An Incentive-Based Online Optimization Framework for Distribution Grids

Zhou, Xinyang; Dall’Anese, Emiliano; Chen, Lijun; Simonetto, Andrea

doi:10.1109/tac.2017.2760284

Cited by 93 publications

(100 citation statements)

References 40 publications

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“…[2] RC k P K calculates and sends ř iPN k`µ i pt`1q´µ i pt`1q˘to CC; unclustered node i P N 0 sends pµ i pt`1q´µ i pt`1qq to CC. [3] CC computes within the reduced network…”

Section: A Distribution Feeder As Networked Autonomous Gridsmentioning

confidence: 99%

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

Zhou

Liu

Wang

et al. 2019

2019 American Control Conference (ACC)

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We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primaldual gradient algorithm that solves the OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve an improvement of more than tenfold in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

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“…[2] RC k P K calculates and sends ř iPN k`µ i pt`1q´µ i pt`1q˘to CC; unclustered node i P N 0 sends pµ i pt`1q´µ i pt`1qq to CC. [3] CC computes within the reduced network…”

Section: A Distribution Feeder As Networked Autonomous Gridsmentioning

confidence: 99%

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

Zhou

Liu

Wang

et al. 2019

2019 American Control Conference (ACC)

Self Cite

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show abstract

“…Furthermore, the discrepancy due to the regularization term can be bounded and is proportional to η. We refer the details to [7], [33]. For the rest of this section, we will focus on solving the saddle point of the regularized Lagrangian (7).…”

Section: B Opf and Primal-dual Gradient Algorithmmentioning

confidence: 99%

Accelerated Voltage Regulation in Multi-Phase Distribution Networks Based on Hierarchical Distributed Algorithm

Zhou

Liu

Zhao

et al. 2020

IEEE Trans. Power Syst.

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We propose a hierarchical distributed algorithm to solve optimal power flow (OPF) problems that aim at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large multi-phase distribution networks by jointly exploring the tree/subtrees structure of a large radial distribution network and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves OPF. The proposed implementation significantly reduces the computation loads compared to the centrally coordinated implementation of the same primal-dual algorithm without compromising optimality. Numerical results on a 4,521node test feeder show that the designed algorithm achieves more than 10-fold acceleration in the speed of convergence compared to the centrally coordinated primal-dual algorithm through reducing and distributing computational loads.

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“…Several different market-based coordination mechanisms have been proposed in the literature [2], [3], [23]. For analysis purposes, we primarily focus on the mechanism proposed in [2] (also given in Section II of [3]) and suggest generalizations in later sections.…”

Section: B Market Clearing Mechanismmentioning

confidence: 99%

“…6(b) and 6(c). By (22), (23), B on and B off will then act on X on k and X off k , respectively, to give X k+1 .…”

Section: Reformulation Of the Transition Equationsmentioning

confidence: 99%

A Dynamical Systems Approach to Modeling and Analysis of Transactive Energy Coordination

Nazir

Hiskens

2019

IEEE Trans. Power Syst.

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Under transactive (market-based) coordination, a population of distributed energy resources (DERs), such as thermostatically controlled loads (TCLs) and storage devices, bid into an energy market. Consequently, a certain level of demand will be cleared based on the operating conditions of the grid. This paper analyzes the influence of various factors, such as price signals, feeder limits, and user-defined bid functions and preferences, on the aggregate energy usage of DERs. We identify cases that can lead to load synchronization, undesirable power oscillations and highly volatile prices. To address these issues, the paper develops an aggregate model of DERs under transactive coordination. A set of Markov transition equations have been developed over discrete ranges (referred to as "bins") of price levels and their associated DER operating states. A detailed investigation of the performance of this aggregate model is presented. With reformulation of the transition equations, the bin model has been incorporated into a model predictive control setting using both mixed integer programming and quadratic programming. A case study shows that a population of TCLs can be managed economically while avoiding congestion in a distribution grid. Simulations also demonstrate that power oscillations arising from synchronization of TCLs can be effectively avoided.

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An Incentive-Based Online Optimization Framework for Distribution Grids

Cited by 93 publications

References 40 publications

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

Accelerated Voltage Regulation in Multi-Phase Distribution Networks Based on Hierarchical Distributed Algorithm

A Dynamical Systems Approach to Modeling and Analysis of Transactive Energy Coordination

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