Miao Di, Hossain Sarmistha
Shenzhen Polytechnic, Shenzhen Polytechnic, Shenzhen, Guangdong, 518055, China.
Chittagong University of Engineering and Technology, Chittagong, 4349, Bangladesh.
ISA Trans. 2020 Jul;102:376-387. doi: 10.1016/j.isatra.2020.02.016. Epub 2020 Feb 15.
Micro-grids consist of distributed power generation systems (DGs), distributed energy storage devices (DSs), and loads. Micro-grids are small-scale networks at low voltage levels that are use to provide thermal and electrical loads of small locations where there is no access to the main electrical grid. Given the environmental and economic issues for these areas, micro-grids can be a good solution for energy production. In this paper, determining the size and location of optimal electrical energy storage systems is presented. In other side, a new method based on the cost benefit analysis for optimal sizing of an energy storage system in a microgrid (MG) is proposed. The uncertainties associated with renewable energy sources and the occurrence of defects in the grid connection network and the effect of the contribution of load responses in a micro-grid are taken into account. The combined system consists of wind turbines and fuel cells. Basically, wind power is not definitively available. The new proposed method is based on two-stage randomization design (TSRD) for modeling the effect of wind power uncertainty so that the predicted wind energy error is considered as the main random parameter in the model. A standard probability distribution function is used to represent the error variations. Given the continuity of the mentioned function, the probability error function is extracted using the new discrete method and a certain number of scenarios with a certain probability. Finally, the problem has been transformed into an optimization problem, and a gray wolf optimization (GWO) algorithm has been used to solve it. In the proposed developed model based on local and global search, the algorithm tries to reach the final result in the shortest possible time and with the most precision. The results of the simulation show the efficiency of the proposed method in solving the micro-grid problem.
微电网由分布式发电系统（DGs）、分布式储能装置（DSs）和负载组成。微电网是低电压等级的小规模网络，用于为无法接入主电网的小区域提供热负荷和电负荷。考虑到这些区域的环境和经济问题，微电网可能是能源生产的一个良好解决方案。本文提出了确定最优电能存储系统的规模和位置的方法。另一方面，提出了一种基于成本效益分析的微电网（MG）储能系统最优规模确定新方法。考虑了与可再生能源相关的不确定性、电网连接网络中故障的发生以及微电网中负载响应贡献的影响。该组合系统由风力涡轮机和燃料电池组成。基本上，风力发电并不确定可用。新提出的方法基于两阶段随机化设计（TSRD）来模拟风力发电不确定性的影响，以便将预测风能误差视为模型中的主要随机参数。使用标准概率分布函数来表示误差变化。鉴于上述函数的连续性，采用新的离散方法并以一定概率提取一定数量的场景来确定概率误差函数。最后，该问题已转化为一个优化问题，并使用灰狼优化（GWO）算法来求解。在所提出的基于局部和全局搜索的模型中，该算法试图在尽可能短的时间内以最高精度达到最终结果。仿真结果表明了所提方法在解决微电网问题方面的有效性。
