Litcius/Paper detail

Distributed power flow and distributed optimization—Formulation, solution, and open source implementation

Tillmann Mühlpfordt, Xinliang Dai, Alexander Engelmann, Veit Hagenmeyer

2021Sustainable Energy Grids and Networks18 citationsDOIOpen Access PDF

Abstract

Solving the power flow problem in a distributed fashion empowers different grid operators to compute the overall grid state without having to share grid models—this is a practical problem to which industry does not have off-the-shelf answers. We propose two physically consistent problem formulations (a feasibility and a least-squares formulation) amenable to two solution methods from distributed optimization: the Alternating direction method of multipliers (admm), and the Augmented Lagrangian based Alternating Direction Inexact Newton method (aladin); the latter comes with convergence guarantees. In addition, we provide open source matlab code for rapid prototyping for distributed power flow (rapidpf): a fully matpower-compatible software that facilitates the laborious task of formulating power flow problems as distributed optimization problems. Simulation results for systems ranging from 53 buses (with 3 regions) up to 4662 buses (with 5 regions) show that the least-squares formulation solved with aladin requires just about half a dozen coordinating steps before the power flow problem is solved.

Topics & Concepts

Computer scienceMathematical optimizationModular designConvergence (economics)GridCode (set theory)MATLABFlow (mathematics)Power (physics)Power flowDistributed computingParallel computingComputational scienceElectric power systemSet (abstract data type)MathematicsOperating systemEconomic growthPhysicsProgramming languageQuantum mechanicsEconomicsGeometryOptimal Power Flow DistributionPower System Optimization and StabilityAdvanced Numerical Methods in Computational Mathematics