Andrea Benigni

A Parallel Approach to Real-Time Simulation of Power Electronics Systems

We define here a new parallel simulation method designed for real-time execution. This method is highly parallelizable and scalable, and the simulation execution time is fully predictable, which is very important for real-time execution. The stability conditions for the method are defined. Furthermore, we show how to define appropriate flow variable injections so that this method can be extended to multiphysic applications and how to implement multirate time step in the defined method. Finally, we present simulation tests that validate the presented method.

New monitoring approach for distribution systems

This paper introduces a new data-driven bottom-up monitoring approach for distribution systems. Unlike model-based techniques, which require a given number of measurement inputs for their state estimation equations, this approach uses an artificial neural network to directly estimate the voltages. Thus, the process does not use state estimation equations and is flexible with regard to the number of required measurements. Depending on the available measurements, the estimation accuracy may vary but there are no convergence issues. Furthermore, rather than performing voltage estimations for the entire system in a single step, this approach uses a hierarchical, bottom-up structure to build up the overall picture. More precisely, the estimations performed at the MV/LV substations are communicated to the upper-level HV/MV substation, contributing to more accurate voltage estimation at MV level. The estimation process is computationally simple and can be executed on low-cost hardware, as demonstrated in this work. In our test, BeagleBone Black was used for implementing the developed algorithm. Preliminary results are presented which show representative estimations in an LV feeder.

A Decentralized Observer for Electrical Power Systems: Implementation and Experimental Validation

In the last few years the growing in complexity of the electrical power networks, mainly due to the increased use of electronic converters together with the requirements of higher level of reliability and security, pushed the development of new techniques for the state estimation of the power systems. In this paper, the author focus their attention on the implementation and experimental validation of a decentralized observer for the state estimation in an electric ship, whose power network is characterized by fast dynamics and by the presence of many electronic devices. The proposed solution implements a Decentralized Information Filter(DIF).

A Scalable Data-Driven Monitoring Approach for Distribution Systems

This paper introduces a new data-driven bottom-up monitoring approach for distribution systems. In this approach, local estimations of the subsections into which the system is split are performed independently, thus leading to a scalable architecture. The monitoring approach is focused only on the estimation of voltage magnitude rather than the complete state of the system. This reduces the measurement requirements significantly, thus addressing economical and technical concerns for existing systems, while staying open to accommodating further incremental improvements in the available data and data quality. The estimation of each section is realized via an artificial neural network (ANN), for which a set of parameterizations is available to cope with different operating conditions. The estimation convergence is achieved even with relatively few measurements, although accuracy varies depending on the available measurements. At the Medium Voltage (MV) level, where reconfiguration is common, a configuration identification unit chooses the right ANN, the one trained for the actual network configuration. The estimation process is computationally simple and can be executed on low-cost hardware, as demonstrated in this paper by the implementation on a BeagleBone Black board. To demonstrate the concept, a prototype and a laboratory setup have been developed. The experimental test results are presented both for an Low Voltage distribution system and an MV distribution system.

Development of a simulator-to-simulator interface for geographically distributed simulation of power systems in real time

The geographically distributed simulation concept enables connecting laboratories over long distances with the goal of sharing simulation resources and integrating multiple (Power) Hardware-in-the-Loop setups. The main obstacle in applying this concept is the impact of the communication medium on fidelity and stability of the simulation. This paper presents advantages and challenges of developing a simulator-to-simulator interface based on the time-frequency representation of interface quantities. The proposed approach is first analyzed using a simple electrical circuit as case study, and then conclusions are verified on a larger system including voltage-source converters that realize a high-voltage dc point-to-point link which connects two ac systems. To assess the approach in a realistic framework, an Internet-distributed simulation platform that integrates two remote real-time digital simulators, OPAL-RT (located at University of South Carolina, USA) and OPAL-RT (located at RWTH Aachen University, Germany) is developed and both linear and nonlinear system models are simulated.

Cloud-based IoT solution for state estimation in smart grids: Exploiting virtualization and edge-intelligence technologies

Abstract Smart Grids (SGs) are expected to be equipped with a number of smart devices able to generate vast amounts of data about the network status, becoming the key components for an efficient State Estimation (SE) of complex grids. To exploit their potentials, the ICT infrastructure needs to be scalable to follow the increasing amount of data flows and flexible to give the possibility to assign and re-assign grid functions and data flow control policies at runtime, possibly in a context-aware manner. In this scenario, this paper proposes and validates a Cloud-IoT-based architectural solution for SE in SG that combines cloud-capabilities and edge-computing advantages and uses virtualization technologies to decouple the handling of measurement data from the underlying physical devices. Case studies in the field of distribution networks monitoring are also analyzed, demonstrating that the proposed architecture is capable to accomplish the assigned operational tasks, while satisfying the needed quality level from both the communication and the grid perspectives with a significant degree of flexibility and adaptability with respect to state of the art solutions.

An embedded solution for multi-agent control of PEBB based power electronic systems

This paper presents a hardware solution for embedding multi-agent controls of PEBB based power electronics systems. The architecture of the proposed solution is presented here together with the experimental results of Hardware in the Loop testing of a prototype. Validation of both power and communication characteristics has been addressed. The test case consists of the voltage control of a radial distribution feeder with three distributed energy resources.

Day-ahead optimal scheduling of PV inverters and OLTC in distribution feeders

In this paper, we present a day-ahead optimal scheduling for reactive power of PV inverters and tap position of on-load tap changer (OLTC) in distribution network. We used a pattern search optimization algorithm based on the forecasted load demand and PVs active power generation. While the objective is to minimize the node voltage deviation and network losses, the maximum number of tap operation is maintained in a predefined limit. A modified IEEE 34 node test feeder is used to demonstrate the applicability and effectiveness of the proposed scheduling approach. A stochastic analysis is presented to show the performance of the proposed optimal scheduling in the presence of forecast errors of the PV generation and load demand.

A smart PV inverter controller with PMU capability

This paper introduces the control of a photovoltaic (PV) interface converter ready to offer auxiliary service - reactive power control - that also has Phasor Measurement Unit capability. A prototype of the controller is implemented using a National Instruments Compact RIO and tested using Hardware In the Loop techniques. Experimental results demonstrate the converter functionalities.

System-Level, FPGA-Based, Real-Time Simulation of Ship Power Systems

In this paper, we present a scalable approach for real-time simulation of ship power systems with high-frequency power electronics converters (100–200 kHz). The proposed approach is based on the latency-based linear multistep compound method and relies on field-programmable gate array (FPGA) execution. Several examples of increasing dimension and complexity are used to evaluate the scalability—both of in terms of computational delay and of resources usage—of the proposed approach. Real-time execution with a 50 ns time step is achieved for all the examples considered.