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Optimal Real-Time Operation Strategy for Microgrid: An ADP-Based Stochastic Nonlinear Optimization Approach

This paper proposes an approximate dynamic programming (ADP) based algorithm for the real-time operation of the microgrid under uncertainties. First, the optimal operation of the microgrid is formulated as a stochastic mixed-integer nonlinear programming (MINLP) problem, combining the ac power flow and the detailed operational character of the battery. For this NP-hard problem, the proposed ADP based energy management algorithm decomposes the original multitime periods MINLP problem into single-time period nonlinear programming problems. Thus, the sequential decisions can be made by solving Bellman's equation. Historical data is utilized offline to improve the optimality of the real-time decision, and the dependency on the forecast information is reduced. Comparative numerical simulations with several existing methods demonstrate the effectiveness and efficiency of the proposed algorithm.
- Aalborg University Library (AUB) Denmark
- Aalborg University Library (AUB) Aalborg Universitet Research Portal Denmark
- Huazhong University of Science and Technology China (People's Republic of)
- Aalborg University Library (AUB) Denmark
- State Key Laboratory of Advanced Electromagnetic Engineering and Technology China (People's Republic of)
Optimization, Microgrid, State of charge, Approximate dynamic programming (ADP), Battery, approximate dynamic programming (ADP), 620, 510, Generators, Batteries, Mathematical model, Real-time optimization, battery, Microgrids, real-time optimization, AC power flow, Real-time systems
Optimization, Microgrid, State of charge, Approximate dynamic programming (ADP), Battery, approximate dynamic programming (ADP), 620, 510, Generators, Batteries, Mathematical model, Real-time optimization, battery, Microgrids, real-time optimization, AC power flow, Real-time systems
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