Voltage control with inverter-based distributed generation

Bollen, M.H.J.; Sannino, A.

doi:10.1109/tpwrd.2004.834679

Cited by 143 publications

(17 citation statements)

References 2 publications

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“…The fractal structure presented in Table 1 thus shows a design anomaly in level 3, the gray element. In contrast, in level 4, the table is already filled, because with the integration of rooftop PVs, associated inverters are used to support the voltage control in low voltage grids by providing reactive power (almost purely inductive) [60]. Studies have shown that the use of customers' own devices to control the voltage on low voltage grids is technically not effective [61,62] and can lead to social problems [63].…”

Section: Fractality In Smart Gridsmentioning

confidence: 99%

Design of the Smart Grid Architecture According to Fractal Principles and the Basics of Corresponding Market Structure

Ilo

2019

Energies

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Nowadays, there is a dramatic upsurge in the use of renewable energy resources, ICT and digitalization that requires more than the straightforward refinements of an established power system structure. New solutions are required to perform dynamic optimizations in real time, closed loops and so on, taking into account the high requirements on data privacy and cyber security. The LINK-paradigm was designed to meet these requirements. It was developed on the basis of the bottom-up method that can lead to misinterpretations or wrong conclusions. This work mainly deals with the verification of the authenticity and correctness of LINK. Fractal analysis is used to identify the unique and independent elements of smart grids required for the design of an architectural paradigm. The signature of the fractal structure, the so-called fractal pattern, is founded and referred to as electrical appliances (ElA). The latter has proven to be the key component of the architectural LINK paradigm. The definition of the LINK paradigm is finally validated: It consists of unique and independent elements that avoid misinterpretation or the need for any changes in its definition. Additionally, the fractal analysis indicates two fractal anomalies in the existing power system structure, while the fractal dimension calculation insinuates the highest complexity in the fractal level of electrical devices. The LINK-based holistic architecture is given a finishing touch. A compact presentation of the control chain strategy is provided that should facilitate its practical implementation. The basis for the harmonization of the market structure with the grid link arrangements is established. The processes of demand response and conservation voltage reduction are presented under the new findings.

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Section: Fractality In Smart Gridsmentioning

confidence: 99%

Design of the Smart Grid Architecture According to Fractal Principles and the Basics of Corresponding Market Structure

Ilo

2019

Energies

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“…After the steady state subgraphs were generated, we needed to evaluate the robustness of the ADN using Equation (1). The evaluation algorithm is proposed in Algorithm 2, which is used to evaluate the proportion of normal operational nodes in the ADN.…”

Section: Evaluation Robustnessmentioning

confidence: 99%

“…In recent years, many countries strongly support the access of a great many distributed generators to low/medium voltage distribution networks [1,2], which are called active distribution networks (ADNs). The basic goal of designing an ADN is to provide users with convenient and real-time Due to the intrinsic complexity and the characteristic of deep interdependence between the PN and CN, the ADN is vulnerable to cross-domain cascading failures (CCFs) which propagate across nodes from the PN and CN interchangeably [5,6].…”

Section: Introductionmentioning

confidence: 99%

Cyber–Physical Active Distribution Networks Robustness Evaluation against Cross-Domain Cascading Failures

et al. 2019

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Active distribution networks (ADNs) are a typical cyber-physical system (CPS), which consist of two kinds of interdependent sub-networks: power networks (PNs) and communication networks (CNs). The combination of typical characteristics of the ADN includes (1) a large number of distributed generators contained in the PN, (2) load redistribution in both the PN and CN,and (3) strong interdependence between the PN and CN, which makes ADNs vulnerable to cross-domain cascading failures (CCFs). In this paper, we focus on the robustness analysis of the ADN against the CCF. Rather than via the rate of the clusters with size greater than a predefined threshold, we evaluate the robustness of the ADN using the rate of the clusters containing generators after the CCF. Firstly, a synchronous probabilistic model is derived to calculate the proportions of remaining normal operational nodes after the CCF. With this model, the propagation of the CCF in the ADN can be described as recursive equations. Secondly, we analyze the relationship between the proportions of remaining normal operational nodes after the CCF and the distribution of distributed generators, unintentional random initial failure rate, the interdependence between the sub-networks, network topology, and tolerance parameters. Some results are revealed which include (1) the more distributed generators the PN contains, the higher ADN robustness is, (2) the robustness of the ADN is negatively correlated with the unintentional random initial failure rate, (3) the robustness of the ADN can be improved by increasing the average control fan in of each node in the PN and the average power fan in of each node in the CN, (4) the robustness of the ADN with Erdos-Renyi (ER) network topological structure is greater than that with Barabasi-Albert (BA) network topological structure under the same average node degree, and (5) the robustness of the ADN is greater, when the tolerance parameters increase. Lastly, some simulation experiments are conducted and experimental results also demonstrate that the conclusions above are effective to improve the robustness of the ADN against the CCF.Appl. Sci. 2019, 9, 5021 2 of 32 electricity [3]. As shown in Figure 1, the ADN is a large complex network that consists of two interdependent sub-networks: power networks (PNs) and communication networks (CNs) [4]. The PN is composed of the power equipment, such as generators, transmission lines, substations, and loads, etc. The CN is composed of the information equipment, such as sensors, computers, communication lines, data storage, and actuators, etc. All these equipment are interconnected according to a certain topological structure. Some nodes in the PN supply power to the nodes in the CN, meanwhile some nodes in the CN collect information of the nodes in the PN and thus to control the actions of them. In general, the operational process of the ADN includes the physical process and the computational process. The physical process can be described by the continuous change of the PN parameters (e.g....

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“…The integration of a DG with high variability in a conventional network may create a voltage problem [7,8]. Regarding voltage regulation in transmission systems, several coordination strategies have been proposed so far, which can be classified into two groups: (1) coordinated control between DGs and reactive power compensation facilities, such as a flexible AC transmission system (FACTS) [9,10], and (2) supplementary control functions, which have been implemented for DGs to use the advanced reactive power-voltage control method [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Droop Control Strategy of Utility-Scale Photovoltaic Systems Using Adaptive Dead Band

2020

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This paper proposes a novel droop control strategy for addressing the voltage problem against disturbance in a transmission system connected with a utility-scale photovoltaic. Typically, a voltage control at the renewable energy sources (RESs) connected to the transmission grid uses a reactive power–voltage control scheme with a fixed dead band. However, this may cause some problems; thus, this paper proposes a method for setting a dead band value that varies with time. Here, a method for calculating an appropriate dead band that satisfies the voltage maintenance standard for two disturbances is described using voltage sensitivity analysis and the equation of existing droop control. Simulation studies are conducted using the PSS® E program to analyze the short term voltage stability and display the results for various dead bands. The proposed modeling and operational strategy are validated in simulation using a modified IEEE 39 bus system. The results provide useful information, indicating that the control scheme through an adaptive dead band enables more stable system operation than that through a fixed dead band.

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Voltage control with inverter-based distributed generation

Cited by 143 publications

References 2 publications

Design of the Smart Grid Architecture According to Fractal Principles and the Basics of Corresponding Market Structure

Design of the Smart Grid Architecture According to Fractal Principles and the Basics of Corresponding Market Structure

Cyber–Physical Active Distribution Networks Robustness Evaluation against Cross-Domain Cascading Failures

Droop Control Strategy of Utility-Scale Photovoltaic Systems Using Adaptive Dead Band

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