电网运行状态下的概率优化调度

Probabilistic Optimal Dispatching Under Operating Condition of Power Network

构建电网运行状态下的有功功率概率优化调度模型,该模型以期望运行效益最大化为目标,采用马尔可夫链对系统未来调度时段的预想事故状态概率进行预测,在满足所有预想事故发生前后状态所对应约束集下获取调度解。其中,在容许时间内,针对预想事故发生后可能出现的系统安全破坏情形,以发电机组允许的输出功率再调整、紧急负荷中断及输电元件短时允许过载量作为有机牵制扩展到约束集中,并考虑相应安全校正措施的费用代价。该模型实现了电网运行状态概率预测与有功调度决策的紧密结合,可得到系统期望最大运行收益的时序变化曲线及各时段下风险收益概率均衡的调度方式。以IEEE-14节点系统为例进行测试分析,论证所提模型的合理性和有效性。

A probabilistic active power optimal dispatching model under the power network operating condition has been established in this paper. With the forecasting probabilities of contingency states in future period by Markov chain, the optimal dispatching results can be obtained with the objective of maximizing the expected operating benefit and constraint-set of both pre-contingency and post-contingency state. And for the possible security breaking case during the post-contingency state, the unit ramping, emergent load interruption and transmission component short-term over loading within allowable time have been included in the constraint-set, also the cost of these corrective measures have been taken into account. Therefore, the forecasting probability of the power network operational state and active power optimal dispatching decision-making are close combined in this model, which can attain the curve of expected operating maximal benefit in different dispatching period, and can get the balanced dispatching mode under the probabilistic framework of harmonizing risk with benefit corresponding to that period, particularly adapting to the power system active power dispatching under market environment. At last, the analysis for IEEE-14 test system demonstrates the rationality and validity of this proposed model.