A Proximal Atomic Coordination Algorithm for Distributed Optimization

Romvary, Jordan; Ferro, Giulio; Haider, Rabab; Annaswamy, Anuradha M.

doi:10.1109/tac.2021.3053907

Cited by 18 publications

(6 citation statements)

References 45 publications

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“…The parameters of the PAC algorithm were tuned to guarantee algorithm convergence (see [11], [12] for details).…”

Section: Resultsmentioning

confidence: 99%

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Optimal Coordination of Distributed Energy Resources in Smart Grids Enabled by Distributed Optimization

Haider,

Annaswamy

2020

Preprint

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Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these small-scale and spatially distributed DERs can only be achieved at the nexus of new technological approaches and policies. As such, this paper presents a distributed optimal power flow formulation for the distribution grid, applied to the problem of Volt-VAR optimization (VVO). First, we propose a convex model to describe the power physics of distribution grids of meshed topology and unbalanced structure, based on current injection and McCormick Envelopes. Second, we employ the distributed proximal atomic coordination (PAC) algorithm, which has several advantages over other distributed algorithms, including reduced local computational effort and improved privacy. We implement VVO by optimally coordinating DERs including PV smart inverters and demand response. Results from the IEEE-34 bus network are presented, under different DER penetration scenarios and using different VVO objective functions. Our results show the need for DER coordination to achieve desired grid performance. Finally, we discuss the extension of such an optimal power flow formulation to the development of market derivatives to provide financial compensation to DERs providing grid services such as reactive power support and voltage support, within a local retail market framework.

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“…The parameters of the PAC algorithm were tuned to guarantee algorithm convergence (see [11], [12] for details).…”

Section: Resultsmentioning

confidence: 99%

“…In this section, we introduce the distributed algorithm of [11], [12], for the sake of completeness and comprehension. We first consider the following centralized optimization problem:…”

Section: Proximal Atomic Coordination Algorithmmentioning

confidence: 99%

Optimal Coordination of Distributed Energy Resources in Smart Grids Enabled by Distributed Optimization

Haider,

Annaswamy

2020

Preprint

Self Cite

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“…To reduce the amount of data interaction, Ref. [22] proposed a novel distributed convex optimization framework of proximal atomic coordination (PAC). It could achieve linear convergence when the objective function is convex, which showed great potential in computational efficiency.…”

Section: Distributed State Estimation In Digital Distribution Network...mentioning

confidence: 99%

Distributed State Estimation in Digital Distribution Networks Based on Proximal Atomic Coordination

Liu

Gao

et al. 2022

IEEE Trans. Instrum. Meas.

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“…These DERs include both behind-the-meter resources and those connected directly to the distribution grid, including DR, DGs, and storage. Each agent is equipped with the necessary computational and communication infrastructure to participate in the market, which is built upon a distributed optimization algorithm called PAC (for technical details see Haider et al (2020); Romvary et al (2020); Romvary (2018)). Using this algorithm, each agent self-schedules to minimize its expenses (equivalently maximize profit) while subjected to network constraints such as voltage limits, thermal line limits, and other DSO-level objectives, which are modeled through a non-linear convex optimal power flow formulation.…”

Section: Operation Of Real-time Energy Marketmentioning

confidence: 99%

“…These monetary incentives take the form of distribution-level Locational Marginal Prices (d-LMPs) to participants at the distribution primary feeders, similar to the notion of LMPs employed as pricing signals in the wholesale energy market by Independent System Operators (ISOs) at the transmission level (EIA, 2011). The d-LMPs are determined using a distributed optimization algorithm, termed Proximal Atomic Coordination (PAC) developed in (Romvary et al, 2020;Haider et al, 2020;Romvary, 2018), as a core component. All underlying grid physics and constraints in the distribution system are incorporated in deriving the d-LMPs.…”

Section: Introductionmentioning

confidence: 99%

Reinventing the Utility for DERs: A Proposal for a DSO-Centric Retail Electricity Market

Haider,

D'Achiardi,

Venkataramanan

et al. 2021

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The increasing penetration of intermittent renewables, storage devices, and flexible loads is introducing operational challenges in distribution grids. The proper coordination and scheduling of these resources using a distributed approach is warranted, and can only be achieved through local retail markets employing transactive energy schemes. To this end, we propose a distribution-level retail market operated by a Distribution System Operator (DSO), which schedules DERs and determines the real-time distribution-level Locational Marginal Price (d-LPM). The retail market is built using a distributed Proximal Atomic Coordination (PAC) algorithm, which solves the optimal power flow model while accounting for network physics, rendering locationally and temporally varying d-LMPs. A numerical study of the market structure is carried out via simulations of the IEEE-123 node network using data from ISO-NE and Eversource in Massachusetts, US. The market performance is compared to existing retail practices, including demand response (DR) with no-export rules and net metering. The DSO-centric market increases DER utilization, permits continual market participation for DR, lowers electricity rates for customers, and eliminates the subsidies inherent to net metering programs. The resulting lower revenue stream for the DSO highlights the evolving business model of the modern utility, moving from commoditized markets towards performance-based ratemaking.

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A Proximal Atomic Coordination Algorithm for Distributed Optimization

Cited by 18 publications

References 45 publications

Optimal Coordination of Distributed Energy Resources in Smart Grids Enabled by Distributed Optimization

Optimal Coordination of Distributed Energy Resources in Smart Grids Enabled by Distributed Optimization

Distributed State Estimation in Digital Distribution Networks Based on Proximal Atomic Coordination

Reinventing the Utility for DERs: A Proposal for a DSO-Centric Retail Electricity Market

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