Artificial neural network-based dynamic equivalents for distribution systems containing active sources
27 Dec 2004-Vol. 151, Iss: 6, pp 681-688
TL;DR: In this article, an approach to identify generic dynamic equivalents to distribution systems using recurrent artificial neural networks (ANN)s is presented, which depends on variables at the boundary buses, hence no knowledge of the parameters and the topology of the distribution system is needed.
Abstract: An approach to identify generic dynamic equivalents to distribution systems using recurrent artificial neural networks (ANN)s is presented. It is expected that in the near future a large number of active sources will be utilised within distribution systems and thus, neither detailed modelling nor lumped-load representation for distribution areas will be acceptable. Therefore, the paper suggested training a recurrent ANN to represent the dynamic behaviour of the distribution network is. To involve the dynamic characteristics in the ANN, values of the features that are involved are also introduced at the input layer, thereby defining the order of the dynamic equivalent. The approach depends on variables at the boundary buses, hence no knowledge of the parameters and the topology of the distribution system is needed. At the same time, the computational requirements and the accuracy of the proposed technique are independent of the size and complexity of the network. A 16-machine test network with 112 active distributed sources in the low-voltage area is used to verify the suggested method. Comparisons between the response of the original system and the ANN-based dynamic equivalent show the accuracy of the equivalent model and the validity of the proposed method.
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TL;DR: In this paper, the grey-box approach was used for model development as it incorporates prior knowledge about the ADN structure into the model, making the model more physically relevant and intuitive than black-box or white-box models, and potentially improves the accuracy of the model.
Abstract: This paper presents the development of the dynamic equivalent model of an active distributed network (ADN) based on the grey-box approach. The equivalent model of an ADN comprises a converter-connected generator and a composite load model in parallel. The grey-box approach was chosen for model development as it incorporates prior knowledge about the ADN structure into the model, makes the model more physically relevant and intuitive than black-box or white-box models, and potentially improves the accuracy of the model. The dynamic equivalent model is presented in the seventh-order nonlinear state space format. It was initially loosely developed from the algebraic and differential equations describing assumed typical components of an ADN. Various static load models, dynamic load compositions, fault locations and a diverse range of distributed generation types and scenarios are considered in order to establish the generic range of model parameters for an ADN. The model is intended for the use in large power system stability studies.
110 citations
Cites background from "Artificial neural network-based dyn..."
...Dynamic equivalents of distribution networks have also been based on a recurrent artificial neural network (ANN) [11], [12]....
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TL;DR: The dynamic equivalent model of ADNC is presented in a seventh-order nonlinear quasi state space format, developed from the algebraic and differential equations describing assumed typical components of the ADNC.
Abstract: Paper presents an equivalent model of an active distribution network cell (ADNC) with distributed generation for transmission system stability studies. The equivalent model of ADNC comprises a converter-connected generator and a composite load model in parallel. The gray-box approach was chosen as it enables inclusion of prior knowledge about the ADNC structure into the model development, hence making the model more physically relevant and intuitive than a black-box or white-box model. The dynamic equivalent model is presented in a seventh-order nonlinear quasi state space format, developed from the algebraic and differential equations describing assumed typical components of the ADNC. The developed equivalent model of ADNC was validated through small and large disturbance studies using the modified IEEE nine-bus transmission system model.
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References
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TL;DR: In this article, the main factors that affect the quality of the reduced models are discussed and the benefits of dynamic reductions are demonstrated for three large interconnected power system models for stability studies.
Abstract: This paper documents experience with applications of dynamic reductions to large power system models for stability studies. The main factors that affect the quality of the reduced models are discussed. The quality of reduced models and the benefits of dynamic reductions are demonstrated for three large interconnected power systems.
201 citations
TL;DR: In this article, the results of applying the EPRI Dynamic Equivalencing Program to a large-scale system test case of the New York Power Pool are presented. And the effects of coherent generator selection, network reduction, generator aggregation, and generator modeling on the accuracy of the reduced models are investigated.
Abstract: This paper presents the results of applying the EPRI Dynamic Equivalencing Program to a large-scale system test case of the New York Power Pool. The effects of coherent generator selection, network reduction, generator aggregation, and generator modeling on the accuracy of the reduced models are investigated.
74 citations
TL;DR: In this paper, a trajectory sensitivity method is used to tune the aggregate exciter parameters of the reduced model and the optimal results are used to evaluate the aggregation from the DYNRED program and a weighted MVA method.
Abstract: Constructing a dynamic equivalent for a power system involves several steps: the partition of the system into coherent areas, the coherent area aggregation, and the aggregation of the coherent generators and their control devices. In this paper we investigate the aggregation of exciter models. A trajectory sensitivity method is used to tune the aggregate exciter parameters of the reduced model. The optimal results are used to evaluate the aggregation from the DYNRED program and a weighted MVA method. A three-machine system with one coherent area satisfying the theoretical coherency conditions is used to investigate the impact of the variations of the individual generator, network, and exciter parameters on the aggregate exciter model parameters. The results are then applied to the exciter aggregation of a larger 48-machine system.
60 citations
TL;DR: A novel clustering method using an artificial neural network (ANN) is presented to identify the coherent generators for dynamic equivalents of power systems with rather encouraging results.
Abstract: A novel clustering method using an artificial neural network (ANN) is presented to identify the coherent generators for dynamic equivalents of power systems. First, a new frequency measure is devised to indicate the degree of coherency among system generators. Incorporating with the frequency measure, a neural network implementation of the K-means algorithm is then proposed to identify clusters of coherent generators. The rotor speeds at three selected instants in time are used as the feature patterns for the learning algorithm. To verify the effectiveness of the proposed method, extensive analyses are performed on two different power systems of varying sizes with rather encouraging results. >
55 citations
01 Jan 1998
TL;DR: In this article, a simple dynamic equivalent of an external area containing a group of coherent generators is presented, where the formulation of this equivalent is based on decomposition and aggregation of the coherent generators.
Abstract: The development of a simple dynamic equivalent of an external area containing a group of coherent generators is presented. The formulation of this equivalent is based on decomposition and aggregation of coherent generators. The dynamic equivalent has a power system structure and is connected to the internal area at a set of common boundary buses which separate the two areas. The dynamic equivalent is developed in two stages. A multigenerator dynamic equivalent is first formed, then extended to a single-generator equivalent. Unlike the conventional coherency-based reduction techniques of forming the dynamic equivalents, the proposed technique does not require measurement data at the original generators of the external area to determine the parameters of the resulting dynamic equivalent. This important feature makes the proposed dynamic equivalent attractive and suitable for online transient stability assessment. With the knowledge of only the passive network model of the external area and the total inertia constant of the generators in this area, the parameters of this equivalent are determinable from a set of measurement data taken solely at the boundary buses. The performance of the equivalent has been evaluated. Test results show outstanding quality of the proposed equivalent.
26 citations