OUREL – Optimal Utilization of Renewable Energies in Low Voltage (LV) Power Distribution Systems

OUREL â 低压 (LV) 配电系统中可再生能源的优化利用

• 批准号: 426655646
• 负责人: Professor Dr.-Ing. Christian Becker
• 金额: --
• 依托单位: Institut für Elektrische Energietechnik E-6
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2023-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/426655646?language=en
• 关键词: OUREL; Optimal; Utilization; Renewable; Energies

The increasing amount of distributed renewable energy resources (DER) installed in low voltage power distribution grids (LVDG) imposes new challenges on the grid operation. Load flows will not be predictable anymore and a monitored and managed grid operation will become necessary. Many DER as well as new types of electric loads increase the risk of critical load flows. As the extension of grid capacity is costly and inefficient, new control algorithms are needed to manage the distributed power production and consumption within LVDG, aiming at maximum usage of DER while keeping grid parameters within their limits.Therefore, a utility-based optimization is proposed, a concept that is common practice in com-munication networks, and applied to the problem of determining optimal power generation of DER and consumption of controllable loads within an LVDG. Optimality is understood as maximum utility experienced by producers and consumers. While the optimization algorithm itself shall be ignorant of constraints on grid currents and voltages, it is closely coupled to a corrective power flow module that identifies critical situations and uses sensitivity analysis to propose corrections on single units’ power generation or consumption.At first, a solution of the static problem is implemented at a central place, meaning that power level bounds and producer/consumer utility functions remain constant during the optimization process. This shall demonstrate the applicability of the concept.The final goal is to develop a distributed optimization algorithm under dynamically changing pa-rameters. It shall run at a high update rate, applying incremental power level changes towards the optimum in each time step. A state estimation in distribution grids is employed for identification of the actual grid state. The high update frequency presumably allows for linearized system modelling. The resulting influences on convergence and stability of the optimization algorithm are main questions to be addressed. The distributed nature, which is also well known from communication networks, is expected to increase robustness and ensure scalability while limiting computing demands on single devices. These properties are crucial for reliable and economically efficient operation of a dynamically changing LVDG. At the same time, the distributed approach requires extensive exchange of information between the participants, putting a high burden on the communication network. The performance of the communication network therefore has a crucial impact on the performance of the LVDG optimization algorithm. For the evaluation of the applicability of the distributed algorithm and for the investigation of the overall performance of the proposed utility-based approach, a model of the communication networks is established. This model mainly focuses on the delay distribution functions using mathematical models such as Signal Flow Graphs, Stochastic Network Calculus and Queueing Theory.

随着分布式可再生能源在低压配电网中的安装量不断增加，对电网运行提出了新的挑战。负荷流将不再是可预测的，一个被监控和管理的电网运行将变得必要。许多DER和新型电力负荷增加了临界负荷流的风险。由于电网容量的扩展成本高且效率低，因此需要新的控制算法来管理LVDG内的分布式电力生产和消耗，以最大限度地利用DER，同时使电网参数保持在其限制范围内。因此，提出了一种基于效用的优化方法，这是通信网络中常见的一种概念，并将其应用于确定LVDG内DER的最优发电量和可控负载消耗的问题。最优性被理解为生产者和消费者所经历的最大效用。虽然优化算法本身不需要考虑电网电流和电压的约束，但它与纠偏潮流模块紧密耦合，纠偏潮流模块识别关键情况，并利用灵敏度分析对单机发电或用电提出纠偏。首先，静态问题的解决方案在中心位置实现，这意味着在优化过程中功率水平界限和生产者/消费者效用函数保持不变。这将证明概念的适用性。最终目标是开发动态变化参数下的分布式优化算法。它应以高更新率运行，在每个时间步长中应用增量功率电平变化以达到最佳值。利用配电网的状态估计方法来识别电网的实际状态。高更新频率可能允许线性化系统建模。结果对优化算法的收敛性和稳定性的影响是需要解决的主要问题。在通信网络中众所周知的分布式特性有望增加健壮性并确保可伸缩性，同时限制对单个设备的计算需求。这些特性对于动态变化的LVDG的可靠和经济高效运行至关重要。同时，分布式方法需要参与者之间进行大量的信息交换，这给通信网络带来了很大的负担。因此，通信网络的性能对LVDG优化算法的性能有着至关重要的影响。为了评估分布式算法的适用性和研究基于效用的方法的整体性能，建立了通信网络的模型。该模型主要利用信号流图、随机网络演算和排队论等数学模型来研究时延分布函数。