Optimal layout of a Co-Located wind/tidal current farm considering forbidden zones
Co-location of wind and tidal current turbines (WTs/TCTs) is a new way to improve the economy and reliability of electricity generation from renewable energy sources. In this paper, an optimization model for determining the configuration of a co-located wind/tidal current farm (WF/TCF) is proposed....
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Veröffentlicht in: | Energy (Oxford) 2021-08, Vol.228, p.120570, Article 120570 |
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Sprache: | eng |
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Zusammenfassung: | Co-location of wind and tidal current turbines (WTs/TCTs) is a new way to improve the economy and reliability of electricity generation from renewable energy sources. In this paper, an optimization model for determining the configuration of a co-located wind/tidal current farm (WF/TCF) is proposed. The objectives include the minimization of the system levelized cost of energy (LCOE) and the maximization of the system average power supply reliability (APSR). In the planning area, there are certain zones where there are important restrictions which do not allow WTs/TCTs to be installed. These are called forbidden zones. When deciding the feasible area in the optimization, the complement of the forbidden zones in the planning area is used. The optimization problem is formulated as a coordinate model (CM) and a grid model (GM), both solved by the multi-swarm optimization (MSO) algorithm. The proposed approach is tested in an offshore area of Zhejiang province, China. Simulation results indicate that the co-location of a WF/TCF is an economic-technical efficient approach to harvest marine renewable energy. Also, the MSO algorithm outperforms its counterparts, the particle swarm optimization (PSO) and the discrete particle swarm optimization (DPSO) algorithms, in solving the CM and the GM of the WF/TCF layout optimization problem.
•The layout of a co-located WF/TCF is optimized.•The optimization objectives are the minimization of LCOE and the maximization of APSR.•The forbidden zones in the planning area are considered in the optimization.•The optimization problem is formulated as a CM and a GM, respectively.•The MSO algorithm is compared with the PSO and the DPSO algorithms. |
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ISSN: | 0360-5442 1873-6785 |
DOI: | 10.1016/j.energy.2021.120570 |