ELECTRIMACS 2022

Inhaltsverzeichnis

1. Microgrids and Smart Grids

   1. Frontmatter

   2. A Distributed Secondary Control for Autonomous AC Microgrid Based on Photovoltaic and Energy Storage Systems

      Sidlawendé V. M. Ouoba, Azeddine Houari, Mohamed Machmoum

      Abstract

      In this paper, a distributed control is proposed for Distributed Energy Storage Systems (DESSs) and Renewable Energy Sources (RESs) power management in islanded Microgrid (MG). The power management strategy is designed to maintain generation/consumption balance, to ensure State of Charge (SoC) balancing of the DESSs and MG frequency/voltage (f & V) regulation. A fully distributed control without leader-follower strategy is used to manage the power flow between renewable generators, energy storage and consumption (critical and non-critical loads), to balance the SoC of the DESSs and to restore the frequency and voltage to their nominal value only thanks to low bandwidth communication. The strategy framework of the power management set the islanded MG in 04 operations modes (normal mode, PV active power curtailment mode and load shedding and reconnection mode) in order to provide a high quality and reliable power source in the islanded MG. A MATLAB/Simulink simulation is performed with a system of two Batteries Energy Storage Systems (BESSs), three loads (a critical/variable load and two non-critical/constant loads) and photovoltaic (PV) generator, in order to verify the effectiveness and the resilience of the proposed power management method in several operation modes.

   3. Behavioural Modelling of Multi-MW Hybrid PV/Diesel Modular Power Plant

      Sani Moussa Kadri, Brayima Dakyo, Mamadou Baïlo Camara, Yrébégnan Moussa Soro

      Abstract

      This paper deals with the behavioural modelling of a multi-MW PV/Diesel hybrid power plant based on long term monitoring over years. The approach is based on the analysis of production data correlated with solar resources and fuel consumption. The links between PV power and irradiance at different points of energy conversion chain up to the AC point of common coupling are carried out. The adopted methodology is to proceed to a formulation of the behavioural model of PV production considering trends and statistics observations. The first step was data classification targeting causalities and consequences of main disturbances. The second step validates the established models with operating data. The aim is to provide relevant set for scenarios simulation that allows optimal design and energy management for such hybrid plant.

   4. Simulation and Operation Analysis of a Smart Grid Using Simulink

      Alexander Van Waeyenberge, Bruno Canizes, João Soares, Sérgio Ramos, Simon Ravyts, Juliana Chavez, Zita Vale

      Abstract

      Changes will be required to handle the increased power flow in the network as the distribution infrastructure ages and the number of EVs and renewable grows. Designing and operating an intelligent network that reacts to changing power flows to ensure the optimal operation is the most economical option than fortifying the network with heavier cables. This work aims to build a model of a 13 bus medium voltage distribution network with high penetration of distributed energy resources and use it to analyze network conditions. The MATLAB Simulink software is used to model and evaluate the network. The outcomes suggest the model is promising and valid even when renewable generation is at low levels.

   5. Modelling and Optimization of Power Allocation and Benefit Sharing in a Local Energy Community

      Alyssa Diva Mustika, Rémy Rigo-Mariani, Vincent Debusschere, Amaury Pachurka

      Abstract

      This paper proposes a strategy for the resources management and power allocation in an energy community. Especially, the fairness of the benefit sharing is assessed thanks to a metric introduced as a monthly net energy price (in c€/kWh) from the viewpoint of each individual and computed as the individual bill over the consumed energy. The community management decouples the operational (i.e., power dispatch) from the settlement phase (i.e., monthly community billing). In particular, the investigated billing approach is based on an optimization process with an additional constraint to limit the gap between the maximum and minimum identified prices over all the community members. This study then provides a new method to better address individual’s need in the community. The results show a narrow range of the individual energy price and 11.5% collective bill reduction compared to a case where the members act individually.

   6. Social Data to Enhance Typical Consumer Energy Profile Estimation on a National Level

      Amr Alyafi, Pierre Cauchois, Benoit Delinchant, Alain Berges

      Abstract

      Since the electrical grid creation, assessing the electricity demand is essential as we need to match the energy production/demand at all times. Load analysis is essential in improving the reliability and efficiency of the grid. Beside regular human activities, the main impact factor which explains consumption variations is the outside temperature. But there are still unpredictable variations that are mainly coming from arising social events. To build a better understanding of these variations, this work will focus on how to detect these events from social media and how to quantify their impact on residential and professional typical profiles for energy demand.

   7. Small Signal Stability Study for Island Distributed Generation System Controlled by IDA-PBC-IA and Power Decoupled Droop Control

      Nidhal Khefifi, Azeddine Houari, Mohamed Machmoum, Malek Ghanes, Mehdi Zadeh

      Abstract

      The supply of electricity to remote areas such as islands or rural areas presents many challenges. To reduce costs, the use of renewable energy resources is recommended. In these circumstances, it is always important to improve the power quality in terms of waveform and power sharing between different distributed generators. In this paper, we focus on the power sharing between different distributed generators, and for this purpose, an improved decoupled control, proposed in our previous work, is studied to prove its effectiveness in providing wide range of stability. The internal control has been assimilated to a second-order filter and then, the improved decoupled control is studied to prove its effectiveness to ensure a wide range of stability. For this purpose, a microgrid composed of two distributed generators is studied. Its small-signal model including the distributed generators, the loads and the droop control laws that ensure the interconnection between the generators is revealed. A stability study in the sense of the indirect Lyapunov theory based on the evaluation of the eigenvalues of the system is performed to show the “local stability” in presence of different types of loads, the impact of the system and the control parameters on the eigenvalue is studied using the modal analysis technique. The validation of these results is proven by simulation

   8. MANA-Based Load-Flow Solution for Bipolar DC Microgrids

      Nasim Rashidirad, Jean Mahseredjian, Ilhan Kocar, Omar Saad

      Abstract

      In this paper, a novel load-flow method for unbalanced bipolar dc microgrids (BDCMGs) is presented. The principles of this method are based on the modified augmented nodal analysis (MANA) formulation, which is generic and simple to formulate. An unbalanced BDCMG is also used to verify the validity of the proposed MANA-based formulation. The findings also substantiate that in BDCMGs, different connections of DGs can highly affect the bipolar voltage profiles, in presence of different line resistances and droop coefficients.

   9. Analysis and Assessment of a Commercial Microgrid Laboratory Platform

      Mariem Dellaly, Sonia Moussa, Sondes Skander-Mustapha, Ilhem Slama-Belkhodja

      Abstract

      The growth of residential rooftop solar PV has given rise to new operating concepts such as collective solar self-consumption where several prosumers come together to form a microgrid with its distributed PV generations, its storage systems, its local loads with an energy management system (EMS) to optimize the operation modes according to desired criteria. Such microgrid working is relatively complex and adapting the EMS of a commercial microgrid to meet national standards and regulations or to perform deep investigations requires first analysis and assessments. This paper deals with a commercial microgrid laboratory platform. Tests and data analysis are performed to establish the flowchart of its central EMS, and then, in a future work, to develop an accurate model of the platform to test new investigated EMS.

   10. A Review of Frequency Control Techniques Using Artificial Neural Network for Urban Microgrid Applications

       Louise Petit, Bruno Francois

       Abstract

       The increasing penetration of intermittent Renewable Energy Sources (RES) induces more instability of the grid and constraints on the Energy Management (EM). Microgrids (MG) are more and more experimented to better implement local flexibilities for dynamically balancing the production and load demand inside a specific area as districts of a city, as example. New solutions like Artificial Intelligence (AI) and Artificial Neural Networks (ANN) are being developed in order to improve the real-time energy management. Specifically this paper deals with the operational management of energy resources via the tuning of the frequency control parameters to satisfy the load demand. A non-exhaustive review of ANN techniques for enhancing the frequency control in microgrids is proposed. ANN techniques are shown to be performing better than other AI techniques on the specific cases reported here.

   11. Stator Interturn Short-Circuits Detection in the PMSM Drive by Using Current Symmetrical Components and Selected Machine Learning Algorithms

       Przemyslaw Pietrzak, Marcin Wolkiewicz

       Abstract

       The fault diagnosis of Permanent Magnet Synchronous Motors (PMSMs) has been the subject of much research in recent days. This is due to the growing safety and reliability requirements for drive systems. This paper concerns detection and classification of the PMSM stator interturn short-circuits (ITSC) by using selected machine learning algorithms. The spectral analysis of symmetrical current components is applied for ITSC symptom extraction. The utilized and compared algorithms are K-Nearest Neighbours (KNN), Support Vector Machine (SVM), Naive Bayes (NB) and Multilayer Perceptron (MLP). Experimental results confirm that the use of the KNN, SVM and MLP classifiers allows for ITSC detection with high effectiveness. The most effective is KNN, which is simple to implement and not computationally complex.

2. Energy Storage Systems

   1. Frontmatter

   2. Potential Operation of Battery Systems to Provide Automatic Frequency Reserve Restoration (aFRR) Service

      J. Cardo-Miota, E. Pérez, H. Beltran

      Abstract

      As a consequence of the enormous growth being experienced by renewable energy systems (RES), conventional technologies such as coal or gas, which unlike RES are dispatchable, are reducing their participation in energy markets, increasing the instability of the electric energy systems. Therefore, there is a need for RES or other converter-based technologies to replace the traditional ancillary service providers. In this sense, battery energy storage systems (BESS) are considered the best candidates. This paper defines a model to simulate the Spanish Automatic Generation Control (AGC). This simulator is used to provide inputs to the operation of a BESS that participates in the secondary frequency regulation market and in the continuous intraday energy market. Subsequently, the paper introduces an economic feasibility study to determine the best BESS size to operate simultaneously in both markets. The results obtained show that BESS with energy capacities of 2 h are the best option (from both a technical and an economic point of view) to be part of a regulation zone.

   3. Incremental Capacity Analysis as a Diagnostic Method Applied to Second Life Li-ion Batteries

      Lucas Albuquerque, Fabien Lacressonnière, Xavier Roboam, Christophe Forgez

      Abstract

      This work is inserted in the context of second life Li-ion batteries: for such storage devices, their first life characteristics are unknown and a simple capacity measurement might not be sufficient to fully characterize and get it ready for its second life. The Incremental Capacity Analysis (ICA) was used in this study to give a more intimate diagnosis of the batteries’ Degradation Modes (DMs), providing a link with physical degradation phenomena. This method was applied to a lithium-ion battery module (NMC/Graphite) which was used in an electrical vehicle and to a single cell from a similar module in order to verify its potential use in this context. Both IC curves were then compared to a DM simulation using the ′Alawa software, capable of simulating different ageing phenomena and their effects on the IC curves. Moreover, this work gives an intrinsic view and explanation of the IC signature for the mentioned battery technology.

   4. A Li-Ion Battery Charger with Embedded Signal Generator for On-Board Electrochemical Impedance Spectroscopy

      Luigi Mattia, Giovanni Petrone, Walter Zamboni

      Abstract

      The development of a battery monitoring system is one of main tasks for applications needing an efficient and well-designed battery storage system. In this framework, a fast, on-board, non-invasive and low-cost diagnosis system has a primary importance. Among the large number of diagnosis techniques, the Electrochemical Impedance Spectroscopy (EIS) is one of the most powerful. It allows one to extract information about the overall state of an electrochemical cell by stimulating it with current or voltage signals with appropriate shapes and frequency. In this work, we present the changes made to a commercial Lithium-ion battery charger to implement a system for the generation of EIS stimuli, preserving large part of the native functions of the battery charger. The stimulation functions are implemented using a field-programmable gate array (FPGA) board, which ensures a good voltage resolution and an optimal frequency range for this kind of applications.

   5. A Survey of Energy Management Systems Considering Battery State of Health Preservation in Microgrid Applications

      Maria Carmela Di Piazza, Massimiliano Luna, Giuseppe La Tona

      Abstract

      Electrochemical storage systems play an increasingly central role in microgrids, providing several services which allow for more flexible and reliable operation. Lifetime of battery storage systems is a critical aspect to consider for their sustainable and cost-effective employment. In this paper a survey of energy management systems (EMSs) designed to contribute to battery lifetime extension is presented. To pursue this objective, the design of EMSs must rely on suitable battery degradation models, the most significant of which have been retrieved from the technical literature and described as well.

   6. Impedance Modeling for Multichannel EIS in Industrial Scale Vanadium Redox Flow Batteries

      Andrea Trovò, Walter Zamboni, Massimi Guarnieri

      Abstract

      The work provides early results obtained with a multichannel EIS system, which were used to identify an equivalent circuit of an Industrial Scale Vanadium Redox Flow Battery (IS-VRFB) stack with a rated power/energy of 9 kW/27 kWh. The single cell impedance is represented with three different models, including a series resistance and an RC loop (RRC model), or a constant phase element (CPE) loop (a ZARC element), or a ZARC element including also a Warburg impedance. The inclusion of the CPE constitutes a substantial improvement in the fit. Conversely, the addition of the Warburg element, which aims to model the mass transfer in the electrochemical process, does not produce significant effects for the frequencies at which we have experimental data. This numerical results are validated against EIS measurements taken on IS-VRFB. Very few analyses of this type are reported in the literature for such batteries. This study set the stage for developing advanced online State of Health (SOH) management for IS-VRFB.

   7. Numerical Assessment of Cooling Systems for Thermal Management of Lithium-Ion Batteries

      Girolama Airò Farulla, Davide Aloisio, Valeria Palomba, Andrea Frazzica, Giovanni Brunaccini, Francesco Sergi

      Abstract

      Lithium-ion batteries have the advantages of high energy density, high charge-discharge efficiency, low self-discharge effect and long cycle life that make them suitable in both stationary and mobile applications. They are the most widely used solution in the field of electric vehicles and are increasing their application for stationary applications. Both the life-time and performances are negatively affected by high temperatures so the prevision of the thermal behaviour is a crucial step in the battery modelling.

      Based on an experimental setup, a simplified thermal model was developed to estimate the surface temperatures of a lithium titanate cell from current and voltage measurements.

      The model was implemented in the COMSOL Multiphysics^® Finite Element code. Charge and discharge cycles of the cell were performed and the predicted heat generation used as input of the thermal model. The calibrated model was lastly used to assess two thermal battery management (TBM) cooling systems, in this case applied to a single cell: a passive phase change material (PCM) system and a hybrid PCM/water system. The effects of the PCM thickness and velocity inlet of the water on the cell temperature were investigated. Results showed that, in comparison to the passively air cooled cell, both systems decreased the maximum surface temperatures, thus improving the uniformity of the temperature distribution and keeping the battery in a safe temperature range.

   8. Modeling of the Thermal Runaway Phenomenon of Cylindrical 18650 Li-Ion Cells

      Paola Russo, Sofia Ubaldi, Maria Luisa Mele

      Abstract

      The thermal runaway (TR) is the main safety concern of lithium-ion batteries (LIBs). Methods for predicting and preventing TR are critical to achieve greater battery safety. Many researchers have studied the reactions that take place inside the cell and that because of their exothermicity trigger the TR. In this work the coupled electrochemical-thermal model for a lithium-ion cell was extended with contributions from exothermic reactions based on an Arrhenius law to model mechanisms of abuse, which could lead to a thermal runaway. Firstly, differential scanning calorimetry (DSC) tests were conducted on the individual components of the cell to characterize the reactions of the TR process in terms of onset temperature, thermal and kinetic parameters. The kinetic parameters of each reaction were identified by the Kissinger method. Then the thermal and kinetics parameters of the reactions occurring during the thermal runaway together with the phenomena involving the electrolyte (i.e., evaporation, boiling and venting) were included in the Battery and Fuel Cell Module of COMSOL Multiphysics simulator, to simulate the behaviour of a cylindrical 18650 cell under thermal abuse conditions. In particular, the results of the model appear to agree with the experimental data, concerning to a NCA 18650 cell subjected to radiative heat flux in a cone calorimeter.