计及风电预测误差不确定性的风电参与网架重构优化

在大停电后的电力系统恢复过程中,充分考虑风电场的功率支援可加快系统的恢复速度,而风电场出力又具有不确定性,这为系统恢复方案的制定带来了新的挑战。为此文中提出了一种考虑风电场出力不确定性的网架重构恢复方法,该方法首先以预测误差不确定性描述风电场出力不确定性,然后采用风电场限出力接入策略消除风功率波动性对网架重构带来的负面影响,同时定义网架恢复成功率指标描述风电场预测出力不确定性可能导致的恢复失败风险。之后,在机组节点恢复成功率不低于一定置信水平的前提下建立随机相关机会目标规划模型,以最大化网架恢复成功率和最小化网架恢复时间为优化目标,采用离散粒子群算法和随机模拟技术组成的混合智能算法求解模型。最后,以IEEE 39节点为算例对该方法与传统恢复方法进行了分析比较,结果表明,提出的恢复方法在有效应对风电场出力不确定性的同时能够有效缩短网架恢复时间,加快系统恢复进程。

Optimization of Power Network Reconstruction with Wind Farm Considering Uncertainty of Wind Power Prediction Error

In the process of power system restoration after a large power outage, the power support of wind farms is taken into account that it can speed up the restoration of the system. But the output of wind farms is uncertain, which poses a new challenge for the formulation of system restoration plans. A method of power network reconfiguration restoration is present considering the uncertain output of the wind farm. Firstly, the prediction error uncertainty model is used to describe the uncertain output of the wind farm, and then output strategy is limited by the wind farm to eliminate the negative impact of wind power volatility on grid reconfiguration. Meanwhile, the indicator which reflects the success rate of network restoration is defined to depict that the uncertainty of the wind farm forecast output may lead to the risk of restoration failure. After that, the stochastic dependent-chance programming model is established under the condition that the success rate of node restoration is not lower than a certain confidence level. By maximizing the success rate of network restoration and minimizing the restoration time of grid is regarded as the optimal objective, the model is solved by the hybrid intelligent algorithm composed of discrete particle swarm optimization algorithm and stochastic simulation techniques. Finally, the comparison and analysis of the proposed method and the traditional restoration method is made based on the example of IEEE 39-bus system. The result shows that the restoration strategy proposed in this paper can speed up the process of network reconstruction and reduce the restoration time of the grid while effectively coping with the uncertain output of the wind farm.