124 research outputs found

    Optimal Power Flow for Integrated Primary-Secondary Distribution Networks with Service Transformers

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    Secondary distribution networks (SDNets) play an increasingly important role in smart grids due to a high proliferation of distributed energy resources (DERs) in SDNets. However, most existing optimal power flow (OPF) problems do not take into account SDNets with service transformers. Handling the nonlinear and nonconvex SDNet power flow constraints is still an outstanding problem. To meet this gap, we first utilize the second-order cone programming relaxation and linearization to make service transformer constraints convex, respectively. Then, the linearized triplex service line power flow model, including its compact matrix-vector form, is further developed to compose the SDNet OPF model with our proposed service transformer model. This proposed SDNet OPF model can be easily embedded into existing primary distribution network (PDNet) OPF models, resulting in a holistic power system decision-making solution for integrated primary-secondary distribution networks. A case study is presented for an integrated primary-secondary distribution network that demonstrates the practical effectiveness of this model

    Automatic Self-Adaptive Local Voltage Control Under Limited Reactive Power

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    The increasing proliferation of distributed energy resources has posed new challenges to Volt/VAr control problems in distribution networks. To this end, this paper proposes an automatic self-adaptive local voltage control (ASALVC) by locally controlling VAr outputs of distributed energy resources. In this ASALVC strategy, each bus agent can locally and dynamically adjust its voltage droop function in accordance with time-varying system changes. The voltage droop function is associated with the bus-specific time-varying slope and intercept, which can be locally updated, merely based on local voltage measurements, without requiring communication. Stability, convergence, and optimality properties of this local voltage control are analytically established. In addition, the online implementation of ASALVC is further proposed to address the real-time system changes by adjusting VAr outputs of DERs online. Numerical test cases are performed to validate and demonstrate the effectiveness and superiority of ASALVC

    Clusters and coherent voids in particle-laden wake flow

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    Inertial point particles suspended in a two-dimensional unsteady circular cylinder flow at Re = 100 are studied by one-way coupled three-dimensional numerical simulations. The striking clustering pattern in the near-wake is strongly correlated with the periodically shed Kármán vortex cells. The particles are expelled from the vortex cores due to the centrifugal mechanism and coherent voids encompassing the local Kármán cells are therefore observed. The particle clustering at the upstream side of each void hole form a smooth edge, where the particle velocity magnitude is consistently lower than at the downstream edge of the voids. The trajectories of these particles originate from the side of the cylinder where the sign of vorticity is opposite to that of the vortex encompassed by the corresponding void hole. The particles are seen to decelerate along a substantial part of their trajectories. Particle inertia is parameterized by means of a Stokes number Sk and smooth edges around the void holes still exist when Sk is increased, although their formation is delayed due to larger inertia. Increasing inertia contributes to a decoupling of the particle acceleration from the slip velocity, which almost coincided at Sk = 1publishedVersio

    Different topologies of natural vortex dislocations in Mode A wake

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    This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Cai Tian (田偲), Zhaoyu Shi (史召宇), Fengjian Jiang (蒋奉兼), and Helge I. Andersson , "Different topologies of natural vortex dislocations in Mode A wake", Physics of Fluids 34, 021702 (2022) and may be found at https://doi.org/10.1063/5.0081136The mode A wake behind a circular cylinder at Reynolds number 200 was simulated by directly solving the three-dimensional Navier–Stokes equations. A more detailed investigation of different topologies of natural vortex dislocations in the mode A wake was systematically described. In addition to the two-side natural vortex dislocation defined by Williamson [J. Fluid Mech. 243, 393–441 (1992)], three new topologies of vortex dislocations were identified. Additionally, the formation process and the mechanism of these newly identified dislocation topologies were addressed. The results in this Letter provide a more thorough understanding of the natural vortex dislocations in the mode A wake.acceptedVersio

    A Statistical Approach to Estimate Imbalance-Induced Energy Losses for Data-Scarce Low Voltage Networks

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    Phase imbalance in the U.K. and European low-voltage (415 V, LV) distribution networks causes additional energy losses. A key barrier against understanding the imbalance-induced energy losses is the absence of high-resolution time-series data for LV networks. It remains a challenge to estimate imbalance-induced energy losses in LV networks that only have the yearly average currents of the three phases. To address this insufficient data challenge, this paper proposes a new customized statistical approach, named as the clustering, classification, and range estimation (CCRE) approach. It finds a match between the network with only the yearly average phase currents (the data-scarce network) and a cluster of networks with time series of phase current data (data-rich networks). Then, CCRE performs a range estimation of the imbalance-induced energy loss for the cluster of data-rich networks that resemble the data-scarce network. Chebyshev's inequality is applied to narrow down this range, which represents the confidence interval of the imbalance-induced energy loss for the data-scarce network. Case studies reveal that, given such a few data from the data-scarce networks, more than 80% of these networks are classified to the correct clusters and the confidence of the imbalance-induced energy loss estimation is 89%.</p

    Design of Pulse Forming Networks Triggered by High-Power Hydrogen Thyratron

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    Hydrogen thyratron is a switching device invented based on the phenomenon of gas discharge, and it is widely used in the field of high-power pulse technology. The design of Pulse Forming Network (PFN) triggered by hydrogen thyratron aims to control the switch of subsequent circuit, and shorten the gate-cathode voltage and conduction delay time by increasing the rise rate of the trigger voltage. However, in the currently adopted series resonance network design schemes, usually the value of inductance is very large, which can easily lead to the decline in the electromagnetic compatibility performance; moreover, the large distribution of network component parameters will greatly increase the fabrication difficulties. In view of the features of high-power hydrogen thyratron and the design requirements of PFN, this paper adopted the series resonance network design scheme to devise network series and parameters of the PFN and analyze the shortcomings of the series resonance network design scheme; then, it used the anti-resonance network to design a three-stage transform algorithm model, so as to achieve the purpose of reducing the inductance of the PFN and the difficulty of capacitance model selection in engineering practice. At last, simulation results verified the correctness and feasibility of the designed three-stage transform algorithm model, providing evidences for the pulse network projects of hydrogen thyratron and other high-power equipment in terms of implementation paths, methods, and algorithm models

    A Statistical Approach to Estimate Imbalance-Induced Energy Losses for Data-Scarce Low Voltage Networks

    Get PDF
    Phase imbalance in the U.K. and European low-voltage (415 V, LV) distribution networks causes additional energy losses. A key barrier against understanding the imbalance-induced energy losses is the absence of high-resolution time-series data for LV networks. It remains a challenge to estimate imbalance-induced energy losses in LV networks that only have the yearly average currents of the three phases. To address this insufficient data challenge, this paper proposes a new customized statistical approach, named as the clustering, classification, and range estimation (CCRE) approach. It finds a match between the network with only the yearly average phase currents (the data-scarce network) and a cluster of networks with time series of phase current data (data-rich networks). Then, CCRE performs a range estimation of the imbalance-induced energy loss for the cluster of data-rich networks that resemble the data-scarce network. Chebyshev's inequality is applied to narrow down this range, which represents the confidence interval of the imbalance-induced energy loss for the data-scarce network. Case studies reveal that, given such a few data from the data-scarce networks, more than 80% of these networks are classified to the correct clusters and the confidence of the imbalance-induced energy loss estimation is 89%.</p

    Determination and prediction of the digestible and metabolizable energy contents of corn germ meal in growing pigs

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    Objective This experiment was conducted to determine the chemical composition, digestible energy (DE) and metabolizable energy (ME) contents of corn germ meals (CGM) and to develop equations to predict the corresponding energy contents based on the chemical characteristics of individual CGM. Methods Sixty-six barrows (initial body weight = 51.3±4.6 kg) were allotted to 11 diets including a basal diet and 10 CGM test diets in a completely randomized design. In the test diets, CGM was included in replacement of 30% of the energy-providing ingredients in the basal diet, resulting in a final inclusion rate of 29.1%. Each diet was fed to 6 barrows housed in individual metabolism crates for a 7-d acclimation period followed by a 5-d total but separate collection of feces and urine. Results Considerable variation was observed in acid-hydrolyzed ether extract, ether extract, ash, calcium (Ca) and total phosphorus contents among the CGM samples. On dry matter (DM) basis, the DE and ME contents of the CGM ranged from 10.22 to 15.83 MJ/kg and from 9.94 to 15.43 MJ/kg, respectively. The acid detergent fiber (ADF) contents were negatively correlated with the DE and ME contents of CGM samples. The best-fit prediction equations for the DE and ME values (MJ/kg DM) of the 10 CGM were: DE = 26.85–0.28 insoluble dietary fiber (%)–17.79 Ca (%); ME = 21.05–0.43 ADF (%)–11.40 Ca (%). Conclusion The chemical compositions of CGM vary depending on sources, particularly in ether extract and Ca. The DE and ME values of CGM can be predicted based on their chemical composition in growing pigs
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