Abstract
The aim and challenge of this research project is to define and qualify an innovative distributed measurement system for proper, effective, and efficient implementation of innovative applications in a modern electrical distribution Smart Grid (SG) aimed at increasing the use of renewable energy and handling resources such as distributed generation, storage systems, electric vehicles, etc.. In this context, the starting concept of the project is that any operation that can be defined as "intelligent" has as a necessary starting concept prerequisite an adequate knowledge of the system involved in that operation. The driving idea is that the huge amount of available from the measurement/estimation of both electrical and non-electrical quantities should be translated into actual, which means they have to be accompanied by an indication about their information quality, so that proper risk-based decisional rules can be adopted. The approach that will be followed involves a rigorous research work focused on measurements, which analyzes all aspects of the system in an integrated way: from individual voltage and current sensors to the overall system, from the algorithm for measuring a single quantity (for example, the synchrophasor or the harmonic synchrophasor) to the state estimation procedure, from the metrological characterization of a single device to the propagation of uncertainties. In particular, an innovative coordinated approach is proposed to make the measurement system able to self-detect its weak points and self-compensate their effects, in order to continuously improve its performance. The structure of the project consists of three Work Packages (WPs). - WP1 introduces advanced methods for estimating and optimizing the information quality provided by the individual components of the measurement system (instrument transformers, synchronized measurement devices, pseudo-measurements, etc.) both in the initial metrological characterization and over time. - WP2 assesses the combined impact of the uncertainty sources considered in WP1 on state estimation procedures and then faces probably the most ambitious goal of the project, which is the study of techniques for the self-identification of measurement issues in the system and for their compensation, thus allowing a continuous and adaptive improvement of the metrological performance. - WP3 analyzes, through both simulations and experimental tests, the benefits of the proposed solutions on major applications for SGs. The strengths of the project are complementarity and integration between the specialized competences owned by the involved strengths research units, as well as its substantial impact on the feasibility of innovative SG management paradigms. Results University of Bologna worked extensively on the quality of information from instrumentation installed in MV substations to predict specific grid stress conditions, such as increased power requirements, and to verify the operation of both voltage and current instrument transformers for metrological confirmation. Artificial intelligence algorithms were used to generate dynamic and adaptive models of grid load profiles to mitigate the effects of congestion and overload conditions. Furthermore, advanced test methods were synthesized and experimentally verified for the characterization of instrument transformers, both in terms of linearity in amplitude, frequency, and in relation to the applied load, as well as dynamic characteristics, such as the response to rapid variations in voltage and current or in the presence of frequency components non-multiple of the fundamental frequency (quasi-periodic signals), which are very common in electricity distribution networks with high penetration of renewable and distributed energy sources. The main outcome of the study for the characterization of instrument transformers was the identification of the most significant systematic effects introduced by these devices. This information was shared and used by colleagues of Units involved in estimating the state of the network to include adequate compensation for such systematic effects, based on a parametric or non-parametric models. An intensive research effort was also launched to verify the quality and accuracy of measurements made by using quantities provided by instrument transformers affected by stability phenomena, both short- and long-term. Initially, a study was carried out to select the most important quantities that influence the metrological performance of instrument transformers, with particular reference to temperature, humidity, and electromagnetic fields at nominal frequency. Subsequently, the focus was on studying aging phenomena in the materials used in instrument transformers, which directly influence and affect the stability of long-term accuracy. This allowed us to classify instrument transformers and therefore define quality parameters. Finally, Bologna Unit coordinated work to improve grid monitoring and diagnostics capabilities, with particular reference to the study on inertia estimation. The increase in renewable electricity sources installed on the grid has introduced a new challenge for grid operators: the substantial reduction of grid inertia. In electricity grids with high renewable energy penetration (particularly 50% or greater), this has led to a progressive reduction in the use of rotating machinery for electricity generation. This has led to a different definition of grid inertia, no longer based on the mechanical power of generators, as well as the electrical power, but on the real-time capacity of renewable energy generation plants (solar and wind in particular) to provide the necessary power in specific areas or portions of the grid (virtual inertia). The study primarily focused on determining the target accuracy for instrument transformers to enable accurate inertia estimates, thus enabling grid operators to actively control grid energy sources to correct inertia imbalances. These research activities led to experimental work on the e-distribuzione network in the Piemonte region, where 19 PMUs have been installed. A measurement campaign is currently underway, with data collection that will serve both to verify the propagation of measurement uncertainties due to instrument transformer errors (both voltage and current) and to estimate grid inertia. The results of the measurement campaign will be published at conferences and journals scheduled for 2026. University of Bologna has actively worked to disseminate the research results through the organization of the IEEE Applied Measurements for Power Systems Workshop, 2023-2024-2025 editions, and publication in indexed journals.
Project details
Unibo Team Leader: Lorenzo Peretto
Unibo involved Department/s:
Dipartimento di Ingegneria dell'Energia Elettrica e dell'Informazione "Guglielmo Marconi"
Coordinator:
Università degli Studi di CAGLIARI(Italy)
Total Unibo Contribution: Euro (EUR) 70.880,00
Project Duration in months: 24
Start Date:
28/09/2023
End Date:
28/02/2026
