In this work, the application of an original distributed optimal power flow method to test a microgrid in the Savona area, Italy is proposed. The microgrid shows different types of Distributed Energy Resources (DERs) and is connected to the main grid through a fixed power bus. Due to the high computational speed, the applied distributed Optimal Power Flow can be performed almost in real time, i.e. every 5 minutes or less. The operating solution found for generators, simply using local information, corresponds to a suboptimal condition with reduced losses, bus voltages and line currents within constrained intervals. The distributed optimization algorithm is iterative, but also fast. It is based on the use of Kirchhoff and simplified power flow equations and heuristic rules and can be employed for islanded and grid connected medium or small networks. Test results on a real world test system, the Savona Campus "Smart Polygeneration Microgrid" (SPM), prove that a few iterations are enough to converge to a sub-optimal solution.
Buono, L., Sanseverino, E.R., Di Silvestre, M.L., Bracco, S., Delfino, F. (2016). Distributed optimal power flow for islanded microgrids: An application to the Smart Polygeneration Microgrid of the Genoa University. In 2016 IEEE International Smart Cities Conference (ISC2) (pp.1-7). Institute of Electrical and Electronics Engineers Inc. [10.1109/ISC2.2016.7580793].
Distributed optimal power flow for islanded microgrids: An application to the Smart Polygeneration Microgrid of the Genoa University
Sanseverino, Eleonora Riva;Di Silvestre, Maria Luisa;
2016-01-01
Abstract
In this work, the application of an original distributed optimal power flow method to test a microgrid in the Savona area, Italy is proposed. The microgrid shows different types of Distributed Energy Resources (DERs) and is connected to the main grid through a fixed power bus. Due to the high computational speed, the applied distributed Optimal Power Flow can be performed almost in real time, i.e. every 5 minutes or less. The operating solution found for generators, simply using local information, corresponds to a suboptimal condition with reduced losses, bus voltages and line currents within constrained intervals. The distributed optimization algorithm is iterative, but also fast. It is based on the use of Kirchhoff and simplified power flow equations and heuristic rules and can be employed for islanded and grid connected medium or small networks. Test results on a real world test system, the Savona Campus "Smart Polygeneration Microgrid" (SPM), prove that a few iterations are enough to converge to a sub-optimal solution.File | Dimensione | Formato | |
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