Back to Search
Start Over
Centralized Airflow Control to Reduce Output Power Variation in a Complex OWC Ocean Energy Network
- Source :
- Addi: Archivo Digital para la Docencia y la Investigación, Universidad del País Vasco, Addi. Archivo Digital para la Docencia y la Investigación, instname, Complexity, Vol 2020 (2020)
- Publication Year :
- 2020
- Publisher :
- Hindawi Limited, 2020.
-
Abstract
- A centralized airflow control scheme for a complex ocean energy network (OEN) is proposed in this paper to reduce the output power variation (OPV). The OEN is an integrated network of multiple oscillating water columns (OWCs) that are located at different geographical sites connected to a common electrical grid. The complexity of the OWC-OEN increases manifolds due to the integration of several OWCs and design of controllers become very challenging task. So, the centralized airflow control scheme is designed in two stages. In control stage-1, a proportional-integral- (PI-) type controller is designed to provide a common reference command to control stage-2. In control stage-2, the antiwindup PID controllers are implemented for the airflow control of all the OWCs simultaneously. In order to tune the large number of control parameters of this complex system, a fitness function based on integral squared error (ISE) is minimized using the widely adopted particle swarm optimization (PSO) technique. Next, the simulation results were obtained with random wave profiles created using the Joint North Sea Wave Project (JONSWAP) irregular wave model. The OPV of the proposed OWC-OEN was reduced significantly as compared to the individual OWC. It was further observed that the OPV of the proposed scheme was lower than that achieved with uncontrolled and MPPT controlled OWC-OEN. The effect of communication delay on the OPV of the proposed OWC-OEN scheme was also investigated with the proposed controller, which was found to be robust for a delay up to 100 ms. This work was supported in part by the Basque Government through project IT1207-19 and MCIU/MINECO through RTI2018-094902-B-C21/RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE).
- Subjects :
- Multidisciplinary
Article Subject
General Computer Science
Computer science
Oscillation
020209 energy
020208 electrical & electronic engineering
Particle swarm optimization
PID controller
QA75.5-76.95
02 engineering and technology
control strategies
renewable energy
Electrical grid
wells turbine
Maximum power point tracking
Power (physics)
Water column
Control theory
Electronic computers. Computer science
Marine energy
0202 electrical engineering, electronic engineering, information engineering
wave energy
Subjects
Details
- ISSN :
- 10990526 and 10762787
- Volume :
- 2020
- Database :
- OpenAIRE
- Journal :
- Complexity
- Accession number :
- edsair.doi.dedup.....84b6a348e6c6fa944fbed8b762123eaa