A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties
This paper presents a Particle Swarm Optimization (PSO) methodology to solve the problem of day-ahead microgrid (MG) dispatch with high penetration of Distributed Generation (DG) and considering uncertainties. The proposed methodology has the objective to satisfy demand aiming at obtaining the maxim...
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| Other Authors: | , |
| Format: | conferenceObject |
| Language: | eng |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10400.22/17319 |
| Country: | Portugal |
| Oai: | oai:recipp.ipp.pt:10400.22/17319 |
| Summary: | This paper presents a Particle Swarm Optimization (PSO) methodology to solve the problem of day-ahead microgrid (MG) dispatch with high penetration of Distributed Generation (DG) and considering uncertainties. The proposed methodology has the objective to satisfy demand aiming at obtaining the maximum profit, corresponding to the difference between the income and costs of the MG. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind sources. This uncertainty is modeled with the use of a robust approach in PSO. A case study is presented using a 21-bus MG from a real university campus in Portugal, and the projection of distributed energy resources based on the evolution scenario for the year 2050 managed by an aggregator. |
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