It is challenging for the European power system to exactly predict RES output and match energy production with demand due to changes in wind and sun intensity and the unavoidable disruptions caused by severe weather conditions. Therefore, in order to address the so-called “flexibility challenge” and implement the variable RES production, the European Union needs flexible solutions. In order to accommodate quicker reactions, compared to those performed today, and the adaptive exploitation of flexibility, grid operators must adjust their operational business model, as the electrical grid transitions from a fully centralized to a largely decentralized system. OneNet aspires to complete this crucial step by setting up a new generation of grid services that can fully utilize distributed generation, storage, and demand responses while also guaranteeing fair, open, and transparent conditions for the consumer. Using AI methods and a cloud-computing approach, the current work anticipates that active management of the power system for TSO–DSO coordination will be improved by the web-based client-server application F-channel. In the current work, a user’s experience with the platform for a Business Use Case (BUC) under the scenario of severe weather conditions is presented. The current work aims to increase the reliability of outage and maintenance plans for the system operators (SOs) by granting them a more accurate insight into the conditions under which the system may be forced to operate in the upcoming period and the challenges that it might face based on those conditions. In this way, the methodology applied in this case could, via AI-driven data exchange and analyses, help SOs change the maintenance and outage plans so the potential grave consequences for the system can be avoided. The SOs will have accurate forecasts of the relevant weather parameters at their disposal that will be used in order to achieve the set targets. The main results of the presented work are that it has a major contribution to the optimal allocation of the available resources, ensures the voltage and frequency stability of the system, and provides an early warning for hazardous power system regimes.

This work focused on prescribing, designing, implementing, and evaluating a pilot project conducted in the Greek power system that addressed balancing and congestion management issues that system operators (SOs) face within the clean energy era. The considered pilot project fully focused on the development of the F-channel platform, including the idea behind this application, the steps that were taken in the process, and the outcomes of the performed activities fitting into the overall picture of the OneNet project. The specified F-channel platform is a web-based, client-server application that uses artificial intelligence (AI) techniques and cloud computation engines to improve the management of the active power for the TSO-DSO coordination. The flexibility of the grid’s resources was identified, and an integrated monitoring system based on the precise forecasting of variable generation and demand was implemented. The focus areas were congestion management, frequency control, and voltage control services, for which corresponding network models were created in close cooperation with system operators. The obtained results are essential for the remaining demonstration results because they offer an incredibly accurate basis for further research into their use in congestion management and other weather-related enhanced transmission and distribution system planning and operation practices.

The approach of an integrated electricity market is widespread across Europe, since such a market structure has numerous benefits for both the grid and consumers. The current structure and the related policy framework of the electricity markets adopted within the European countries is based on a benchmark model, the so-called Target Model, which describes a reference energy market framework. In this paper, a comprehensive overview of the legislative effort and the resulting Target Model is provided, aiming to set the basis for the description of the adopted electricity markets in Europe. In a second stage, the current status of the Greek electricity market that operates under the Target model scheme is given via the analysis of the involved submarkets, i.e., the forward market, the day-ahead market, the intraday market, and the balancing market. An intricate case study of the Target Model operation in the Greek electricity market within a day of operation is examined, which actually completes the former description. Within the case study, the Greek electricity market is further investigated for its efficiency and the impact on the obtained electricity prices from the first day of the Target Model implementation, which took place in November 2020, and, finally, today is analysed. The results show an overall successful implementation and satisfactory performance of the Target Model in Greece, with an important main result being the reduction of prices in the balancing market and the increase of the intraday market liquidity. However, several challenges are identified and described in detail, while at the same time measures for their confrontation are proposed in order to improve market operation and fully exploit the benefits of the Target Model.

Plug-in electric vehicle (PEV) is an emerging vehicle that can be directly charged from the power grid via properly designed vehicle-to-grid (V2G) interfaces that coordinate the energy flow between the grid and the connected PEV. The considered PEV structure involves an energy storage system (ESS) and a motor whereas suitable power electronic devices bridge the two subparts. In the proposed scheme, a hybrid ESS (HESS) is taken into account that achieves to overcome the related to the existing batteries limited capabilities, since it combines an energy dense battery and a power dense supercapacitor (SC). Bidirectional dc/dc converters are used as controlled power interfaces between the HESS part and the common dc-side connection point. The V2G interface includes an inverter that controls the power flow from/to the grid and a LCL filter applied to reduce the grid harmonics. The nonlinear mathematical description of the entire PEV-V2G system is developed, in a unified manner, while proper cascaded controllers based on the passivity property are proposed to operate the system in a reliable and desired way. The rigorous stability analysis obtained via advanced Lyapunov techniques ensures global asymptotic stability (GAS) of the entire system around its desired equilibrium by properly tuning the gains of the proposed controllers. The proposed scheme is verified by simulating the complete nonlinear plant and controller system while a further validation is conducted through a hardware in the loop (HIL) real time dSpace-based emulation.

Electric vehicles (EVs), during a route, should normally operate at the desired speed by effectively controlling the power that flows between their batteries and the electric motor/generator. To implement this task, in this paper, the voltage source AC/DC converter is considered as a controlled power interface between the electric machine and the output of the DC storage device; the DC/DC converter is used to automatically regulate the battery operating condition in accordance to the profile of the acting on the vehicle wheels, unknown external torque. Particularly, the speed is continuously regulated by the vehicle driver via the pedal while all other regulations for absorbing or regenerating energy are internally controlled. The driver command is acting as speed reference input on a PI outer-loop motor speed controller which, in its turn, drives a fast P inner-loop current controller operating in cascaded mode. In a similar manner, the machine and the battery performance are self-regulated by a pure PI current controller that achieves maximum electric torque per ampere operation of the motor and by a PI/P cascaded scheme for the DC-voltage/battery–current regulation, respectively. In order to exclude any possibility of instabilities and adverse impacts between the different parts, a rigorous analysis is deployed on the complete electromechanical system that involves the motor, the batteries, the converter dynamic models and the proposed controllers. Modeling the system in Euler–Lagrange nonlinear form and applying sequentially suitable Lyapunov techniques and the time-scale separation principle, a systematic method for tuning the gains of the inner- and outer-loop controllers is derived. Therefore, the proposed controller design procedure guarantees asymptotic stability by considering the accurate system model as a whole. Finally, the proposed approach is validated by simulating realistic route conditions, performed under unknown external torque variations.