Distribution System Parameter and Topology Estimation Applied to Resolve Low-Voltage Circuits on Three Real Distribution Feeders

Lave, Matthew; Reno, Matthew J.; Peppanen, Jouni

doi:10.1109/tste.2019.2917679

Cited by 48 publications

(25 citation statements)

References 16 publications

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“…Various techniques for accurate estimation of distribution line parameters have been reported in the literature. [55][56][57] The error reported is limited to 3% 6%. [55][56][57] Let us assume that there is 10% inaccuracy in estimation/measurement of feeder #2 resistance.…”

Section: Impact Of the Error In The Assessment Of Feeder Resistancementioning

confidence: 88%

An accurate current sharing method for an Islandeddroop‐controlled dcmicrogrid without communication between remote buses

Maulik

Das

2020

Int Trans Electr Energ Syst

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Summary The traditional droop control method in a DC microgrid (DCMG) fails to achieve accurate current sharing among parallel‐connected dispatchable units when the connecting feeders have unequal resistances, or when the units supply local loads apart from loads at the common dc bus. In this paper, a novel modification of the droop control strategy (additional feedback term in the outer control loop) is suggested to overcome the above limitations. The proposed method is robust, noise‐resilient, amenable to the “plug and play model”, and employs local measurements, thereby, dispensing with the need for communication between remote nodes. A small‐signal model of the system with the proposed control strategy is derived for carrying out eigenvalue and participation factor analysis. A sensitivity analysis is also carried out to inspect the impact of variation of system parameters on small‐signal stability. The effect of time delay and noise on system small‐signal stability is also studied. A robust stability analysis is also carried out. The proposed control strategy is easily implementable on digital hardware. Time domain simulations using PSCAD (Power System Computer Aided Design)/EMTDC(Electromagnetic Transients including DC) is carried out to validate and compare the performance of the proposed technique vis‐a‐vis other existing methods. Performance of the proposed method is good even with time delay and noise.

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Section: Impact Of the Error In The Assessment Of Feeder Resistancementioning

confidence: 88%

An accurate current sharing method for an Islandeddroop‐controlled dcmicrogrid without communication between remote buses

Maulik

Das

2020

Int Trans Electr Energ Syst

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“…Smart meters are being rolling out by power utilities in customer premises in order to capture energy demand and other electrical parameters at regular intervals (e.g., 5 and 15 min intervals). Such data are currently being used by some power utilities to build data-based models to observe feeder voltages and energy consumption in real-time (Lave et al, 2019). These data-driven models, which have already been adopted by the system operator in Australia to dynamically size operating reserves (Fahiman et al, 2019), can, and will, be integrated into DRS and VPP portfolios, with the potential to effectively provide frequency support services to improve system stability.…”

Section: Other Emerging Techniquesmentioning

confidence: 99%

Power system stability in the transition to a low carbon grid: A techno‐economic perspective on challenges and opportunities

Meegahapola

Mancarella

Flynn

et al. 2021

WIREs Energy & Environment

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Increasing power system stability challenges are being witnessed worldwide, while transitioning toward low‐carbon grids with a high‐share of power electronic converter (PEC)‐interfaced renewable energy sources (RESs) and distributed energy resources (DERs). Concurrently, new technologies and operational strategies are being implemented or proposed to tackle these challenges. Since electricity grids are deregulated in many jurisdictions, such technologies need to be integrated within a market framework, which is often a challenge in itself due to inevitable regulatory delays in updating grid codes and market rules. It is also highly desirable to ensure that an economically feasible optimal technology mix is integrated in the power system, without imposing additional burdens on electricity consumers. This article provides a comprehensive overview of emerging power system stability challenges posed by PEC‐interfaced RES and DER, particularly related to low inertia and low system strength conditions, while also introducing new technologies that can help tackle these challenges and discussing the need for suitable techno‐economic considerations to integrate them into system and market operation. As a key point, the importance of recognizing the complexity of system services to guarantee stability in low‐carbon grids is emphasized, along with the need to carefully integrate new grid codes and market mechanisms in order to exploit the full benefits of emerging technologies in the transition toward ultra‐low carbon futures. This article is categorized under: Energy Systems Economics > Economics and Policy Energy Systems Analysis > Systems and Infrastructure Energy and Development > Systems and Infrastructure

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“…Compared with other main networks, the PDN covers a larger area, and its measurement conditions are unsatisfactory. erefore, the parameter identification methods used in the PTN may not be suitable for the PDN. In the field of PDN, with the wide application of supervisory control and data acquisition, power management unit (PMU), and advanced metering infrastructure (AMI), some new approaches focusing on efficiency and error have been developed, such as the full-scale approach [5], PSOSR [6], normalized Lagrange multiplier (NLM) test [7], finite-time algorithm (FTA) [8], residual method, sensitivity analysis method, Lagrange multiplier method [9], and Heffron-Phillips method [10]. With the development of machine learning, some new approaches have been proposed, such as a method that considers distance space [11], particle swarm optimization (PSO) algorithm [12], interior point method [13], ensemble Kalman filtering [14], evolutionary strategies [15], estimation using synchrophasor data [16], PSCAD simulation [17], and deep learning [18].…”

Section: Introductionmentioning

confidence: 99%

A Method for Parameter Identification of Distribution Network Equipment Based on Sequential Model-Based Optimization

et al. 2022

International Transactions on Electrical Energy Systems

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We present the first model-based parameter identification method in the power distribution network to successfully achieve parameter identification directly based on sequential model-based optimization. This method is building a model with a posteriori probability to optimize an objective function. Furthermore, to achieve an efficient exploration, three different acquisition functions, i.e., random search, tree-structured Parzen estimator approach, and simulated annealing, were proposed. We applied our three models and the conventional model-free method to the actual feeder data with no adjustment of the other conditions. The experiment shows that our method achieves at least 25% and 70% improvements in accuracy and convergence speed, respectively.

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Distribution System Parameter and Topology Estimation Applied to Resolve Low-Voltage Circuits on Three Real Distribution Feeders

Cited by 48 publications

References 16 publications

An accurate current sharing method for an Islandeddroop‐controlled dcmicrogrid without communication between remote buses

An accurate current sharing method for an Islandeddroop‐controlled dcmicrogrid without communication between remote buses

Power system stability in the transition to a low carbon grid: A techno‐economic perspective on challenges and opportunities

A Method for Parameter Identification of Distribution Network Equipment Based on Sequential Model-Based Optimization

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