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Stochastic congestion management in power markets using efficient scenario approaches

机译：使用有效方案方法进行电力市场中的随机拥塞管理

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摘要

Congestion management in electricity markets is traditionally performed using deterministic values of system parameters assuming a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties comprising outage of generating units and transmission branches. The Forced Outage Rate of equipment is employed in the stochastic programming. Using the Monte Carlo simulation, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. The performance of the ordinary as well as Lattice rank-1 and rank-2 Monte Carlo simulations is evaluated in the proposed congestion management framework. As a tradeoff between computation time and accuracy, scenario reduction based on the standard deviation of accepted scenarios is adopted. The stochastic congestion management solution is obtained by aggregating individual solutions of accepted scenarios. Congestion management using the proposed stochastic framework provides a more realistic solution compared with traditional deterministic solutions. Results of testing the proposed stochastic congestion management on the 24-bus reliability test system indicate the efficiency of the proposed framework.
机译：传统上，电力市场中的拥塞管理是使用系统参数的确定值（假设网络配置固定）执行的。针对电力系统的不确定性，包括发电机组和输电支路的中断，提出了一种用于拥塞管理的随机规划框架。设备的强制断电率用于随机编程中。使用蒙特卡洛模拟，生成了电力系统运行状态的可能方案，并为每种方案分配了概率。在建议的拥塞管理框架中评估了普通以及莱迪思的rank-1和rank-2蒙特卡洛仿真的性能。作为计算时间和准确性之间的折衷，采用了基于已接受方案的标准偏差的方案减少。随机拥塞管理解决方案是通过汇总接受方案的各个解决方案而获得的。与传统的确定性解决方案相比，使用建议的随机框架进行的拥塞管理提供了更现实的解决方案。在24总线可靠性测试系统上测试所提出的随机拥塞管理的结果表明了所提出框架的效率。

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