图C2 不同储能配置下系统SAIDI
图C3 不同储能配置下储能耗尽次数
图C4 不同储能配置下二次故障次数
图C5 不同储能配置下重要负荷P19故障率
仿真结果表明：
1)在光伏装机容量和储能额定功率相同且大于400 kW时,采用考虑光储持续带载能力的策
略3其可靠性指标(ASAI、SAIDI和微网的SAIFI)明显优于策略2。
2)对于不考虑光储持续带载能力的策略2,如附录C图C5所示,在储能容量一定,而额定功率增大时,配电网故障时段内储能电量被耗尽导致重要负荷被迫停电的概率将会增大,而当储能额定功率一定,容量增大时,能有效降低重要负荷的故障率。
3)对于考虑光储持续带载能力的策略3能很好分配储能电量的使用,优先保证对重要负荷的持续供电;提高储能的额定容量或额定功率,均能够进一步减少微网内部负荷的停电次数和时间,提高可靠性水平。
4)仅对储能投资成本作分析,锂离子电池的容量成本为1200元/kW,电量成本为4000元/
(kW˙h)[25]。对于策略3,当系统ASAI达到99.91%时需配置容量为1 MW˙h、额定功率为0.2 MW的能量型储能或者配置容量为0.5 MW˙h、额定功率为0.6 MW的功率型储能,其投资成本分别为
424万元和272万元,可见在当前算例条件下功率型储能对提高配电网可靠性更加经济。
4.4 不同储能容量和置信度对可靠性的影响
通过改变储能容量和光伏可信出力的置信度,并采用本文所提出的动态孤岛划分策略3,得到微网孤岛持续运行成功率ICOSR和微网平均停电频率SAIFI的评估结果如图3和图4所示,由图3、4可知：
图3 不同仿真条件的ICOSR
图4 不同仿真条件的微网SAIFI
1)微网ICOSR值随储能容量的增加而增加,因为储能容量的增加降低了微网孤岛运行条件下因储能电量耗尽而导致的微网内所有用户停电的风险;光伏可信出力置信度的降低会使初始孤岛的范围扩大,在储能容量较小时,过大的初始孤岛范围会显著增加储能电量耗尽的风险,ICOSR指标将会下降。
2)当储能容量一定时,其微网SAIFI指标随置信度的减小而呈现先减小后增大的趋势。这是因为微网SAIFI指标由微网一次故障率和二次故障率组成,其中一次故障是指配电网故障时,因微网负荷不在孤岛运行范围内直接引起的负荷停电,二次故障是指微网孤岛运行时因电源功率或能量不足而导致的负荷停电,如图5所示。当光伏可信出力置信度越低时,初始孤岛所带负荷范围越大,一次故障率也就越低,但二次故障的风险会显著增大。
图5 储能容量为4 MW?h的微网SAIFI分析图
5 结语
本文考虑含光储微网中光伏出力和负荷需求的不确定性,提出了基于光储系统可持续带载能力的微电网动态孤岛划分模型并进行可靠性评估,结果表明：
1)考虑光储系统可持续带载能力的动态孤岛划分策略能够计及故障期间光伏出力和负荷的不确定性,通过动态调整孤岛范围,在保证微网内重要负荷持续稳定供电的前提下,有利于提高系统的整体供电可靠性。
2)在微网内储能容量一定的情况下,通过设置合理的光伏可信出力置信度可以更有效地发挥本文所提动态孤岛划分策略的优势,提高微网内负荷的成功运行概率,减小其二次故障率。
需要指出的是：本文所提的孤岛划分策略和可靠性评估的原理和方法同样适用于含其他间歇性分布式电源的微网的孤岛重构,同时在考虑储能配置成本的前提下,如何通过储能容量的优化配置提高含源配电网供电可靠性将是下一步的研究方向。
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