不确定性环境下的孤岛型微电网鲁棒优化算法

Robust Optimization Algorithm for Islanded Microgrid in Uncertain Environment

  • 摘要: 针对可再生能源出力和负荷功率的不确定性,提出了日前计划-日内调度的孤岛型微电网鲁棒优化算法,其中日前计划针对可能出现的最恶劣场景,利用列约束生成算法将问题分解为主问题和子问题,交互迭代求解最优经济调度方案;日内调度阶段,利用每一时段的实时测量信息,基于日前计划调度结果对调整成本进行二次优化,通过对传统能源发电的功率调整进行惩罚来追踪日前计划调度结果,并对弃风、弃光功率进行分段惩罚,最大程度地消纳可再生能源。算例表明:该算法能使微电网在输入输出不确定情况下保持良好的鲁棒性和经济性,验证了算法的有效性。

     

    Abstract: In allusion to the uncertainty of renewable energy sources and loads, based on day-ahead planning and intra-day scheduling a robust optimization algorithm for islanded microgrid was designed. In this algorithm, aiming at the uncertainty of renewable energy sources and loads that might appear, the day-ahead planning searched the worst case scenario under the uncertain environment and utilizing column constraint generation algorithm the problem was decomposed into primal problem and subproblem, then by means of interactive iteration the optimal economic dispatch scheme under the scenario was solved; in the intra-day scheduling phase, utilizing current realtime measured information of renewable energy sources and loads and based on the dispatching results of day-ahead planning the realtime secondary optimization of the adjustment cost was performed, and the segmented punishment for wind power curtailment and PV power curtailment was implemented, thus renewable energy sources was furthest accommodated. Results of calculation example show that the designed algorithm can make the microgrid kept satisfied robustness and economy in the uncertain input and output environment brought by forecast error, so the effectiveness of the designed algorithm is verified.

     

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