Building scale DC microgrids

Marnay, Chris; Lanzisera, Steven; Städler, Michael; Lai, Jihn‐Sung

doi:10.1109/energytech.2012.6304685

Cited by 9 publications

(3 citation statements)

References 5 publications

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“…From the discussion in Section III-B, the steady state bus voltage v n depends on θ, see eq. ( 4), (6). This suggests that an arbitrary controller can infer the parameter vector θ locally, using local measurements of the steady state bus voltage (see also [40] and references therein for similar approaches).…”

Section: A Parameter Vectormentioning

confidence: 99%

Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations

Angjelichinoski

Scaglione

Popovski

et al. 2018

IEEE Trans. Signal Process.

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We treat the emerging power systems with direct current (DC) MicroGrids, characterized with high penetration of power electronic converters. We rely on the power electronics to propose a decentralized solution for autonomous learning of and adaptation to the operating conditions of the DC Mirogrids; the goal is to eliminate the need to rely on an external communication system for such purpose. The solution works within the primary droop control loops and uses only local bus voltage measurements. Each controller is able to estimate (i) the generation capacities of power sources, (ii) the load demands, and (iii) the conductances of the distribution lines. To define a well-conditioned estimation problem, we employ decentralized strategy where the primary droop controllers temporarily switch between operating points in a coordinated manner, following amplitude-modulated training sequences. We study the use of the estimator in a decentralized solution of the Optimal Economic Dispatch problem. The evaluations confirm the usefulness of the proposed solution for autonomous MicroGrid operation.The proposed solution is illustrated in Fig. 1. We consider a generic DC MG model with multiple buses, described in Sections III and IV. We assume that the MG does not have access to reliable external communication resources. The physical state of DC MGs is characterized by the steady state bus voltages. We introduce a parameter vector θ that collects all system variables whose values are determined by exogenous influences; this includes the generation capacities of the DERs, the load demands and the distribution network topology, i.e., the conductance matrix, see Section IV-A. Using the power balance equation, we represent the bus voltages thorough a non-linear and implicit model, parametrized by θ, see Section III-B. Evidently, θ varies with time; to respond to its variations on different time scales, the DC MG is governed by a hierarchical control system, comprising primary and upper control layer. The primary control is decentralized: several controllers regulate the bus voltages, using only local feedbacks without exchanging any information with peer controllers. They are very fast and capable of responding to high frequency variations in θ. Popular primary controller in DC MGs is the Voltage Source Converter (VSC) with voltage droop control, which is reminiscent to the widespread frequency droop control in AC systems, but defined over the DC voltage; it is therefore standard practice to refer to it simply as droop controller [2], [3]. The upper control layer, on the other hand, responds to less frequent changes in θ that affect the global behavior of the system; examples include changes of the load/generation profile, faults, attacks, etc. Its main role is to adapt the system to the new conditions by computing updated optimal control references for the primary controllers; all upper layer control applications require full/partial knowledge of θ to determine the control references that adequately reflect the new conditions [15]...

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Section: A Parameter Vectormentioning

confidence: 99%

Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations

Angjelichinoski

Scaglione

Popovski

et al. 2018

IEEE Trans. Signal Process.

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“…There have been several studies related to the DC systems; device and control [1][2][3][4][5][6][7][8][9], management [10][11][12], cable and power conversion [13][14][15][16], DC distribution test-bed [17,18], and optimal DG sizing [19][20][21][22][23]. Although the optimal operation method [24] makes the multiple DGs properly share the loads as well as instantly respond to the load variations, the DGs must control their output voltages very accurately to do this.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Droop Based Virtual Slack Control of Multiple DGs in Practical DC Distribution System to Improve Voltage Profile

Lee

2019

Energies

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This paper proposes an adaptive droop based virtual slack (ADVS) control for multiple distributed generations (DGs) to improve voltage stability of a practical DC distribution system. Although there have been many researches for optimal sizes of multiple DGs, their solutions are valid only in the particular operating point. Additionally, a previous study proposed a voltage control based optimal operation method, its performance depends on measurement accuracy in practice. The proposed ADVS control operates the system based on the current sensitivities between the DGs and loads, so that it can regulate the system voltages without a large computational effort. This is effective even if measurements are noisy and biased. All DGs contribute to voltage regulation by current control even though they do not directly control voltages. As an additional effect, they effectively share the load. To verify the proposed method, the DC system is modeled based on the real distribution system of the Do-gok area in Seoul, Korea. Then, the Levenberg-Marquardt algorithm determines its operation point. The proposed method is verified based on the electromagnetic transient (EMT) simulation with random loads.

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“…These very low costs place electricity metering and reporting in the reach of very cheap devices such as compact fluorescent or light-emitting diode (LED) light bulbs and battery chargers. Appliances that primarily use power through motors or resistive heating are not candidates for this technology nowadays, but these devices will likely move to variable speed drive and variable speed heat pump-based systems in the future [4]. Variable speed systems use the same sort of switching power supply making these more advanced and efficient systems candidates for the proposed technology.…”

Section: Introductionmentioning

confidence: 99%

Communicating Power Supplies: Bringing the Internet to the Ubiquitous Energy Gateways of Electronic Devices

Lanzisera

Weber

Liao

et al. 2014

IEEE Internet Things J.

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Saving energy in buildings is often hampered by the lack of detailed information about what is using the energy, how much it is using, and how to automatically and remotely control devices. The problem is especially acute for the large number of small, energy-using devices that are present in both residential and commercial buildings. Most of these products use a switching ac to dc power supply to operate electronic and other internal components. We describe a "communicating power supply" (CPS) to enable the communication of energy and control information between the device and a building management system or other central entities. We developed a proof-of-concept system of Internetconnected CPSs and demonstrated both energy reporting and control utilizing a custom, cloud-based information clearing house. If CPS technology became widespread in devices, a combination of automated and human interactive solutions would enable high levels of energy savings.

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Building scale DC microgrids

Cited by 9 publications

References 5 publications

Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations

Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations

Adaptive Droop Based Virtual Slack Control of Multiple DGs in Practical DC Distribution System to Improve Voltage Profile

Communicating Power Supplies: Bringing the Internet to the Ubiquitous Energy Gateways of Electronic Devices

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