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Optimal Battery Sizing in Microgrids Using Probabilistic Unit Commitment
DOI:10.1109/TII.2015.2509424.png)
摘要
En 中文
The Stochastic nature of wind power can cause insufficiency of supply in electrical systems. Applying an energy storage system can alleviate the impact of wind power forecast error on power systems performance and increase system tolerance against deficiency of supply. This paper attempts to investigate a new unit commitment (UC) problem based on the cost-benefit analysis and here-and-now (HN) approach for optimal sizing of battery banks (BBs) imicrogrids (MGs) with wind power systems. To solve this problem, particle swarm optimization is used to minimize the total cost and maximize the total benefit. In this paper, 12 scenarios have been considered in the presence of BBs and without them in 2 operating modes: 1) stand-alone mode and 2) grid-connected mode. Using the HN approach, the uncertainty of wind power is applied as a constraint in these operating modes. The mathematical formulations related to the HN approach in MGs and its combination in a UC problem are presented in detail for optimal sizing of BBs. Simulation results show that the best sizes of BBs and the scheduling of distributed generations would be entirely different when the accessibility of wind power is taken into consideration by applying HN approach to the proposed probabilistic UC problem.
Keyword:
Battery bank (BB)
distributed generation (DG)
microgrid (MG)
unit commitment (UC)
期刊
IF:
9.9
论文数:
8.6K
被引数:
6.0W
机构
引用论文
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Optimal Dispatch of Electric Vehicles and Wind Power Using Enhanced Particle Swarm Optimization基于改进粒子群算法的电动汽车与风电优化调度

