Chen-Wei Yang

Information is a key component of progress. Industry 4.0, and especially the future Industry 5.0, is closely related to the topic of the Digital Twin, where virtual components interact with each other. The main advantage of such a system is that it can fully mimic the behaviour of the complicated system, including various unexpected perturbations such as noise, jitter, delays, etc. Thus, the ability to create complex models and run them in real-time is a basic need for extending the Digital Twin. One of the major problems in the development of digital twins is the increasing complexity of the models. Therefore, large processing capacities and parallel computation become critical. The field-programmable gate array (FPGA) is a type of hardware that best fits this task. The FPGA-in-the-loop (FiL) can be considered as the container for running the Digital-Twin model. The transformation of a digital model into FiL is known and used by many companies at this time. However, the authors found that there are no publicly available model-to-FiL transformation methods. In this paper, the authors aim to fill this gap. We first discuss the major design challenges of a FiL system and provide recommendations to overcome them in the form of a road map. We then demonstrate a step-by-step process for converting a simple MATLAB/SIMULINK model to a FiL system using the proposed road map. Finally, we will demonstrate the validation process of the designed FiL systems and prove that they are running in real-time.

The optimal utilisation of distribution grids requires the proactive management of volatilities caused by mixed energy resources installed into different grid levels, such as buildings, energy communities (ECs) and substations. In this context, proactive control based on predictions for energy demand and generation is applied. The mitigation of conflicts between the stakeholders' objectives is the main challenge for the control of centralized and distributed energy resources. In this paper, a bi-level approach is proposed for the control of stationary battery energy storage systems (SBES) supporting the local distribution system operator (DSO) at the transformer level, as well as distributed energy resources (DERs) operated by end customers, i.e., EC-members. Model predictive control (MPC)- based and hybrid approaches merging rule- and MPC-based control schemes are evaluated. Simulation studies based on a typical European low voltage (LV) feeder topology yield the performance assessment in terms of technical and economic criteria. The results show an advantage of hybrid approaches with respect to the DSO's cost savings from peak shaving. From the EC's perspective, both hybrid and MPC-based schemes can achieve effective cost savings from proactive energy management.

Data centres are becoming an increasingly important part of our society’s infrastructure. The number of data centres is growing constantly, making growing the gross level of electrical energy consumption. At the same time, the rapid spread of sophisticated electrical devices as well as other automation systems in general produces an opportunity for making data centres an attractive player in the constantly designing energy market. But for this, new advanced technologies must be applied to solve the problems of complexity and heterogeneity in various types of data centre design. A new concept, which is based on the automated generation of a digital twin (DT) system, directly from its schematic representation is presented in this paper. A DT is a virtual version of an object or system, designed to aid decision-making and virtual commissioning through simulation, machine learning, and reasoning. In the scope of current work, the IEC 61850 standard is chosen as a starting point for a multi-step generation of the DT combining simulation model and decentralized control logic. As a result, the designed DT “clone” of an electrical system consists of the SIMULINK model of the electrical system plus the automatically generated control application (based on the IEC 61499 standard).

The wide propagation of electric vehicle (EV) charging infrastructure integrated into the energy distribution network poses numerous challenges for the engineering and control of the latter: the load dynamic characteristics become more unsteady, requiring more advanced control, predictions, and virtual commissioning. One step toward automation of the design and simulation of new charging stations can be reached through the integration of the EV-specific standards and protocols with other widely spread electrical standards and thereby improving the compatibility between standards, increasing the reuse of the intelligent work results, and promoting the development of EVs' infrastructure. A method for virtual commissioning of electrical charging stations is proposed, implemented, and tested in a form of a software tool, in which the electrical system description from the widely used IEC61850 standard is used as an input. The designed tool builds a Digital Twin of the charging station that consists of its SIMULINK model as well as two automatically generated communication code primitives using the Open Charge Point Protocol (OCPP) for control and management purposes over the auto-generated model. The generated Digital Twin can be used for virtual commissioning purposes. The application of the method is illustrated in a case study.

The growing integration of intermittent renewable energy sources (RESs) and the increasing trend of shutting down fossil-fuel-based power plants has brought about the need for additional flexibility in energy systems. This flexibility can be provided in various forms, including controllable generation and consumption, storage, conversions, and exchanges with interconnected systems. In this context, an increasing focus is placed on the development of smart energy systems (SESs) that combine different types of distributed energy resources (DERs), information and communication technologies (ICTs), demand side management (DSM), and energy conversion technologies. The utilization of SESs can lead to multiple benefits for the stakeholders involved; therefore, the assessment of their performance is a primary concern. Due to their multidisciplinary nature, there are no known or universally accepted standards for assessing the performance of SESs. Previous efforts only define key performance indicators (KPIs) for individual homogeneous subsystems, focusing on a specific SES type and application area. This paper focuses on the development of a novel comprehensive KPI framework that can be applied to any type of SES, regardless of the application area. The proposed framework consists of four layers that specify the application area, the main SES requirements, and the involved stakeholders’ objectives. Next, the KPIs are identified for each of the stakeholders’ objectives. The proposed KPI framework is applied to the use case of a European research project with different application areas, to demonstrate its features. Finally, a repository of KPIs is identified for each use case with respect to the aforementioned SES requirements.

Datacentres are becoming a sizable part of the energy system and are one of the biggest consumers of the energy grid. The so-called “Green Datacentre” is capable of not only consuming but also producing power, thus becoming an important kind of prosumers in the electric grid. Green datacentres consist of a microgrid with a backup uninterrupted power supply and renewable generation, e.g., using photovoltaic panels. As such, datacentres could realistically be important participants in demand/response applications. However, this requires reconsidering their currently rigid control and automation systems and the use of simulation models for online estimation of the control actions impact. This paper presents such a microgrid simulation model modelled after a real edge datacentre. A case study consumption scenario is presented for the purpose of validating the developed microgrid model against data traces collected from the green edge datacentre. Both simulation and real-time validation tests are performed to validate the accuracy of the datacentre model. Then the model is connected to the automation environment to be used for the online impact estimation and virtual commissioning purposes.

Article 1120. Пензенский государственный университет

The smart grid is positioned as the next generation energy distribution system which incorporates distributed renewable energy and digital communication infrastructure. The Smart Grid is considered by many as a complex Cyber-Physical System, a system with tight integration between its modular cyber and physical processes interacting in a networked environment. Traditionally, the method of testing Smart Grid automation systems is based on device-based testing and this is largely influenced by the bottom-up design methods that are used widely in the engineering of the substation automation system. However, with the advent of the Smart Grid and the introduction of distributed based automation systems, requirement-driven testing of the whole automation system may be more beneficial than device based testing. In this paper, a scripted co-simulation platform is introduced with the purpose of automating the testing of functional requirements in distributed substation automation systems. The scripted co-simulation testing framework is illustrated on a CIGRE case study where the distributed automation system is validated against the functional requirements.

Статья 7118. Пензенский государственный университет