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Effects of resilience-oriented design on distribution networks operation planning

机译:以集性为导向设计对分销网络运营规划的影响

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This paper presents an optimal framework for the resilience-oriented design (ROD) in distribution networks to protect these grids against extreme weather events such as earthquakes and floods. This strategy minimizes the summation of daily investment and repair costs of back up distributed generation (DG), hardening and tie lines, operation cost of network and DGs, and load shedding cost. Also, it considers AC power flow equations, system operation limits and planning and reconfiguration constraints. This problem is generally a mixed integer nonlinear programming (MINLP) problem, but it is converted to a mixed integer linear programming (MILP) problem to achieve a globally optimal solution with a low computation time. Moreover, the Benders decomposition (BD) approach is used for the proposed problem to obtain higher computation speed in large scale networks. In addition, this problem includes uncertain parameters such as load, energy price, and availability of network equipment in the case of extreme weather conditions. Hence, a scenario-based stochastic programming (SBSP) approach is used to model these uncertain parameters in the proposed ROD method, based on a hybrid approach, including roulette wheel mechanism (RWM) and the simultaneous backward method. The proposed problem is simulated on 33-bus and large-scale 119-bus distribution networks to prove its capabilities in different case studies.
机译:本文为配送网络中的可弹性导向设计(ROD)提供了一种最佳框架,以保护这些网格免受地震和洪水等极端天气事件。该策略最大限度地减少了日常投资和维修成本的总和,备份分布式发电(DG),硬化和系带,网络和DGS的运营成本,以及负载脱落成本。此外,它考虑了交流电流方程,系统操作限制和规划和重新配置约束。这个问题通常是混合整数非线性编程(MINLP)问题,但它被转换为混合整数线性编程(MILP)问题,以实现具有低计算时间的全局最佳解决方案。此外,弯曲器分解(BD)方法用于提出的问题,以获得大规模网络中的更高的计算速度。此外,此问题包括在极端天气条件的情况下的负载,能源价格和网络设备的可用性等不确定参数。因此,基于混合方法,包括轮盘键机构(RWM)和同时向后方法,用于在所提出的杆方法中模拟这些不确定参数的模拟这些不确定参数。建议的问题是在33总线和大型119母线配送网络上模拟,以证明其在不同案例研究中的能力。

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