Grid-aware Distributed Model Predictive Control of Heterogeneous Resources in a Distribution Network: Theory and Experimental Validation
| Autor: | Gupta, Rahul Kumar, Sossan, Fabrizio, Paolone, Mario |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Energy Conversion 2020 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/TEC.2020.3015271 |
| Popis: | In this paper, we propose and experimentally validate a scheduling and control framework for distributed energy resources (DERs) that achieves to track a day-ahead dispatch plan of a distribution network hosting controllable and stochastic heterogeneous resources while respecting the local grid constraints on nodal voltages and lines ampacities. The framework consists of two algorithmic layers. In the first one (day-ahead scheduling), we determine an aggregated dispatch plan. In the second layer (real-time control), a distributed model predictive control (MPC) determines the active and reactive power set-points of the DERs so that their aggregated contribution tracks the dispatch plan while obeying to DERs operational constraints as well as the grids ones. The proposed framework is experimentally validated on a real-scale microgrid that reproduces the network specifications of the CIGRE microgrid benchmark system. Comment: This work has been accepted for publication in IEEE Transactions on Energy Conversion |
| Databáze: | arXiv |
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