Load Aggregation Methods for Quasi-Static Power Flow Analysis on High PV Penetration Feeders

Wang, J.; Zhu, Xiangqi; Lubkeman, David; Liu, Ning; Samaan, Nader; Werts, Brant

doi:10.1109/tdc.2018.8440485

Cited by 10 publications

(6 citation statements)

References 4 publications

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“…The PECAN STREET project residential load data set from Jan 1 to June 30, 2017, is used in this research work [37]. Based on the results of the load profile aggregation (LPA) algorithm proposed in [38] for the IEEE 123-bus test feeder, there are average 8 houses on each bus with 3.5 kW peak load/house. The capacity of the rooftop PV installed at each house on branch nodes is 6 kW.…”

Section: B Ieee 123-bus Test Networkmentioning

confidence: 99%

Consensus-Based ADMM for Distributed Optimization in Power Systems using Private Blockchain Network

Shah¹,

Wies²,

King³

2021

Preprint

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The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, which limits the size of the problem that can be solved, and also creates a high communication overhead since all the data is transferred to the central controller. These limitations are addressed by a proposed consensus-ADMM (alternating direction method of multiplier) based distributed optimization algorithm, which decomposes the optimization problem into sub-problems. The distribution feeder is partitioned into low coupling sub-networks/regions, which solves the sub-problem locally and exchanges information with the neighboring regions to reach consensus to solve for the global update. The information exchange and synchronization between sub-networks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a virtual aggregator for synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for 0.5-MW laboratory microgrid for one hour ahead and day-ahead for IEEE 123-bus and EPRI J1 test feeder, and results are compared with a centralized solution.

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Section: B Ieee 123-bus Test Networkmentioning

confidence: 99%

Consensus-Based ADMM for Distributed Optimization in Power Systems using Private Blockchain Network

Shah¹,

Wies²,

King³

2021

Preprint

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“…To better model load diversity in the distribution feeders, a feeder load disaggregation algorithm is used to disaggregate the feeder head load profile to each load node using smart meter data provided by Duke Energy. Details for the disaggregation method were introduced in [8].…”

Section: A Transmission and Distribution Systems Modelingmentioning

confidence: 99%

Networked HIL Simulation System for Modeling Large-scale Power Systems

Xie

McEntee

Zhang

et al. 2021

2020 52nd North American Power Symposium (NAPS)

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This paper presents a network hardware-in-theloop (HIL) simulation system for modeling large-scale power systems. Researchers have developed many HIL test systems for power systems in recent years. Those test systems can model both microsecond-level dynamic responses of power electronic systems and millisecond-level transients of transmission and distribution grids. By integrating individual HIL test systems into a network of HIL test systems, we can create large-scale power grid digital twins with flexible structures at required modeling resolution that fits for a wide range of system operating conditions. This will not only significantly reduce the need for field tests when developing new technologies but also greatly shorten the model development cycle. In this paper, we present a networked OPAL-RT based HIL test system for developing transmission-distribution coordinative Volt-VAR regulation technologies as an example to illustrate system setups, communication requirements among different HIL simulation systems, and system connection mechanisms. Impacts of communication delays, information exchange cycles, and computing delays are illustrated. Simulation results show that the performance of a networked HIL test system is satisfactory.

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“…The error is modeled as Gaussian variance and added to the measurements. The other detailed parameters of the network are from references [26,27].…”

Section: Case Studymentioning

confidence: 99%

“…The error is modeled as Gaussian variance and added to the measurements. The other detailed parameters of the network are from references [26,27]. The installed capacities of DG-1 to DG-7 are 0.5, 1.3, 0.68, 0.48, 1.42, 0.71, 1.08 MW, respectively.…”

Section: Online Dynamic Characteristics Assessment In a Single Time Windowmentioning

confidence: 99%

Real-Time Dynamic Behavior Evaluation of Active Distribution Networks Leveraging Low-Cost PMUs

Zheng

Wang

et al. 2021

Energies

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The investigation of real-time dynamic behavior evaluation in the active distribution networks (ADNs) is a challenging task, and it has great importance due to the emerging trend of distributed generations, electric vehicles, and flexible loads integration. The advent of new elements influences the dynamic behavior of the electric distribution networks and increases the assessment complexity. However, the proper implementation of low-cost phasor measurement units (PMUs) together with the development of power system applications offer tremendous benefits. Therefore, this paper proposes a PMU-based multi-dimensional dynamic index approach for real-time dynamic behavior evaluation of ADNs. The proposed evaluation model follows the assessment principles of accuracy, integrity, practicability, and adaptability. Additionally, we introduced low-cost PMUs in the assessment model and implemented them for real-time and high-precision monitoring of dynamic behaviors in the entire distribution network. Finally, a complete model called the real-time dynamic characteristics evaluation system is presented and applied to the ADN. It is pertinent to mention that our proposed evaluation methodology does not rely on the network topology or line parameters of the distribution network since only the phasor measurements of node voltage and line current are involved in the dynamic index system. Thus, the presented methodology is well adaptive to different operation states of ADN despite frequent topology changes. The validation of the proposed approach was verified by conducting simulations on the modified IEEE 123-node distribution network. The obtained results verify the effectiveness and relevance of the proposed model for the real-time dynamic behavior evaluation of ADNs.

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Load Aggregation Methods for Quasi-Static Power Flow Analysis on High PV Penetration Feeders

Cited by 10 publications

References 4 publications

Consensus-Based ADMM for Distributed Optimization in Power Systems using Private Blockchain Network

Consensus-Based ADMM for Distributed Optimization in Power Systems using Private Blockchain Network

Networked HIL Simulation System for Modeling Large-scale Power Systems

Real-Time Dynamic Behavior Evaluation of Active Distribution Networks Leveraging Low-Cost PMUs

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