Network-Aware Coordination of Residential Distributed Energy Resources

Scott, Paul; Gordon, Dan; Franklin, Evan; Jones, Laura; Thiébaux, Sylvie

doi:10.1109/tsg.2019.2907128

Cited by 79 publications

(42 citation statements)

References 24 publications

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“…The results indicate that uncoordinated PV-battery systems have limited beneficial impact on LV networks, which goes against the conjecture that battery scheduling will serendipitously mitigate the technical problems induced by high PV penetration. Perhaps surprisingly, the inclusion of ToU tariffs in the HEM problem only marginally affects the peak demand compared to SCM, which goes to show that at very high penetration levels, DER scheduling needs to be coordinated by a distribution system operator, using a distribution power flow [34][35][36] or peer-to-peer trading with network constraint envelopes [37].…”

Section: Discussionmentioning

confidence: 99%

A novel probabilistic framework to study the impact of photovoltaic-battery systems on low-voltage distribution networks

Azuatalam

Power

et al. 2019

Applied Energy

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Section: Discussionmentioning

confidence: 99%

A novel probabilistic framework to study the impact of photovoltaic-battery systems on low-voltage distribution networks

Azuatalam

Power

et al. 2019

Applied Energy

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“…The self-su ciency algorithm is but one of any number of potential non-nancial algorithms. Some technical objectives, such as voltage or frequency management, are well studied in the literature 37,38 , while there are many more, such as prioritising transparency, that are deserving of future research. We note that while algorithms may allow multiple objectives to be combined and co-optimised (we have not done so in the interest of clarity), such co-optimisation still requires design choices on how each objective is prioritised and traded-off relative to others.…”

Section: Non-nancial Objectivesmentioning

confidence: 99%

An interdisciplinary exploration of responsible algorithm design in the era of distributed energy resources

Ransan-Cooper¹,

Sturmberg

Shaw

et al. 2021

Preprint

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While the governance of algorithms is of growing societal concern, the energy sector has been slow to engage with this issue. We argue that there are at least three systemic concerns to the design and operation of algorithms in the new, digital energy era. Namely, reliance on algorithms can bias considerations towards the easily quantifiable, that they can inhibit explainability, transparency and trust, and that they could undermine energy users’ autonomy and control. We examine these tensions through an interdisciplinary study that reveals the diversity and materiality of algorithms. Our study focuses on neighbourhood-scale batteries (NSBs) in Australia as a case study of new energy algorithms. We conducted qualitative research with energy sector professionals and citizens to understand the range of perceived benefits and risks of NSBs and the algorithms that drive their behaviour. Issues raised by stakeholders were integrated into our development of multiple NSB optimisation algorithms, whose impacts on NSB owners and customers we quantified through techno-economic modelling. Our results show the allocation of benefits and risks vary considerably between different algorithm designs. This insight a need to improve energy algorithm governance, enabling accountability and responsiveness across the design and use of algorithms so that the digitisation of energy technology does not lead to adverse public outcomes. Taken together, our study underscores the importance for researchers and developers of new algorithms to take a holistic view of stakeholders and public benefit, and demonstrates one method to practice responsible algorithm design.

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“…The ADMM algorithm in [17], [18] solves the OPF problem, exchanging voltage information between the neighboring regions; however, DERs and BESS are not integrated into the test network. A fullscale distributed OPF is implemented using ADMM in [4], [19]- [23] in which participating nodes/controllers exchange information with the system or virtual aggregator to solve for the global update. The OPF problem with nonconvex feasible sets in [24]- [28] is solved using a decentralized algorithm in which a specific node communicates only with its adjacent nodes with no central or virtual aggregator.…”

Section: Introductionmentioning

confidence: 99%

Distributed ADMM Using Private Blockchain for Power Flow Optimization in Distribution Network With Coupled and Mixed-Integer Constraints

2021

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The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with the 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, limiting the size of the problem that can be solved and creating a high communication overhead because all the data is transferred to the central controller. These limitations are addressed by the proposed distributed consensus-based alternating direction method of multiplier (DC-ADMM) optimization algorithm, which decomposes the optimization problem into subproblems with private cost function and constraints. The distribution feeder is partitioned into low coupling subnetworks/regions, which solves the private subproblem locally and exchanges information with the neighboring regions to reach consensus. The relaxation strategy is employed for mixed-integer and coupled constraints introduced in the optimal power flow (OPF) problem by stationary and transportable BESS because DC-ADMM convergence is only guaranteed for strict convex problems. The information exchange and synchronization between subnetworks/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 mediator for secure data exchange and synchronization in distributed computation. The blockchain-based distributed optimization problem's effectiveness is tested for a 0.5-MW laboratory microgrid for one hour ahead and day-ahead for the IEEE 123-bus and EPRI J1 test feeders, and results are compared with a centralized solution. INDEX TERMS Alternating direction method of multiplier, Battery energy storage systems, Blockchain, Distributed optimization, Optimal power flow, Microgrid.

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Network-Aware Coordination of Residential Distributed Energy Resources

Cited by 79 publications

References 24 publications

A novel probabilistic framework to study the impact of photovoltaic-battery systems on low-voltage distribution networks

A novel probabilistic framework to study the impact of photovoltaic-battery systems on low-voltage distribution networks

An interdisciplinary exploration of responsible algorithm design in the era of distributed energy resources

Distributed ADMM Using Private Blockchain for Power Flow Optimization in Distribution Network With Coupled and Mixed-Integer Constraints

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