Residential load and rooftop PV generation: an Australian distribution network dataset

Ratnam, Elizabeth L.; Weller, Steven R.; Kellett, Christopher M.; Murray, Alan T.

doi:10.1080/14786451.2015.1100196

Cited by 175 publications

(62 citation statements)

References 29 publications

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“…In this section, we examine the performance of the distributed dual ascent Algorithm 2 by simulating the algorithm using data obtained from the Australian electricity distribution company Ausgrid (Ratnam et al, 2015). Consistent with the Ausgrid data, we fix T = 0.5[h] and we use a prediction horizon of N = 48, which then corresponds to a prediction of one day.…”

Section: Numerical Simulationsmentioning

confidence: 99%

“…In ) we investigated several model predictive control (MPC) schemes for the control of a small scale electricity network and demonstrated the performance of these schemes using a dataset provided by the company Ausgrid (see (Ratnam, Weller, Kellett, & Murray, 2015) for an overview of the dataset). The control schemes in concentrated on reducing fluctuations of the aggregate power demand and on temporary operation of the electricity network in islanded mode (see (Braun, Faulwasser, et al, 2016)).…”

Section: Introductionmentioning

confidence: 99%

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Towards price-based predictive control of a small-scale electricity network

Braun

Grüne

Kellett

et al. 2017

International Journal of Control

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With the increasing deployment of battery storage devices in residential electricity networks, it is essential that the charging and discharging of these devices be scheduled so as to avoid adverse impacts on the electricity distribution network. In this paper, we propose a non-cooperative, price-based hierarchical distributed optimisation approach that provably recovers the centralised, or cooperative, optimal performance from the point of view of the network operator. The performance of this algorithm is validated on recent measurements taken from an Australian electricity distribution company, Ausgrid.

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Section: Numerical Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards price-based predictive control of a small-scale electricity network

Braun

Grüne

Kellett

et al. 2017

International Journal of Control

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“…Load and generation data, w, is taken from a dataset provided by the Australian electricity distribution network provider, Ausgrid. This dataset is described in detail in [20].…”

Section: B Decentralized Model Predictive Control (Dempc)mentioning

confidence: 99%

“…Then, based on real data from an Australian electricity distribution company, Ausgrid, a numerical case study is presented in order to show the benefit of DiMPC compared to CMPC and DeMPC. An overview of the load and generation data provided by Ausgrid can be found in [20].…”

Section: A Numerical Case Studymentioning

confidence: 99%

A Distributed Optimization Algorithm for the Predictive Control of Smart Grids

Braun

Grüne

Kellett

et al. 2016

IEEE Trans. Automat. Contr.

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Abstract-In this paper, we present a hierarchical, iterative distributed optimization algorithm, and show that the algorithm converges to the solution of a particular global optimization problem. The motivation for the distributed optimization problem is the predictive control of a smart grid, in which the states of charge of a network of residential-scale batteries are optimally coordinated so as to minimize variability in the aggregated power supplied to/from the grid by the residential network. The distributed algorithm developed in this paper calls for communication between a central entity and an optimizing agent associated with each battery, but does not require communication between agents. The distributed algorithm is shown to achieve the performance of a large-scale centralized optimization algorithm, but with greatly reduced communication overhead and computational burden. A numerical case study using data from an Australian electricity distribution network is presented to demonstrate the performance of the distributed optimization algorithm.

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“…The study of integrated PV-BESs along with two proposals of new FIT schemes in Australia is presented in [43,44]; Ratnam et al and Weller et al proposed an optimization-based approach to scheduling residential battery storage with solar PV. The aim is to maximize the electricity generation in order to achieve financial benefits for residential customers and simultaneously alleviate the utility burden associated with peak demand and reverse power flow.…”

Section: The Case Of Australiamentioning

confidence: 99%

Recent Developments of Photovoltaics Integrated with Battery Storage Systems and Related Feed-In Tariff Policies: A Review

Bayod-Rújula

Burgio

Leonowicz

et al. 2017

International Journal of Photoenergy

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The paper presents a review of the recent developments of photovoltaics integrated with battery storage systems (PV-BESs) and related to feed-in tariff policies. The integrated photovoltaic battery systems are separately discussed in the regulatory context of Germany, Italy, Spain, United Kingdom, Australia, and Greece; the attention of this paper is focused on those integrated systems subject to incentivisation policies such as feed-in tariff. Most of the contributions reported in this paper consider already existing incentive schemes; the remaining part of the contributions proposes interesting and novel feed-in tariff schemes. All the contributions provide an important resource for carrying out further research on a new era of incentive policies in order to promote storage technologies and integrated photovoltaic battery systems in smart grids and smart cities. Recent incentive policies adopted in Germany, Italy, Spain, and Australia are also discussed.

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Residential load and rooftop PV generation: an Australian distribution network dataset

Cited by 175 publications

References 29 publications

Towards price-based predictive control of a small-scale electricity network

Towards price-based predictive control of a small-scale electricity network

A Distributed Optimization Algorithm for the Predictive Control of Smart Grids

Recent Developments of Photovoltaics Integrated with Battery Storage Systems and Related Feed-In Tariff Policies: A Review

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