynamic voltage regulator, static synchronous compensator, unified power quality conditioner and energy storage system are able to compensate power quality events which are caused by PV grid-tied system. From the studies, AI methods usually outperform conventional methods in terms of response time and controllability. They also show talent in multi-mode operation, which is to switch to different operation modes according to the environment. However, they require memory to achieve abovementioned tasks. It is believed that unsupervised learning AI is the future trend as it can adapt to the environment without the need of collecting large amount of data before the AI is implemented.
110 citations
References
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06 Aug 2002
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Abstract: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described.
35,104 citations
Additional excerpts
...PSO was introduced in 1995 by Kennedy and Eberhart [ 19 ], which was inspired by the social behavior of bird flocking and fish schooling....
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06 Jul 1999
TL;DR: The experimental results show that the PSO is a promising optimization method and a new approach is suggested to improve PSO's performance near the optima, such as using an adaptive inertia weight.
Abstract: We empirically study the performance of the particle swarm optimizer (PSO). Four different benchmark functions with asymmetric initial range settings are selected as testing functions. The experimental results illustrate the advantages and disadvantages of the PSO. Under all the testing cases, the PSO always converges very quickly towards the optimal positions but may slow its convergence speed when it is near a minimum. Nevertheless, the experimental results show that the PSO is a promising optimization method and a new approach is suggested to improve PSO's performance near the optima, such as using an adaptive inertia weight.
3,976 citations
TL;DR: In this paper, a new instantaneous reactive power compensator comprising switching devices is proposed, which requires practically no energy storage components, and is based on the instantaneous value concept for arbitrary voltage and current waveforms.
Abstract: The conventional reactive power in single-phase or three- phase circuits has been defined on the basis of the average value concept for sinusoidal voltage and current waveforms in steady states. The instantaneous reactive power in three-phase circuits is defined on the basis of the instantaneous value concept for arbitrary voltage and current waveforms, including transient states. A new instantaneous reactive power compensator comprising switching devices is proposed which requires practically no energy storage components.
3,331 citations
TL;DR: This paper presents a detailed overview of the basic concepts of PSO and its variants, and provides a comprehensive survey on the power system applications that have benefited from the powerful nature ofPSO as an optimization technique.
Abstract: Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. Also, it provides a comprehensive survey on the power system applications that have benefited from the powerful nature of PSO as an optimization technique. For each application, technical details that are required for applying PSO, such as its type, particle formulation (solution representation), and the most efficient fitness functions are also discussed.
2,147 citations
TL;DR: This paper compares two evolutionary computation paradigms: genetic algorithms and particle swarm optimization, and suggests ways in which performance might be improved by incorporating features from one paradigm into the other.
Abstract: This paper compares two evolutionary computation paradigms: genetic algorithms and particle swarm optimization. The operators of each paradigm are reviewed, focusing on how each affects search behavior in the problem space. The goals of the paper are to provide additional insights into how each paradigm works, and to suggest ways in which performance might be improved by incorporating features from one paradigm into the other.
1,661 citations
"Particle Swarm Optimization-Based F..." refers methods in this paper
...Compared with the genetic algorithm [22], [23], the advantage of the PSO is that it is very simple in terms of mathematical expression and understanding....
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