| Title | Economic predictive control for isolated microgrids based on real world demand/renewable energy data and forecast errors |
|---|---|
| Authors | MANZANO CRESPO, JOSÉ MARÍA, SALVADOR ORTIZ, JOSÉ RAMÓN, ROMAINE, JAMES BRIAN, ALVARADO BARRIOS, LÁZARO |
| External publication | No |
| Means | Renew. Energy |
| Scope | Article |
| Nature | Científica |
| JCR Quartile | 1 |
| SJR Quartile | 1 |
| JCR Impact | 8.7 |
| SJR Impact | 1.815 |
| Web | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131404799&doi=10.1016%2fj.renene.2022.05.103&partnerID=40&md5=1c5fa04ae3559733721c6be6ad8dcaaa |
| Publication date | 01/07/2022 |
| ISI | 000810187900011 |
| Scopus Id | 2-s2.0-85131404799 |
| DOI | 10.1016/j.renene.2022.05.103 |
| Abstract | In this work, the operation of microgrids is studied, using real data for demand and renewable energy sources. A mixed integer nonlinear program to operate the microgrid is proposed, following a model predictive control methodology, which allows to enhance the economic performance by means of a predictive strategy. A comparison with other techniques without predictive feature nor forecast mismatches is made, showing that our method outperforms them by adapting the current control decision to future costly issues. The case study shows savings of more than 10%, analysing the qualitative aspects of the proposed strategy. (c) 2022 Elsevier Ltd. All rights reserved. |
| Keywords | Microgrid; Economic dispatch; Predictive control; Real data; Forecast mismatch |
| Universidad Loyola members |