计及源/网不确定性的区域电网有功不平衡度评估

区域电网互联可提高供电可靠性和新能源消纳能力，现有调度研究多关注全网功率平衡和联络线功率优化，忽略区域有功平衡能力。评估区域有功不平衡度，需要考虑长期运行中的不确定性因素，不能基于单个时间断面。计及风/光出力不确定性和电网随机故障，提出区域有功不平衡度指标和评估算法。首先改进K-means算法聚类风光出力场景。其次定义描述区域不平衡度的两个指标：电力不平衡度和供电能力不平衡度。考虑源/网不确定性，采用状态枚举和概率加权方法计算上述指标。将不平衡度指标分别纳入目标函数和约束条件，提出计及不平衡度的发电再调度模型。最后建立目标函数对不平衡度约束的灵敏度模型，估计放宽不平衡度约束对优化目标的影响。结果表明：所提算法以切负荷量增加为代价，可减小区域电网有功不平衡度。在不同出力/故障场景下，各区域综合不平衡度变化趋势基本一致。放松电力不平衡度约束，可减小综合优化目标。

Active Power Imbalance Assessment of Regional Grids with Uncertainty of Source/Network

Regional grid interconnection improves power supply reliability and renewable power consumption. The existing studies mostly focus on the power balance of the whole system and the power optimization of the tie line, and ignore the active power balance of the regional grids. Evaluation to active power imbalance of regional grids should based on long-term operation with uncertainties instead of a given snapshot. Considering the uncertainty of wind/photovoltaic outputs and the random fault of the grid, the indices and evaluation method for regional active power imbalance are proposed. Firstly, the K-means algorithm is improved to cluster the wind/photovoltaic output scenarios. Secondly, two indices are defined to describe regional imbalance degree, power imbalance degree and power supply capacity imbalance degree. Considering the uncertainty of source/network, state enumeration and probability weighting methods are applied to calculate the indices. The imbalance indices are introduced into the objective function and the constraints respectively, and the generation re-dispatch model considering the imbalance degree is proposed. Finally, the sensitivity model of the objective function to the imbalance degree constraint is established to estimate the effect of adjusting the imbalance degree constraint on the optimization objective. The numerical results show that the proposed algorithm can reduce the active power imbalance of regional grid at the cost of increasing the cutting load. With different outputs/fault scenarios, the variation trend of comprehensive imbalance degree in all regions is basically the same. Releasing the power imbalance constraint can reduce the comprehensive optimization objective.