Convex Relaxation of Grid-Connected Energy Storage System Models With Complementarity Constraints in DC OPF
- Univ. of Colorado, Boulder, CO (United States)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Univ. of California, San Diego, CA (United States)
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. Here, 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.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (EE-5B)
- Grant/Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1660118
- Report Number(s):
- NREL/JA--5500-77407; MainId:26353; UUID:1cea5bde-b4b8-4c54-8e36-7c54e82cb65c; MainAdminID:14128
- Journal Information:
- IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 5 Vol. 11; ISSN 1949-3053
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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