Real-Time State Estimation of the EPFL-Campus Medium-Voltage Grid by Using PMUs

We describe the real-time monitoring infrastructure of the smart-grid pilot on the EPFL campus. We experimentally validate the concept of a real-time state-estimation for a 20 kV active distribution network. We designed and put into operation the whole infrastructure composed by the following main elements: (1) dedicated PMUs connected on the medium-voltage side of the network secondary substations by means of specific current/voltage transducers; (2) a dedicated communication network engineered to support stringent time limits and (3) an innovative state estimation process for real-time monitoring that incorporates phasor-data concentration and state estimation processes. Special care was taken to make the whole chain resilient to cyber-attacks, equipment failures and power outages. The achieved latency is within 65ms. The refresh rate of the estimated state is 20ms. The real-time visualization of the state estimator output is made publicly available, as well as the historical data (PMU measurements and estimated states). To the best of our knowledge, the work presented here is the first operational system that provides low-latency real-time state estimation by using PMU measurements of a real active distribution network

A unified control strategy for active distribution networks via demand response and distributed energy storage systems

AbstractAs part of the transition to a future power grid, distribution systems are undergoing profound changes evolving into Active Distribution Networks (ADNs). The presence of dispersed generation, local storage systems and responsive loads in these systems incurs severe impacts on planning and operational procedures. This paper focuses on the compelling problem of optimal operation and control of ADNs, with particular reference to voltage regulation and lines congestion management. We identify the main challenges and opportunities related to ADNs control and we discuss recent advances in this area. Finally, we describe a broadcast-based unified control algorithm designed to provide ancillary services to the grid by a seamless control of heterogeneous energy resources such as distributed storage systems and demand-responsive loads

Lifetime Control of Modular Smart Transformers Considering the Maintenance Schedule

Smart Transformers (ST) are power electronic transformers capable of providing grid services and DC connectivity compared to conventional low-frequency transformers. However, failure of the components and consequent maintenance is one of the major challenges compared to it's counterpart, limiting its application. By controlling the power flowing through the cells in a modular ST architecture, the remaining lifetime of these cells can be controlled. The idea is to schedule the maintenance by actively controlling the lifetime of the individual cells using an optimization algorithm. The proposed algorithm has the ability to schedule the maintenances according to predefined maintenance intervals. A potential ST architecture consisting of Cascaded H-bridge (CHB) and Dual-Active Bridge (DAB) converters are analyzed with simulations and experiments to validate the proposed power routing algorithm and its impact on the lifetime and maintenance scheduling

Assessment of Battery Ageing and Implementation of an Ageing Aware Control Strategy for a Load Leveling Application of a Lithium Titanate Battery Energy Storage System

The manuscript describes a method to embed into a battery energy storage system (BESS) control strategy the performance degradation associated with the battery operation. In particular, the proposed method aims at minimizing the degra- dation of the BESS electrochemical cells. A load leveling strategy is described as a case study and the ageing effects associated with the battery current extraction are embedded as constraints into the optimization problem. The main contributions of the work, compared to the existing literature are: i) the degradation process is formulated as a weighted energy throughput, thus taking into account the C-rate effect on the degradation phenomena; ii) the performance of the proposed control strategy has been applied to a large scale lithium-titanate BESS of 280 kWh interfaced to a 20 kV active distribution network

Improving distribution network model accuracy using impedance estimation from micro-synchrophasor data

An accurate network model is essential for performing detailed analysis of a power system. The quality of many distribution network models is very diverse, especially for low voltage (LV) networks. To help identify areas where the model is incomplete or incorrect, Micro Phasor Measurement Units (μPMUs) can be integrated into a network. These μPMUs would work together, with a trusted cloud back-end system. The basis for this paper is to determine how the data collected by μPMUs can be used, and what can be calculated from this data to help recognize areas where the network model is inaccurate and may need resurveyed. As a preliminary investigation to determine the feasibility of the approach, this paper discusses the calculation of the impedance of both a transformer and line, and compares the values obtained from μPMU data to the level of value expected on the network