采用马尔可夫链—多场景技术的交直流主动配电网优化调度

针对含有柔性直流装置的交直流混合主动配电网,构建基于场景分析的随机优化调度模型。计及时间轴线上各点误差相关性,利用基于马尔可夫链的多场景技术模拟风电、光伏与负荷随时间变化的间歇性和波动性;通过模糊C均值聚类思想进行场景削减得到典型场景。提出多时间尺度的协调优化调度策略:长时间尺度计及不确定性,以电网期望成本最小为目标,优化联络线出力和柔性直流装置出力;短时间尺度调整可控单元,使两级优化结果偏差最小。算例验证了采用马尔可夫链的多场景抽样能有效描述原始问题的不确定性,修正随时间推移逐渐增大的预测偏差,减轻短时间尺度调度压力;验证了所述调度策略能有效应对间歇式能源的不确定波动,提高分布式能源消纳能力。

Optimized Scheduling of AC/DC Hybrid Active Distribution Network Using Markov Chains-Multiple Scenarios Technique

Aimed at the AC/DC hybrid active distribution network(ADN)containing voltage sourced converters(VSCs), a scenario-based stochastic optimal scheduling model is built. Considering the temporal correlation of the errors changes, a multiple scenarios technique combined with Markov chain is used to imitate the intermittency and volatility of the wind power, photovoltaic power and uncertain load. A large number of scenarios are clustered by fuzzy C-means algorithm to gain representative scenarios. A multi-time-scale coordinated scheduling strategy is proposed and the specific strategies are as follows: In the long-time scale, the outputs of the connecting line and flexible DC devices are optimized with the goal of minimizing the total cost of the power grid, while in the short-time scale, the output of adjustable resources is corrected on the basis of long-time scale results to minimize the difference. The results verify that multiple scenarios technique with the Markov chain can describe the uncertainty of original problem effectively and correct the prediction deviation which increases over time. It is also beneficial to reducing the pressure of short-time scale dispatch. In addition, this paper illustrates that the model is contributed to deal with the uncertain fluctuations and improve the consumptive ability of intermittent resource.