Risk-Averse Scheduling via Conservation Voltage Reduction in Unbalanced Distribution Feeders

Mohammad MansourLakouraj, H. Livani, M. Benidris
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引用次数: 2

Abstract

The increasing penetration of solar photovoltaics (PVs) generation in distribution grids necessitates the need for optimal operation and scheduling of active/reactive resources for regulating the voltage along distribution feeders and reducing power consumption. In this paper, a mixed integer linear programming (MILP) risk-averse stochastic optimization model is proposed to co-optimize the traditional switching of capacitor banks and transformer tap along with PV and energy storage system (ESS) inverters. In day-ahead (DA) stage, traditional devices and purchased power of DA are scheduled. In real-time stage, the fast response inverters, ESS, and real-time market ensure sufficient active and reactive power support for distribution grids considering the conservation voltage reduction (CVR) plan. The CVR is integrated with the framework to reduce the energy consumption of voltage dependent loads by operating the grid close to the lower acceptable voltage ranges. The uncertainty of sudden changes in PV generation is represented by a Gaussian Mixture model (GMM). The generated uncertainty scenarios are reduced using an unsupervised fuzzy k-means method. Finally, the effectiveness of the proposed framework is verified using a modified version of the unbalanced IEEE 33-node system.
不平衡配电馈线电压守恒降低的风险规避调度
随着太阳能光伏发电在配电网中的普及程度不断提高,需要对有功/无功资源进行优化运行和调度,以调节配电馈线沿线的电压,降低电力消耗。本文提出了一种混合整数线性规划(MILP)风险规避随机优化模型,用于光伏和储能系统(ESS)逆变器与电容器组和变压器抽头的传统开关协同优化。在日前(DA)阶段,对DA的传统器件和购买功率进行调度。在实时阶段,快速响应的逆变器、ESS和实时市场保证了配电网有足够的有功和无功支持,以考虑保护电压降低(CVR)计划。CVR与框架集成,通过运行接近较低可接受电压范围的电网来减少电压相关负载的能耗。光伏发电突变的不确定性用高斯混合模型(GMM)表示。生成的不确定性场景使用无监督模糊k-means方法减少。最后,使用改进版本的非平衡IEEE 33节点系统验证了所提框架的有效性。
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