Improved gravitational search algorithm for unit commitment considering uncertainty of wind power
Improved gravitational search algorithm for unit commitment considering uncertainty of wind power
复制标题
考虑风电不确定性的机组组合改进引力搜索算法
DOI：
10.1016/j.energy.2014.02.014
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发表时间：
2014
期刊：
影响因子：
9
通讯作者：
Tian Hao
中科院分区：
文献类型：
--
作者：
Ji Bin;Yuan Xiaohui;Chen Zhihuan;Tian Hao
随着风电场并网率的不断提高，由于风电功率的间歇性和波动性，机组组合问题的求解变得更加困难。本文应用想定生成与归约技术，模拟了其不确定性对系统运行的影响。在此基础上，建立了考虑风电并网的热统一计算问题模型。提出了结合量子二进制引力搜索算法(GSA)和情景分析方法来求解UCW问题。同时，采用启发式搜索策略处理各情景下热力机组的约束条件。此外，在优化过程中还利用了基于平均满负荷成本和最大功率输出之间的权重的热电机组优先列表。并以风电并网和不并网的UC测试系统为例，验证了该方法的可行性和有效性以及算法的性能。并对计算结果进行了详细的分析，验证了该模型和方法的可行性。与其他方法的比较表明，该方法对有无风电场并网的UC问题具有较高的求解效率。
With increasing wind farm integrations, unit commitment (UC) is more difficult to solve because of the intermittent and fluctuation nature of wind power. In this paper, scenario generation and reduction technique is applied to simulate the impacts of its uncertainty on system operation. And then a model of thermal UC problem with wind power integration (UCW) is established. Combination of quantum-inspired binary gravitational search algorithm (GSA) and scenario analysis method is proposed to solve UCW problem. Meanwhile, heuristic search strategies are used to handle the constraints of thermal unit for each scenario. In addition, a priority list of thermal units based on the weight between average full-load cost and maximal power output is utilized during the optimization process. Moreover, two UC test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method as well as the performance of the algorithm. The results are analyzed in detail, which demonstrate the model and the proposed method is practicable. The comparison with other methods clearly shows that the proposed method has higher efficiency for solving UC problems with and even without wind farm integration.