186,834 research outputs found

    Identification Of Weak Buses In Electrical Power System Based On Modal Analysis And Load Power Margin

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    This paper presents the identification of weak buses in electrical power system with the use of modal analysis technique and load power margin values. A weak bus can be defined as a load bus that has high tendency towards experiencing voltage instability. This type of bus cannot afford high value of load incremental values. The modal analysis technique will show the list of weak buses in the power system. Meanwhile load power margin is very useful for showing how much the load at the bus can be increased before experiencing voltage instability. Both modal analysis technique and load power margin values are applied upon the IEEE 39-bus test power system. From there, five weak buses in the test power system are selected and compared. The results proved that weak buses determined by modal analysis technique have low load power margin values

    Voltage stability analysis of load buses in electric power system using adaptive neuro-fuzzy inference system (anfis) and probabilistic neural network (pnn)

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    This paper presents the application of neural networks for analysing voltage stability of load buses in electric power system. Voltage stability margin (VSM) and load power margin (LPM) are used as the indicators for analysing voltage stability. The neural networks used in this research are divided into two types. The first type is using the neural network to predict the values of VSM and LPM. Multilayer perceptron back propagation (MLPBP) neural network and adaptive neuro-fuzzy inference system (ANFIS) will be used. The second type is to classify the values of VSM and LPM using the probabilistic neural network (PNN). The IEEE 30-bus system has been chosen as the reference electrical power system. All of the neural network-based models used in this research is developed using MATLAB

    Online Voltage Stability Assessment for Load Areas Based on the Holomorphic Embedding Method

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    This paper proposes an online steady-state voltage stability assessment scheme to evaluate the proximity to voltage collapse at each bus of a load area. Using a non-iterative holomorphic embedding method (HEM) with a proposed physical germ solution, an accurate loading limit at each load bus can be calculated based on online state estimation on the entire load area and a measurement-based equivalent for the external system. The HEM employs a power series to calculate an accurate Power-Voltage (P-V) curve at each load bus and accordingly evaluates the voltage stability margin considering load variations in the next period. An adaptive two-stage Pade approximants method is proposed to improve the convergence of the power series for accurate determination of the nose point on the P-V curve with moderate computational burden. The proposed method is illustrated in detail on a 4-bus test system and then demonstrated on a load area of the Northeast Power Coordinating Council (NPCC) 48-geneartor, 140-bus power system.Comment: Revised and Submitted to IEEE Transaction on Power System

    Active damping of a DC network with a constant power load: an adaptive passivity-based control approach

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    This paper proposes a nonlinear, adaptive controller to increase the stability margin of a direct-current (DC) small-scale electrical network containing a constant power load, whose value is unknown. Due to their negative incremental impedance, constant power loads are known to reduce the effective damping of a network, leading to voltage oscillations and even to network collapse. To tackle this problem, we consider the incorporation of a controlled DC-DC power converter between the feeder and the constant power load. The design of the control law for the converter is based on the use of standard Passivity-Based Control and Immersion and Invariance theories. The good performance of the controller is evaluated with numerical simulations.Postprint (author's final draft

    Voltage instability analysis for electrical power system using voltage stabilty margin and modal analysis

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    Voltage instability analysis in electric power system is one of the most important factors in order to maintain the equilibrium of the power system. A power system is said to be unstable if the system is not able to maintain the voltage at all buses in the system remain unchanged after the system is being subjected to a disturbance.The research work presented in this paper is about the analysis of voltage instability of electric power system by using voltage stability margin (VSM), load real power (P) margin, reactive power (Q) margin, reactive power-voltage (QV) and real power-voltage (PV) modal analysis. IEEE 30-bus system has been chosen as the power system. The load flow analysis are simulated by using Power World Simulator software version 16. Both QV and PV modal analysis were done by using MATLAB application software

    Distribution of Optimum Reactive Power in the Presence of Wind Power Plant and considering Voltage Stability Margin using Genetic Algorithm and Monte Carlo methods

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    Network reactive power resources are important factors affecting voltage stability that somehow can have effect on safety margin of system voltage stability. In this study, question of relationship between distribution of optimum reactive power and voltage stability margin in presence of wind power plant has been performed. For this reason, to minimize the reactive power costs due to the synchronous generator, synchronous condenser and the capacitor bank and also given the importance maximization the voltage stability margin and considering equality and inequality constraints, has been used from a nonlinear programming method. In here, problem by using Genetic Algorithm in order to minimize cost of reactive power and with considering the voltage stability margin based on Monte Carlo simulation method. In MATLAB software has been optimized. Problem simulation over 30-bus network has been solved for two state low load and full load and with two scenarios was run and analyzed

    Classifications of voltage stability margin (VSM) and load power margin (LPM) using probabilistic neural network (PNN)

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    Voltage stability margin (VSM) and load power margin (LPM) arethe indicators that show how close a load bus is to experiencing voltage instability. The smaller the values of VSM or LPM of a particular load bus, the closer the load bus towards voltage instability. This paper presents the application of probabilistic neural network (PNN) for classifying VSM and LPM values. A number of training data is generated for the PNN model to classify. The PNN model used in this paper should be able to classify which values are within VSM/LPM values and which values are not. The IEEE 14-bus system has been chosen as the reference electrical power system. MATLAB is used to deploy the PNN model for VSM and LPM classifications

    Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties

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    Optimal design of a standalone wind-PV-diesel hybrid system is a multi-objective optimisation problem with conflicting objectives of cost and reliability. Uncertainties in renewable resources, demand load and power modelling make deterministic methods of multi-objective optimisation fall short in optimal design of standalone hybrid renewable energy systems (HRES). Firstly, deterministic methods of analysis, even in the absence of uncertainties in cost modelling, do not predict the levelised cost of energy accurately. Secondly, since these methods ignore the random variations in parameters, they cannot be used to quantify the second objective, reliability of the system in supplying power. It is shown that for a given site and uncertainties profile, there exist an optimum margin of safety, applicable to the peak load, which can be used to size the diesel generator towards designing a cost-effective and reliable system. However, this optimum value is problem dependent and cannot be obtained deterministically. For two design scenarios, namely, finding the most reliable system subject to a constraint on the cost and finding the most cost-effective system subject to constraints on reliability measures, two algorithms are proposed to find the optimum margin of safety. The robustness of the proposed design methodology is shown through carrying out two design case studies
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