73 research outputs found

    Improvement of Power Quality in Primary Distribution Systems Based on Static-Var Compensators

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    A flexible AC Transmission Systems (FACTS) is a new technology offers a fast and reliable control over the transmission and distribution parameters like voltage and phase angle between the sending end voltage and receiving end voltage. Distribution static synchronous compensator (DSTATCOM) is a second generation member of the (FACTS) controllers. Reactive power compensation is an important aspect in the control of distribution systems. Reactive current in addition to increasing the distribution system losses, introduces voltage drop at lead point and finally it causes poor power quality in power systems. Primary radial distribution feeders have high resistance to reactance ratio, which causes voltage drop and high power loss in radial distribution systems. providing high demanding power to entire load while maintaining voltage magnitude at acceptable range is one of the major system constraints, using of capacitor banks to improve the reactive power have not quite enough at high reactive power feeder, because it have more slow in step by step response and have not capable to generate continuously variable reactive power. In some primary distribution feeders at the state of Khartoum, it is observed that there are some appropriate drops in voltage and quality service at high reactive power loads although some individual capacitor banks have been connected at these feeders, from here we researched for a new technology to overcome this problem. A steady-state model of (DSTATCOM) is proposed and developed to compensate the reactive power by using a Voltage Source Converter (VSC) with Pulse Width Modulation (PWM) and cascade control of four direct proportional integral controllers (PI) in synchronous reference frame. The detailed modeling and control design of (DSTATCOM) with specific typical radial primary distribution feeders (industrial, commercial, residential) are presented and implemented along necessary mathematical model equations in the Matlab software. Simulation schemes of (DSTATCOM) are done with help of control block diagrams and stability analysis. Load flow is an important method for analysis, operation and planning studies of any power system in a steady-state condition. In this research backward forward sweeps load flow method (Kirchhoff’s Laws) has been proposed rather than Newton-Raphson and Fast decoupled methods because the distribution feeders have a high R/X ratio which make the systems are ill-conditioned iterations analysis. (DSTATCOM) was installed on specific typical radial feeders at the (DSTATCOM) which using for distribution lines and load compensation has been the subject of considerable interest beside it is a new technology for a good power quality solution. Keywords: Power System, Flexible AC Transmission Systems (FACTS) Devices, STATCOM, PI Controller DOI: 10.7176/ISDE/13-1-05 Publication date:May 31st 202

    CANFIS based DSTATCOM modelling for solving power quality problems

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    Devolution of the power grid into smart grid was necessitated by the proliferation of sensitive load profiles into the system, as well as incessant environmental challenges. These two factors culminated into aggravated disturbances that cause serious havoc along the entire system structure. The traditional proportional-plus-integral-plus-derivative (PID) solution offered by the distribution synchronous compensator (DSTATCOM) could no longer hold. As such, this paper proposes some soft-computing framework for redesigning DSTATCOM to automatically deal with power quality (PQ) problems in smart distribution grids. A recipe of artificial neural network (ANN) and coactive neuro-fuzzy inference systems (CANFIS) was fabricated for the objective. The system was modelled, simulated, and validated in MATLAB/Simulink SimPowerSystems environment. The performance of the CANFIS against adaptive neuro-fuzzy inference systems (ANFIS), ANN and fuzzy logic controllers’ algorithms proved superior in handling PQ issues like voltage sag, voltage swell and harmonics

    Planning of Unbalanced Radial Distribution Systems with Reactive and Distributed Energy Sources Using Evolutionary Computing Techniques

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    The distribution system plays a key role in power system as it provides energy to the consumers safely, reliably, and economically. However, due to high R/X ratio, and low operating voltages, most of the losses occur in the distribution system. Moreover, distribution systems are generally unbalanced due to unequal single phase loads at the three phases of the system, and also additional unbalancing is introduced due to non-equilateral conductor spacing. This, causes the voltage, the current, and the power unbalance in the system. Further, the total neutral current of the system increases causing unwanted tripping of the relay. Hence, the service quality and the reliability of the distribution system reduces. Therefore, a suitable phase balancing strategy is required to mitigate the phase unbalancing in the unbalanced distribution systems. Also, apart from reducing the phase unbalancing in the unbalanced distribution systems, a suitable strategy is required to minimize the system power loss. In this regard, it is necessary for the distribution engineers to plan the unbalanced distribution systems in order to reduce the losses, voltage unbalances, and neutral current of the system for safe and reliable operation. Most of the approaches for the planning of the unbalanced distribution systems are based upon metaheuristic algorithms. Moreover, the recent research has focused only on either phase balancing or simultaneous phase balancing and conductor sizing optimization in unbalanced distribution systems using metaheuristic algorithms. However no work has been carried out to study the impact of the simultaneous optimization of the phase balancing, the conductor sizing, the capacitor location and sizing, the DG location and sizing, DSTATCOM location, and rating on system power loss, voltage unbalance, etc. utilizing these algorithms. As the metaheuristic algorithms are random in nature, the convergence is not guaranteed in a single simulation run. Hence, it is necessary to perform a statistical comparison among them in order to understand their relative merits and demerits for multiple simulation runs. In this thesis, the impact of the simultaneous optimization of the phase balancing and the conductor sizing on the planning problems/objective functions of the unbalanced distribution system such as; the power loss, the voltage unbalance, the total neutral current, and the complex power unbalance studied using various metaheuristic algorithms such as the DE, the CSA, the PSO, and the GA. In the first step, these objective functions are optimized separately; then they are aggregated with weights into a multi-objective optimization problem. Further, a performance comparison in terms of the mean value of the objective functions and standard deviation (SD) carried out. The reactive power compensating devices, such as the Capacitor, and the DSTATCOM has been integrated into the planning problem for the power loss minimization, the voltage profile improvement, and the voltage unbalance mitigation of the unbalanced distribution systems. Moreover, a three phase unbalanced modelling of the DSTATCOM has been developed. In this thesis, the effect of the simultaneous optimization of the phase balancing, the conductor sizing, the capacitor sizing, and the simultaneous optimization of the phase balancing, the conductor sizing, and the DSTATCOM sizing on the planning problem investigated. Both, single and multi-objective optimization approach are used in order to solve this problem. Also, statistical performance among the metaheuristic algorithms such as; the DE, the CSA, the PSO, and the GA in terms of the mean value of the objective function and SD carried out. Further, the renewable sources such as the DG and a combined DG and DSTATCOM has been incorporated into the unbalanced system in order to study their impact on various planning problems

    Planning and Operation of DSTATCOM in Electrical Distribution Systems

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    In present day scenario, it is most essential to consider the maximum asset performance of the power distribution systems to reach the major goals to meet customer demands. To reach the goals, the planning optimization becomes crucial, aiming at the right level of reliability, maintaining the system at a low total cost while keeping good power quality. There are some problems encountered which are hindering the effective and efficient performance of the distribution systems to maintain power quality. These problems are higher power losses, poor voltage profile near to the end customers, harmonics in load currents, sags and swells in source voltage etc. All these problems may arise due to the presence of nonlinear loads, unpredictable loads, pulse loads, sensor and other energy loads, propulsion loads and DG connections etc. Hence, in order to improve the power quality of power distribution systems, it is required to set up some power quality mitigating devices, for example, distribution static synchronous compensator (DSTATCOM), dynamic voltage restorer (DVR), and unified power quality conditioner (UPQC) etc. The goal of this project work is to devise a planning of optimal allocation of DSTATCOM in distribution systems using optimization techniques so as to provide reactive power compensation and improve the power quality

    Dynamic voltage restorer quality improvement analysis using particle swarm optimization and artificial neural networks for voltage sag mitigation

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    Power quality is one of the problems in power systems, caused by increased nonlinear loads and short circuit faults. Short circuits often occur in power systems and generally cause voltage sags that can damage sensitive loads. Dynamic voltage restorer (DVR) is an efficient and flexible solution for overcoming voltage sag problems. The control system on the DVR plays an important role in improving the quality of voltage injection applied to the network. DVR control systems based on particle swarm optimization (PSO) and artificial neural networks (ANN) were proposed in this study to assess better controllers applied to DVRs. In this study, a simulation of voltage sag due to a 3-phase short-circuit fault was carried out based on a load of 70% of the total load and a fault location point of 75% of the feeder’s length. The simulation was carried out on the SB 02 Sibolga feeder. Modeling and simulation results are carried out with MATLAB-Simulink. The simulation results show that DVR-PSO and DVR-ANN successfully recover voltage sag by supplying voltage at each phase. Based on the results of the analysis shows that DVR-ANN outperforms DVR-PSO in quality and voltage injection into the network

    Embedding quasi-static time series within a genetic algorithm for stochastic optimization: the case of reactive power compensation on distribution systems

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    This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required

    New typical power curves generation approach for accurate renewable distributed generation placement in the radial distribution system

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    This paper investigates, for the first time, the accuracy of normalized power curves (NPCs), often used to incorporate uncertainties related to wind and solar power generation, when integrating renewable distributed generation (RDG), in the radial distribution system (RDS). In this regard, the present study proposes a comprehensive, simple, and more accurate model, for estimating the expected hourly solar and wind power generation, by adopting a purely probabilistic approach. Actually, in the case of solar RDG, the proposed model allows the calculation of the expected power, without going through a specific probability density function (PDF). The validation of this model is performed through a case study comparing between the classical and the proposed model. The results show that the proposed model generates seasonal NPCs in a less complex and more relevant way compared to the discrete classical model. Furthermore, the margin of error of the classical model for estimating the expected supplied energy is about 12.6% for the photovoltaic (PV) system, and 9% for the wind turbine (WT) system. This introduces an offset of about 10% when calculating the total active losses of the RDS after two RDGs integration

    Power quality improvement in low voltage distribution network utilizing improved unified power quality conditioner.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.The upgrade of the power system, network, and as it attained some complexity level, the voltage related problems and power loss has become frequently pronounced. The power quality challenges load at extreme end of the feeder like voltage sag and swell, and power loss at load centre due to peak load as not received adequate attention. Therefore, this research proposes a Power Angle Control PAC approach for enhancing voltage profile and mitigating voltage sag, voltage swell, and reduced power loss in low voltage radial distribution system (RDS). The amelioration of voltage sag, voltage swell, weak voltage profile, and power loss with a capable power electronics-based power controller device known as Improve Unified Power Quality Conditioner I-UPQC was conceived. Also, the same controller was optimally implemented using hybrid of genetic algorithm and improved particle swarm optimization GA-IPSO in RDS to mitigate the voltage issues, and power loss experienced at peak loading. A new control design-model of Power Angle Control (PAC) of the UPQC has been designed and established using direct, quadrature, and zero components dq0 and proportional integral (PI) controller method. The simulation was implemented in MATLAB/Simulink environment. The results obtained at steady-state condition and when the new I-UPQC was connected show that series inverter can participate actively in ameliorating in the process of mitigating sag and swell by maintaining a PAC of 25% improvement. It was observed that power loss reduced from 1.7% to 1.5% and the feeder is within the standard limit of ±5%. Furthermore, the interconnection of I-UPQC with photovoltaic solar power through the DC link shows a better voltage profile while the load voltage within the allowable range of ±5% all through the disturbance and power loss reduction is 1.3%. Lastly, results obtained by optimal allocation of I-UPQC in RDS using analytical and GA-IPSO show that reactive power injection improved the voltage related issues from 0.952 to 0.9989 p.u., and power loss was further reduced to 1.2% from 3.4%. Also, the minimum bus voltage profile, voltage sag, and power loss are within statutory limits of ±5 % and less than 2 %, respectively. The major contributions of this research are the reduction of sag impact and power loss on the sensitive load in RDS feeder.Publications on page iii
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