Real-Time Feedback-Based Optimization of Distribution Grids: A Unified Approach

With a large-scale integration of distributed energy resources (DERs), distribution systems are expected to be capable of providing capacity support for the transmission grid. To effectively harness the collective flexibility from massive DER devices, this paper studies distribution-level power aggregation strategies for transmission-distribution interaction. In particular, this paper proposes a method to model and quantify the aggregate power flexibility, i.e., the net power injection achievable at the substation, in unbalanced distribution systems over time. Incorporating the network constraints and multi-phase unbalanced modeling, the proposed method obtains an effective approximate feasible region of the net power injection. For any aggregate power trajectory within this region, it is proved that there exists a feasible disaggregation solution. In addition, a distributed model predictive control (MPC) framework is developed for practical implementation of the transmission-distribution interaction. At last, we demonstrate the performances of the proposed method via numerical tests on a real-world distribution feeder with 126 multi-phase nodes.Index Terms-Power aggregation, distributed energy resources, unbalanced optimal power flow, power flexibility, distributed optimization. NOMENCLATUREA. Parameters N Number of buses (except the substation). N Y , N ∆ Number of buses with wye-, delta-connection. L Number of distribution lines. v, v Upper, lower limits of the three-phase nodal voltage magnitudes for all buses. i L , i L Upper, lower limits of the three-phase line current magnitudes for all distribution lines. P g,ψ i,t , P g,ψ i,t Upper, lower limits of active PV power generation in phase ψ of bus i at time t. S g,ψ i,t Apparent power capacity of PV units in phase ψ of bus i at time t. P e,ψ i,t , P e,ψ i,t Upper, lower limits of active power output of ES devices in phase ψ of bus i at time t. S e,ψ i,t Apparent power capacity of ES devices in phase ψ of bus i at time t. E i , E i Upper, lower limits for state of charge of ES devices at bus i. X. Chen and N. Li are with the School of Engineering and Applied Sciences, Harvard University, USA. d,ψ i,t , P d,ψ i,t Upper, lower limits for controllable active loads in phase ψ of bus i at time t. F out i,t Outside temperature for HVAC systems at bus i at time t. F i , F i Upper, lower limits of comfortable temperature zone for HVAC systems at bus i. ∆t Length of each time slot under discretized time horizon. B. Variables p Y , q Y ∈ R 3N Y Column vector of the three-phase active, reactive power injection via wye-connection. p ∆ , q ∆ ∈ R 3N∆ Column vector of the three-phase active, reactive power injection via delta-connection. v ∈ R 3N Column vector collecting the three-phase nodal voltage magnitudes for all buses. i L ∈ R 3L Column vector collecting the three-phase line current magnitudes for all distribution lines. p 0 ∈ R 3 Column vector of the three-phase net active power injection at the substation. P g,ψ i,t , Q g,ψ i,t Active, reactive PV power generation ...

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“…We set the initial SOC of the energy storage devices to 50%. Detailed configurations and parameters of this feeder system are provided in [27].…”

Section: A Simulation Setupmentioning

confidence: 99%

Aggregate Power Flexibility in Unbalanced Distribution Systems

Chen

Dall’Anese

Zhao

et al. 2020

IEEE Trans. Smart Grid

Self Cite

127

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“…We consider the case where a subset of the buses have PV generation (bus 2, 4, 7, 8,9,10,11,12,13,14,15,16,19,20,23,25,26,32). We use the load and PV generation profile in [39]. The time span of the data set is one day (24 hours), and the time resolution is 6 seconds.…”

Section: A Performance and Robustness Under Time-varying Load And Pvmentioning

confidence: 99%

Distributed Optimal Voltage Control With Asynchronous and Delayed Communication

Magnússon

2020

IEEE Trans. Smart Grid

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The increased penetration of volatile renewable energy into distribution networks necessities more efficient distributed voltage control. In this paper, we design distributed feedback control algorithms where each bus can inject both active and reactive power into the grid to regulate the voltages. The control law on each bus is only based on local voltage measurements and communication to its physical neighbors. Moreover, the buses can perform their updates asynchronously without receiving information from their neighbors for periods of time. The algorithm enforces hard upper and lower limits on the active and reactive powers at every iteration. We prove that the algorithm converges to the optimal feasible voltage profile, assuming linear power flows. This provable convergence is maintained under bounded communication delays and asynchronous communications. We further numerically test the performance of the algorithm using the full nonlinear AC power flow model. Our simulations show the effectiveness of our algorithm on realistic networks with both static and fluctuating loads, even in the presence of communication delays.

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“…Next, we test OPTDIST-VC in a more realistic setting. We use the load and PV generation profile in [44]. The time span of the data set is one day (24 hours), and the time resolution is 6s.…”

Section: A Single Phase Networkmentioning

confidence: 99%

“…We evaluate OPTDIST-VC on a three-phase unbalanced network. 8 We use the network with 126 multiphase nodes, the PV generation and the load profile in [44]. See [44, Section V] for a detailed description of the network structure and parameters.…”

Section: B Three-phase Unbalanced Networkmentioning

confidence: 99%

Optimal Distributed Feedback Voltage Control Under Limited Reactive Power

2020

IEEE Trans. Power Syst.

101

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In this paper, we propose a distributed voltage control in power distribution networks through reactive power compensation. The proposed control can (i) operate in a distributed fashion where each bus makes its decision based on local voltage measurements and communication with neighboring buses, (ii) always satisfy the reactive power capacity constraint, (iii) drive the voltage magnitude into an acceptable range, and (iv) minimize an operational cost.We also perform various numerical case studies to demonstrate the effectiveness and robustness of the controller using the nonlinear power flow model.

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Real-Time Feedback-Based Optimization of Distribution Grids: A Unified Approach

Cited by 125 publications

References 47 publications

Aggregate Power Flexibility in Unbalanced Distribution Systems

Aggregate Power Flexibility in Unbalanced Distribution Systems

Distributed Optimal Voltage Control With Asynchronous and Delayed Communication

Optimal Distributed Feedback Voltage Control Under Limited Reactive Power

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