TY - JOUR
T1 - Convex Relaxation of Grid-Connected Energy Storage System Models with Complementarity Constraints in DC OPF
AU - Garifi, Kaitlyn
AU - Baker, Kyri
AU - Christensen, Dane
AU - Touri, Behrouz
N1 - Manuscript received July 8, 2019; revised October 21, 2019 and March 5, 2020; accepted April 7, 2020. Date of publication April 30, 2020; date of current version August 21, 2020. This work was supported in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract DE-AC36-08GO28308, and in part by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Building Technologies Office. Paper no. TSG-00973-2019. (Corresponding author: Kaitlyn Garifi.) Kaitlyn Garifi and Kyri Baker are with the College of Engineering and Applied Science, University of Colorado Boulder, Boulder, CO 80309 USA (e-mail: [email protected]; [email protected]).
PY - 2020/9
Y1 - 2020/9
N2 - Including complementarity constraints in energy storage system (ESS) models in optimization problems ensure an optimal solution will not produce a physically unrealizable control strategy where there is simultaneous charging and discharging. However, the current approaches to impose complementarity constraints require the use of non-convex optimization methods. In this paper, we propose a convex relaxation for a common ESS model that has terms for both charging and discharging based on a penalty reformulation for use in a model predictive control (MPC) based optimal power flow (DC OPF) problem. In this approach, the complementarity constraints are omitted and a penalty term is added to the optimization objective function. For the DC OPF problem, we provide analysis for the conditions under which the convex relaxation of the complementarity constraint ensures that a solution with simultaneous ESS charging and discharging operation is suboptimal. Simulation results demonstrating ESS behavior with and without the penalty reformulation are provided for an MPC-based DC OPF problem on multiple IEEE test systems.
AB - Including complementarity constraints in energy storage system (ESS) models in optimization problems ensure an optimal solution will not produce a physically unrealizable control strategy where there is simultaneous charging and discharging. However, the current approaches to impose complementarity constraints require the use of non-convex optimization methods. In this paper, we propose a convex relaxation for a common ESS model that has terms for both charging and discharging based on a penalty reformulation for use in a model predictive control (MPC) based optimal power flow (DC OPF) problem. In this approach, the complementarity constraints are omitted and a penalty term is added to the optimization objective function. For the DC OPF problem, we provide analysis for the conditions under which the convex relaxation of the complementarity constraint ensures that a solution with simultaneous ESS charging and discharging operation is suboptimal. Simulation results demonstrating ESS behavior with and without the penalty reformulation are provided for an MPC-based DC OPF problem on multiple IEEE test systems.
KW - energy storage systems
KW - model predictive control
KW - Optimal power flow
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U2 - 10.1109/TSG.2020.2987785
DO - 10.1109/TSG.2020.2987785
M3 - Article
AN - SCOPUS:85090110290
SN - 1949-3053
VL - 11
SP - 4070
EP - 4079
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
IS - 5
M1 - 9082838
ER -