A Chance Constrained Information-Gap Decision Model for Multi-Period Microgrid Planning
A Chance Constrained Information-Gap Decision Model for Multi-Period Microgrid Planning
复制标题
多周期微电网规划的机会约束信息间隙决策模型
DOI：
10.1109/tpwrs.2017.2747625
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发表时间：
2018
影响因子：
6.6
通讯作者：
Zeng, Bo
中科院分区：
文献类型：
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作者：
Cao, Xiaoyu;Wang, Jianxue;Zeng, Bo
提出了一种多周期微电网扩展规划的机会约束信息差决策模型，该模型考虑了随机和非随机两类不确定性。MMEP的主要任务是确定微电网中分布式能源（DER）的最佳规模，类型选择和安装时间。在所提出的配方，信息缺口决策理论（IGDT）被用来对冲长期需求增长的非随机不确定性。然后，在运行阶段施加机会约束，以解决每小时可再生能源发电量和负荷变化的随机不确定性。机会约束信息差决策模型的目标是在满足一组高概率的运营约束条件的同时，最大化DER投资的稳健性水平。然而，IGDT和机会约束规划的结合使得计算变得非常具有挑战性。为了解决这一挑战，我们提出并实现了一个加强的双线性Benders分解方法。最后，通过简单和实际复杂微电网的算例研究，验证了所提规划模型的有效性。此外，我们的新的计算方法展示了一个上级解决方案的能力和可扩展性。相比直接使用专业的混合整数规划求解器，可以将计算时间减少几个数量级。
This paper presents a chance constrained information gap decision model for multi-period microgrid expansion planning (MMEP) considering two categories of uncertainties, namely random and non-random uncertainties. The main task of MMEP is to determine the optimal sizing, type selection, and installation time of distributed energy resources (DER) in microgrid. In the proposed formulation, information gap decision theory (IGDT) is applied to hedge against the non-random uncertainties of long-term demand growth. Then, chance constraints are imposed in the operational stage to address the random uncertainties of hourly renewable energy generation and load variation. The objective of chance constrained information gap decision model is to maximize the robustness level of DER investment meanwhile satisfying a set of operational constraints with a high probability. The integration of IGDT and chance constrained program, however, makes it very challenging to compute. To address this challenge, we propose and implement a strengthened bilinear Benders decomposition method. Finally, the effectiveness of proposed planning model is verified through the numerical studies on both the simple and practical complex microgrid. Also, our new computational method demonstrates a superior solution capacity and scalability. Compared to directly using a professional mixed integer programming solver, it could reduce the computational time by orders of magnitude.
系统规划中的权衡方法
DOI：
--
发表时间：
1988
期刊：
影响因子：
--
作者：
W. Burke;H. Merrill;F. Schweppe;B. E. Lovell;M. F. McCoy;S. Monohon
通讯作者：
S. Monohon