Regulatory issues in the deployment of distributed storage devices in distribution networks

2016 ◽  
Author(s):  
Ricardo Ferreira ◽  
Manuel Matos ◽  
Joao Pecas Lopes
Keyword(s):  
Distributed Storage ◽  
Distribution Networks ◽  
Regulatory Issues ◽  
Storage Devices

scholarly journals Optimal Energy Storage System Positioning and Sizing with Robust Optimization

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 512 ◽  
Author(s):  
Nayeem Chowdhury ◽  
Fabrizio Pilo ◽  
Giuditta Pisano
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Robust Optimization ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Distributed Storage ◽  
Distribution Networks ◽  
Fine Tuning ◽  
Optimal Placement ◽  
Storage Devices

Energy storage systems can improve the uncertainty and variability related to renewable energy sources such as wind and solar create in power systems. Aside from applications such as frequency regulation, time-based arbitrage, or the provision of the reserve, where the placement of storage devices is not particularly significant, distributed storage could also be used to improve congestions in the distribution networks. In such cases, the optimal placement of this distributed storage is vital for making a cost-effective investment. Furthermore, the now reached massive spread of distributed renewable energy resources in distribution systems, intrinsically uncertain and non-programmable, together with the new trends in the electric demand, often unpredictable, require a paradigm change in grid planning for properly lead with the uncertainty sources and the distribution system operators (DSO) should learn to support such change. This paper considers the DSO perspective by proposing a methodology for energy storage placement in the distribution networks in which robust optimization accommodates system uncertainty. The proposed method calls for the use of a multi-period convex AC-optimal power flow (AC-OPF), ensuring a reliable planning solution. Wind, photovoltaic (PV), and load uncertainties are modeled as symmetric and bounded variables with the flexibility to modulate the robustness of the model. A case study based on real distribution network information allows the illustration and discussion of the properties of the model. An important observation is that the method enables the system operator to integrate energy storage devices by fine-tuning the level of robustness it willing to consider, and that is incremental with the level of protection. However, the algorithm grows more complex as the system robustness increases and, thus, it requires higher computational effort.

scholarly journals Supporting SLA via Adaptive Mapping and Heterogeneous Storage Devices in Ceph

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 847
Author(s):  
Sopanhapich Chum ◽  
Heekwon Park ◽  
Jongmoo Choi
Keyword(s):  
Positive Impact ◽  
Distributed Storage ◽  
Storage System ◽  
Hard Disk Drives ◽  
Service Level Agreement ◽  
Service Level ◽  
Cost Ratio ◽  
Solid State Drives ◽  
Storage Devices ◽  
Management Scheme

This paper proposes a new resource management scheme that supports SLA (Service-Level Agreement) in a bigdata distributed storage system. Basically, it makes use of two mapping modes, isolated mode and shared mode, in an adaptive manner. In specific, to ensure different QoS (Quality of Service) requirements among clients, it isolates storage devices so that urgent clients are not interfered by normal clients. When there is no urgent client, it switches to the shared mode so that normal clients can access all storage devices, thus achieving full performance. To provide this adaptability effectively, it devises two techniques, called logical cluster and normal inclusion. In addition, this paper explores how to exploit heterogeneous storage devices, HDDs (Hard Disk Drives) and SSDs (Solid State Drives), to support SLA. It examines two use cases and observes that separating data and metadata into different devices gives a positive impact on the performance per cost ratio. Real implementation-based evaluation results show that this proposal can satisfy the requirements of diverse clients and can provide better performance compared with a fixed mapping-based scheme.

scholarly journals Predictive Voltage Control: Empowering Domestic Customers With a Key Role in the Active Management of LV Networks

2020 ◽  
Vol 10 (7) ◽  
pp. 2635
Author(s):  
Micael Simões ◽  
André G. Madureira
Keyword(s):  
Distribution System ◽  
Smart Grids ◽  
Low Voltage ◽  
Voltage Control ◽  
Distribution Networks ◽  
Active Management ◽  
Storage Devices ◽  
Home Energy Management ◽  
System Operator ◽  
Home Energy Management System

In order to avoid voltage problems derived from the connection of large amounts of renewable-based generation to the electrical distribution system, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in Low Voltage (LV) distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional resources from the Distribution System Operator (DSO), such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm—the Low Voltage Control (LVC)—is detailed in this paper. The algorithm was tested through simulation using a real Portuguese LV network and real consumption and generation data, in order to evaluate its performance in preparation for a field-trial validation in a Portuguese smart grids pilot.

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