基于降低风电机组叶片损伤的风电机组组合优化

对于大型风电场，研究机组组合优化，可以提高风电场运行水平，提高风电场经济效益。叶片是风电机组的关键部件之一，占风机总成本的20%，是影响风电机组使用寿命的重要因素之一。通过对叶根在不同风况下四种不同载荷工况的受力分析，量化了不同运行工况下叶片损伤量，确定了叶片损伤量与叶片寿命的关系，建立了风电场各机组总叶片损伤量的数学模型；应用改进二进制粒子群(BPSO)优化算法，结合风电场预测功率数据和负荷调度要求，以叶片损伤量最小为优化目标，建立风电场内机组组合优化调度模型。将所提出模型应用于某49.5 MW风电场，对33台机组进行组合优化，算例结果表明在满足负荷的要求下，可减少启停机次数，延长机组寿命，验证了该算法的可行性和有效性。

Wind turbine unit commitment optimization based on the reduced blade damage

For large wind farms, the unit combinatorial optimization research can improve the level of wind farm operation and increase the economic efficiency of wind farms. The blades are one of the key components of wind turbines, which not only account for 20% of total wind turbine cost, but also have much influence on the wind turbine life. This paper makes a stress analysis of blades root at four different load conditions, quantifies damage of the blades, determines its relationship with blade life, and establishes a mathematic model of total blade damage value of each wind turbine unit. Moreover, based on the theory of improved binary particle swarm optimization (BPSO) algorithm, a unit commitment optimization model is proposed. For this model, the minimum of blade damage is taken as optimization objective, and wind power prediction results and load dispatch demand of electrical system are fully considered. A 49.5 MW wind farm is taken as an example and combinatorial optimization of 33 units is made. Case study shows that while meeting the load requirements, it can reduce the number of start-stop times and extend the unit life, verifying the feasibility and reliability of the proposed optimal dispatching model.