基于风力机尾流排斥的平坦地形风电场微观选址优化

平坦地形风电场微观选址的优化研究中,常采用带有随机量的元启发式算法,这些算法难以达到全局最优,优化效率较低,且通常需要通过划分网格、增加约束才能得到稳定解。针对这些问题,文中提出了一种专门针对平坦地形风电场微观选址的高效且有稳定优化解的元启发式算法——风力机尾流排斥优化算法。参考范德华力原理,提出了风力机尾流排斥力的概念,用于描述风力机在尾流作用下的相互影响:2台风力机之间尾流作用越大,风力机尾流排斥力也越大。在算法优化过程中,风力机会在风力机尾流排斥力的作用下向使尾流减小的方向不断移动,直到达到最优解。仿真结果表明:风力机尾流排斥优化算法不需要网格约束,优化效率高,能得到确定的优质解,且优化结果符合实际工程要求。

Micro-siting Optimization of Wind Farm in Flat Terrain Based on Wind Turbine Wake Repellency

For micro-siting optimization of wind farms in the flat terrain, the meta-heuristic algorithms with random quantities are frequently used. These algorithms are hard to achieve a global optimization, and are relatively inefficient. Grids and constraints are usually needed to make a stable solution. To address these problems, this paper proposes an efficient meta-heuristic algorithm with stable optimization solution for the micro-siting of wind farms in the flat terrain, i.e., wind turbine wake repellency optimization algorithm. According to the principle of van der Waals force, the concept of wind turbine wake repulsive force is proposed, which is used to describe the mutual influence between wind turbines with wake effects. The greater the wake effect between two wind turbines, the greater the wind turbine repulsive force. During the process of optimization, the wind turbine will continuously move in the direction to reduce the wake under the action of the wind turbine wake repulsive force until the optimal solution is obtained. Simulation results show that the wind turbine wake repellency optimization algorithm does not need grid constraints, has a high optimization efficiency, and can obtain a certain optimal result, while the optimization results meet the actual engineering requirements.