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Electric vehicles (EVs) and the recent pandemic outbreak give cities a new trend to primarily private and shared mobility with low noise and less air pollution. Crucial factors for the widespread of EVs are the electrical charging infrastructure, driving range, and the reduction of the cost of battery packets. For this reason, there is a massive effort from manufacturers, governments, and the scientific community to reduce battery costs and boost sustainable electrical production and distribution. Battery reuse is an alternative to reduce batteries’ costs and environmental impacts. Second-life batteries can be used in a wide variety of secondary applications. Second-life batteries can be connected with off-grid or on-grid photovoltaic and wind systems, vehicle charging stations, forklifts, and frequency control. The present work aims to analyze the main challenges imposed on the reuse of batteries, the leading technologies for their reuse, and the different types of batteries in terms of their feasibility for second-life use. The main novelty of this work is the discussion about the barriers, opportunities, uncertainties, and technologies for the second life market. Here we summarize the present state of the art in reusing lithium-ion batteries discussing technical and economic feasibility, environmental impacts, and perspectives. The results show five business models that have been proposed in the literature, three types of markets for trading second-life batteries, and the main opportunities and barriers for each actor in the battery supply chain.

Among different solutions to increase flexibility of electricity system, grid interactive water heaters (GIWHs) can make a large contribution, against a relatively low cost. They can advantageously be used within a single building, a local energy community or within an entire distribution grid, thanks to the very fast response time, low cost, highly distributed resource and widely demonstrated technology. In the near future, the flexibility potential of GIWHs will certainly increase, thanks to the advantageous flexibility programs that have been implementing in some area of the world, with the aim of coordinating several million of GIWHs with the electricity network. In this study, we assess the potential value that the flexibility of GIWHs can bring to the electrical power system, compared to the other sources of flexibility, focusing on the US market, specifically California, Oregon and Washington. The GIWH technology and the main GIWH control strategies are described, highlighting the flexibility behaviour of GIWHs. An overview of the GIWH pilot programs currently developed in the US market is provided, and current available technologies are shown, both for new and for retrofit GIWH installations. Most of the papers discussed in the literature focus on different aspects of demand response (DR), but very few of them focus specifically on GIWHs, and none of them offers a review of GIWHs in the US context. The present work thus constitutes a research gap, and could help stakeholders to assess the US GIWH market evolution, identifying the potential value of GIWH flexibility.

Microgrid systems that combine cooling, heating and power (CHP) with distributed cogeneration units and renewable energy sources are a practical way to meet the growing need for energy, and industrial parks have enormous potential for the development of integrated electrical and thermal systems. This paper presents a microgrid CHP model and evaluates the possibility of developing the model in the Dong Nam industrial park in Ho Chi Minh City, Vietnam. HOMER software was used to evaluate the effectiveness of the model.

The Blorin project started at the end of 2019 to support the implementation of a blockchain platform to support the energy services provision from end users by means of Demand Response and Vehicle to Grid programs. The experimental part of the project is being carried out on two Mediterranean islands and inside the University campus in Palermo. Customized smart contracts have been designed to support the active participation of end users to regulation services for the two weak electrical grids of the islands in the view of a deep penetration of renewable energy in the two energy systems. In particular, the smart contract for remuneration accounts for the very special energy situation of islands where TSO, DSO, energy seller and aggregator collapse in a unique market actor. Moreover, in islands the electricity provision is typically still relying on diesel generators thus strongly connecting the Demand Response programs benefit to the reduction of fuel consumption, as an effect of increased efficiency of diesel generators. Due to the critical international situation and to the climate crisis, fossil fuels get more and more costly, thus a speed up of the energy transition in small islands is highly needed. This paper addresses the problem of designing a customized smart contract for remuneration of Demand Response service provision in small islands.

Transportation is one of the key sectors causing greenhouse gas (GHG) emissions and air pollution. With the substantial increase in passenger and freight transportation, the corresponding GHG emissions and air pollutants are expected to increase significantly. Recent global and national policies are targeting at reducing environmental impacts of transportation activities. The promotion of public transportation and development of electric buses (e-buses) will reduce the use of fossil fuels in transportation, and consequently, reduce GHG emissions. This study assesses the life cycle GHG emissions and other environmental impacts of e-bus, and compares them with those of conventional bus operated in Vietnam. The results indicate that e-bus is a preferred choice in most of studied environmental impact categories over the whole life cycle such as GHG emission, ozone depletion, ozone formation, fine particulate matter formation, acidification, etc. For GHG emissions, the adoption of electric mobility will reduce 42.62 gCO(2)eq per passenger km of carbon footprint if conventional buses are substituted by e-buses in Vietnam.

This chapter presents the outcomes of the experimental implementation of the architecture described in Chap. 4 running a hardware testbed for the emulation of domestic electrical load profiles. Besides it shows how this experimental scenario integrates both with the legacy metering architecture and with the blockchain platform. Finally, the integrated use with an Energy Management System designed on purpose is also described with the aim of ensuring intervention and automating the end user’s response to a DR event.

Renewable electricity for off-grid areas is widely seen as one of the top choices in supporting local economic development in most countries, and so is Vietnam. Over the years, many isolated networks using renewable energy sources have been deployed for off-grid areas in Vietnam. However, the use of these energy sources in Vietnam’s isolated networks is still facing many challenges due to its infancy here. The issues of reliability and vulnerability of these networks are not given the expected attention. Another challenge is that the issues of the operational security of these systems could also be negatively affected by the variable nature of renewable sources, including static and dynamic security. For this reason, this study aims to contribute to a better understanding of integrating renewable energy into isolated networks, and in this case, using solar power for the An-Binh Island grid in Vietnam. The findings from this study suggest that choosing the right structure of the power mix could contribute to improving the operational security of isolated networks. Moreover, several solutions to enhance the reliability of this grid are also proposed. The NEPLAN environment was selected for simulation and analysis for all the scenarios in this study.

Featured Application: The potential application of the proposed model is a computationally inexpensive semi- or fully automated system for the optimization of operation in residential buildings in terms of energy consumption. Some analyses state that buildings contribute to overall energy consumption by 20–40%, which, in the context of the recent geopolitical energy crisis, makes them a critical issue to study. Finding solutions for better energy management in buildings can have a significant impact on the energy sector, thus reducing EU energy dependencies and contributing to the fulfillment of the REPowerEU goals. This paper focuses on proposing a simplified model of a residential house considering the main appliances, heating and cooling, a photovoltaic system, and electric vehicle recharging. Weather and solar irradiance forecasts are taken into account. The model predicts the energy demands of a house based on online weather forecasts and the desired indoor temperature. The article also focuses on the analysis of how weather forecast uncertainty affects energy demand prediction. This model can be used to better understand and predict the energy demand of either a single house or a set of houses. A multi-objective optimization approach that takes into account the preferences of users/inhabitants is developed to provide a compromise between the price paid for the electricity and temperature comfort. The authors plan to apply the proposed model to a residential house’s real-time control system. The model will be tuned, its predictions will be tested, and it will be used for energy demand optimization.

To date, the European regulatory framework requires the development of new energy policies at the national level that can reduce overall consumption and support the implementation of customer-focused control and management systems. Therefore, it is necessary to study the feasibility of the various strategies available, especially for the involvement of residential users in services that can contribute to the management of the electricity grid. The advent of blockchain technology has enabled the development of new business models for the electricity market, opening this world to end users who previously did not have the opportunity to participate in energy trading and allowing the implementation of services to ensure the proper operation of the power grid. Due to its characteristics, blockchain could be the solution to balancing problems caused by the penetration of unpredictable renewable sources. This paper describes a test bench for a Smart Prosumer simulation with the goal of emulating a user who is both a consumer and a producer, but also able to be smart, i.e., to optimally manage production and consumption and to communicate with a blockchain network for the provision of energy services. The document shows the different components of the test bench and how it is connected to a local blockchain implemented in the framework of the Blorin research project.

Issues related to the stability of non-interconnected grids are of high relevance given the increasing presence of renewable sources in the power generation system. In order to ensure adequate levels of system's reliability, it is necessary to find new methods to ensure the stability of the electric grid. The present work proposes a methodology for the definition of the minimum number of Vehicle-to-Grid (V2G) charging points that would allow the integration of 1 MW of photovoltaic power in the power grid of the Italian island of Favignana, electrically disconnected from the continental grid. Primary frequency regulation simulations are carried out in Matlab/Simulink environment for different scenarios related to the generation park. The results show that with a limited number of V2G points levels of stability of the electrical system comparable to those before the installation of the photovoltaic plants can be ensured.

This paper describes a blockchain-based approach for sharing data among all the actors involved in Vehicle-to-Grid programs. The shared information is used both for monitoring the health status of the vehicle’s battery and for remuneration in Vehicle-to-Grid programs. A blockchain platform and a set of appropriate smart contracts have been developed for supporting the interactions among the different actors and for creating battery usage profiles. To protect sensitive data, we limit the visibility scope of such data only to subsets of actors using blockchain channels. This approach preserves the privacy of the car owner on one hand and guarantees the compliance to correct charging and discharging modes, on the other hand, by using dedicated smart contracts to manage data for each of the channels. The approach here described proposes and develops a blockchain-based ecosystem for efficiently managing electric vehicles especially when these are called to provide electrical grid services, such as it happens for Vehicle-to-Grid programs. In this case, it is indeed possible that the battery undergoes an accelerated aging and thus certified recording of charging data for legal liability is one of the issues here dealt with. When possible, data are collected from multiple sources (e.g. the charging station and the Electric Vehicle) and from different parties with conflicting interests for validating data and breaking data silos that are within the car, the charging stations and the Battery Management System.

This study presents how to improve the short-term forecast of photovoltaic plant's output power by applying the Long Short-Term Memory, LSTM, neural networks for industrial-scale solar power plants in Vietnam under possible curtailment operation. Since the actual output power does not correspond to the available power, new techniques (Global Horizontal Irradiance - GHI interval division, P/GHI factor addition (P - Power)) have been designed and applied for processing errors and missing data. The prediction model (LSTM network, structure of hidden layers, number of nodes) has been developed by the authors in a previous work. In this new version of the model, the training technique is improved by using validation and experiments to determine the appropriate relevant parameters. The forecast results show that the proposed new method is more efficient than the old method, as the MAPE (Mean Absolute Percentage Error) forecast error is reduced by 6.059% and the RMSE (Root Mean Square Error) is reduced by 6.710%.

The use of technologies such as Internet of Things (IoT), data processing and blockchain have allowed companies to serve their customers with better quality, efficiency, reliability and in the shortest possible time. The growing adoption of electric vehicles on the market has increased the demand for batteries that may have numerous manufacturers. Life expectancy is affected on manufacture, but also on operational conditions. A large number of parameters have a role on battery's health and thousands of data need to be evaluated and combined. The present work investigates the scenario of the battery industry in order to implement a blockchain-based platform for the supply chain implementation thus allowing a better control on performance of batteries and environmental impact. To achieve this goal, the authors carried out a systematic review with the following steps: identification of relevant studies, evaluation and summary of similar studies, comparison and extraction of data from the papers. The main motivation of this work is the use of the literature for justifying the use of the blockchain technology to track batteries and for identifying the main challenges in the related markets that can be addressed by this technology. The results of this systematic review show that the development of a blockchain-based platform for battery tracking will allow for greater transparency across the entire supply chain: production, reuse, recycling, disposal. Trasparency and traceability prevent clandestine markets, misuse and release of pollutants. Adressing these topics forsters the successful implemention of electric vehicles in the market.

The Directive (EU) 2018/2001 (RED II) requires Member States to authorize the constitution of consumers as self-consumers of renewable electricity by ensuring them non-discriminatory and disproportionate treatment. Member States must establish a favorable framework for promoting and facilitating the development of self-consumption, including in collective form (art. 21). According to the Directive, the granting of rights to renewable energy self-consumers who act collectively allows to increase the energy efficiency of households and helps to combat energy poverty by reducing consumption and supply tariffs. In Italy, the decree n. 162/2019 and then amended with Decree 199/2021 has partially enacted the RED II Directive. On the other hand, it must be observed that after more than 2 years the number of energy communities in Italy is still limited. One of the main barriers is related to the fact that there is no clear indication about how to share the incentive among the REC's members. In this paper, an effective model for the remuneration of the energy community members is proposed and an experiment is carried out in a laboratory environment, supported by Prycam Home devices.

Transport sector is moving towards clean and green transportation with the growing market of electric vehicles globally. Electric vehicles are independent fossil fuels consumption, but the massive adoption of electric vehicles soon can lead to a significant burden on the power distribution networks. In this paper, a study on the potential impact of electric vehicles on the power distribution networks of two different regions with totally different realities of population density, an average number of cars per inhabitant, and travel habits has been carried out. The first region is the island of Favignana having an insular power distribution network, while the other region, the city of Palermo has a grid-connected power distribution network with eight substations. The load profiles of these two regions have been analyzed in detail with future scenarios of 10, 20, and 50 % penetration levels of electric vehicles. The Monte Carlo method having the capability of generating data on the behavior of car owners with consideration of different scenarios has been used, utilizing MATLAB software. The simulation results indicate that the high penetration levels of electric vehicles in the future will lead to high peak load demands and these results will be more severe for the regions having high population densities, a high average of cars per inhabitant, and long driving distances.

Vietnam became the world’s third largest market for solar photovoltaic energy in 2020. Especially after the Vietnamese government issued feed-in tariffs for grid-connected solar photovoltaic systems, the installed capacity of solar photovoltaic applications exploded in 2019. From studies carried out in the relevant literature, it can be said that support policies are highly important for the initial development of the renewable energy industry in most countries. This is especially true in emerging countries such as Vietnam. This paper reviews the feed-in tariffs issued and deployed in different regions of Vietnam for grid-connected solar photovoltaic applications. Moreover, the paper takes a closer look at the costs of electricity production from these systems in relation to the feed-in tariffs issued in Vietnam. The results show that the gap between the levelized cost of electricity and the feed-in tariff for solar photovoltaic electricity is relatively high, particularly in regions with a lower irradiation potential.

Data play an essential role in the optimal control of smart buildings’ operation, especially in building energy-management for the target of nearly zero buildings. The building monitoring system is in charge of collecting and managing building data. However, device imperfections and failures of the monitoring system are likely to produce low-quality data, such as data loss and inconsistent data, which then seriously affect the control quality of the buildings. This paper proposes a new approach based on Gaussian process regression for data-quality monitoring and sensor network data compensation in smart buildings. The proposed method is proven to effectively detect and compensate for low-quality data thanks to the application of data analysis to the energy management monitoring system of a building model in Viet Nam. The research results provide a good opportunity to improve the efficiency of building energy-management systems and support the development of low-cost smart buildings.

The advent of blockchain technology allows the raise of new business models for the electricity market, opening the way also to end-users and letting them offer regulation services to the power grid. Thanks to the characteristic of being distributed, the blockchain technology could be a solution to balancing problems caused by the penetration of renewable sources, implementing a platform for Demand-Response programs delivery. Demand-Response allows consumers to respond to market signals by increasing or reducing their energy consumption, contributing to greater flexibility and stability of the grid and to a more efficient use of infrastructures and energy resources. Currently, Demand-Response is carried out by controlling aggregates of loads, storage or generating units managed by centralized Supervisory Control and Data Acquisition systems such as SCADA. Regulatory changes and the increasing penetration of renewable sources distributed over the territory are turning the whole electricity system into a smart-grid. More recently and with reference to the end-users participation in regulation services, smartness is achieved through the so-called Internet of Things, which can be considered the modern equivalent of SCADA, but with the possibility of to being applied to distributed and diversified assets. For this reason, great efforts have been made to study the interoperability and coexistence between Internet of Things and blockchain, two emerging paradigms that are gaining popularity in the energy world. Limited or no contribution can instead be found in the literature on the integration of SCADA systems and blockchain. Indeed, in order to ensure an easier and faster widespread application of blockchain in the context of power systems, it is interesting to study its possible coexistence with legacy and more established industrial technologies such as OpenADR or SCADA. In Europe, the prevailing technology is the latter one. For this reason, in this paper, the coexistence of blockchain technology with SCADA systems is discussed. In particular, both Hyperledger Fabric blockchain and SCADA systems are considered together to assess the feasibility of aggregation of energy resources for Demand-Response, as well as the relevant measured data. The analysis is carried out by first presenting the two different paradigms: the centralized data acquisition in trusted environments and analysis via OpenADR and SCADA, and the global, distributed and secured ones with the blockchain. Then an architecture for the integration of SCADA and blockchain technology is proposed and the related challenges within the frame of a project for innovative technologies DR programs implementation are outlined.

The reduction of climate change effects (mitigation) is now mainly driven by the limitation of CO2 emissions which is currently becoming increasingly necessary and urgent to achieve. In this context, within the past Horizon 2020 program, the Urban Europe Joint Programming Initiative aimed to promote the development and deployment of at least 100 Positive Energy Districts by 2025. The latter are flexible, energy-efficient urban areas or groups of buildings that produce zero net CO2 emissions and actively manage annual renewable energy surplus production at the local or regional level. As they are connected to the electric power system, Positive Energy Districts have the ability to offer flexibility services to the grid, such as frequency or voltage regulation, being part of a larger scheme as the Italian energy communities recently regulated by the Milleproroghe Decree. In this paper, a blockchain-based architecture is proposed with the aim of providing a system for the trusted certification of energy self-sustainability and the management of energy trading among different districts or the supply of energy services delivered from the district to the electricity grid, promoting their effective integration with the power system.

The paper analyses the dramatic effects of the first wave of the COVID-19 pandemic on the Italian power system, considering the impacts on load and generation, market issues and ancillary services provision. During the period between March and May 2020, the Italian scenario was considered as exemplary due to the large reduction of loads and thermal generation caused by the hard lockdown across the Country. Italy has experienced the most severe effects of pandemic in terms of increase of death rates and of pressure on the health system as well as severity of the countermeasures. As a domino effect, the total lockdown of one of the most industrialized countries in the world has created an emergency situation that has put a big stress on the power system, reducing the possibility for the system to recover under contingencies. The weakness of the system in such an extreme situation is analyzed in depth using open data, while some countermeasures for providing resilience to the power systems in such cases are analyzed in simulation. Two technologies are here considered as exemplary countermeasures for providing resilience to the Italian power system: Fast Frequency Response by Photovoltaic and Wind plants with rated power above 10 MVA and the massive implementation of Demand Response programs through Energy communities and aggregation using Blockchain technology. The simulations show, on one hand, that the frequency recovery under contingency seems compromised in the current situation and that the support from such innovative technologies can provide a significant relief bringing the operational features close to those before the COVID-19 pandemic.

The new European Directive RED-II on the promotion of the use of renewable energy sources has introduced the concept of the Renewable Energy Community. This new entity has the potential to change the relations among end-users and the latter and the other actors of the energy sector. In particular, the electrical sector appears the most influenced by the implementation of this paradigm. Indeed, the need for self-consumption and for exploiting the full potential of renewable energy in a Renewable Energy Community influences how the end-users exchange energy with the power grid, the rules for their connection to the grid, the implementation of Demand Response and other energy management programs. For this reason, after a review of the existing legal framework, this paper investigates various aspects concerning the interaction of Renewable Energy Communities with the power system, highlighting what issues must still be addressed for a complete implementation of Renewable Energy Communities and their integration in the power system, with a focus on the Italian context.

Energy Communities (EC) are a promising solution to reduce both the carbon footprint and the impact of Renewable Energy Sources (RES) on the distribution grid. Based on a simple energy sharing principle, EC can be decisive in the next future energy transition of some problematic territories, like small islands not supplied by the main power grid. By integrating Battery Energy Storage Systems (BESS), it is possible to improve the EC performance. However, due to the still high BESSs unit prices, the goal of this work is to find the optimal size of BESSs, under various conditions, which combines the need to maximize shared energy and the possible revenue of EC actors. To set this multi-objective problem, in this paper is presented a procedural algorithm, numerically implemented in MS Excel environment and optimized through GRG nonlinear algorithm of MS Excel Solver. The algorithm is applied to the case study of Pantelleria island.

Energy production from distributed renewable power plants underwent a takeoff in last years as never before. Nevertheless, the installation of technologies based on variable energy resources and their connection on transmission power lines might cause congestions due to the transmission capacity limits. This paper describes the modelization of a HV transmission line with local renewable production and its optimal management through an Energy Hub model. Aim of the study is to identify the optimal size of the power storage, based on an electoryzer, a hydrogen storage and a fuel cell, in order to minimize the congestion risks and to maximize the exploitation of renewable energy production.

For the participation in the frequency control of the system, power converters can be controlled with different strategies and methods, sharing the common concept of virtual inertia capability. In this work, a sensitivity analysis of two main categories of converter controls with virtual inertia is presented. The considered schemes are a grid-following current vector control with additional virtual inertia block and a grid-forming control scheme based on virtual synchronous machine concept. A proper basis for the comparison is first assessed providing an analytical correlation between the control parameters of the two schemes. For the two control strategies, the sensitivity analysis of the most relevant factors is performed on the linearised model of the system. Time-domain simulations are also performed on the full non-linear model, investigating the frequency dynamics of the two control structures under different oscillating conditions. The analytical comparison and the results of the analyses indicate specific and distinct oscillatory characteristics of the examined control structures, pointing out for each of them opportunities and limitations for participation in the frequency dynamics of the system.

This paper presents the results of a simulation study concerning different Demand Response logics applied to Electric Storage Water Heaters on the island of Lampedusa. Electric Storage Water Heaters are the devices that are primarily used on the island to produce domestic hot water. Starting from measured load profiles collected in Lampedusa, a domestic hot water consumption profile was derived, to simulate the energy usage of the Storage Water Electric Heaters during the day. This work was carried out as a preliminary feasibility study for the BloRin project, financed by cohesion funds in the Sicilian region. According to the project, which also includes the installation of domestic photovoltaic systems on the island, two development scenarios have been formulated. The results show that even a limited penetration of photovoltaic power in the energy system of Lampedusa can lead to steep load ramps and risk of power inversion in distribution substations. To overcome these problems, several Demand Response programs have been considered. By setting a higher value of the desired water temperature of the Storage Water Electric Heaters, in the hours of maximum photovoltaic generation, thermal loads can be shifted towards central hours of the day, with clear benefits in terms of power inversion containment and peak reduction.

The energy transition and climate neutrality are a short time scenario as climate concerns are rising fast. Small islands are natural microgrids in which the energy transition is subjected to economic and regulatory constraints and highly challenged by technical issues. As a first step, the Mediterranean island of Favignana has been considered in this study, to assess how electric mobility could impact the power system. According to the plans from the local decision makers, the island is moving towards a full public electric mobility in the near term, also due to the participation in the BloRin project. For this reason, a feasibility study about the technical and environmental impact of electric mobility is highly needed. What appears is that the network is ready for such a transition even if carried out in massive terms, while the current electric mix makes the shift to electric mobility more polluting. Therefore, the assessment of the environmental impact, quantified comparing the emissions of the current scenario with those of a future condition with a 20% penetration of EVs on the island, highlights the need of a simultaneous shift to zero emission power production. The simulations are carried out using the NEPLAN software and considering various operating scenarios. In most cases, the substations are charged two times the current power flows, but never going beyond the rated capacity.

The study (a) assesses the life cycle energy consumption and air emissions impacts of battery electric buses (e-buses) and conventional buses operated in Vietnam, and (b) compares them with those of hydrogen buses. The results indicate that e-buses and hydrogen buses are preferred options compared to conventional buses in terms of energy consumption, GHG emissions and other air quality impacts over their whole life cycle. Life cycle energy consumption of diesel buses is triple that of e-buses, and is significantly higher than that of hydrogen buses. Replacing conventional buses with e-buses can reduce energy consumption by 50%. For GHG emissions and air quality impacts, the adoption of electric and hydrogen mobility in replacement of conventional buses will reduce GHG emissions by 39%, and other impacts related to air quality by 13% to 90%.

The energy transition towards efficient energy production, transport, and use, renewable energy (RE) technologies and innovative energy management brings benefits to reducing greenhouse gas (GHG) emissions and achieving climate targets. The transition requires resources, minerals, metals, and materials for RE technologies themselves, for example, solar photovoltaics (PV), hydrogen fuel cell vehicles (HFCVs) as well as innovative supporting technologies for variable RE, for example, energy storage systems (ESSs). This requirement of resources and materials occurs over the whole supply chain of the technologies, from the extraction of resources, the manufacture of technology, and the deployment of technology, till the very end of its life cycle. In such context, the consideration of resources in general and critical raw materials (CRMs) in particular and their relations to the risk of supply chain disruption are highly important for achieving the global green energy transition. This editorial paper provides a brief view of the close connectivity between materials/resources and the green transition over the whole supply chain of energy technologies.

The operation of a power system with 100% converter-interfaced generation poses several questions and challenges regarding various aspects of the design and the control of the system. Existing literature on the integration of renewable energy sources in isolated systems mainly focuses on energy aspects or steady-state issues, and only a few studies examine the dynamic issues of autonomous networks operated with fully non-synchronous generation. A lack of research can be found in particular in the determination of the required amount of grid-forming power, the selection of the number and rated power of the units which should implement the grid-forming controls, and the relative locations of the grid-forming converters. The paper aims to address those research gaps starting from a theoretical point of view and then by examining the actual electrical network of an existing island as a case study. The results obtained from the investigations indicate specific observations and design opportunities, which are essential for securing the synchronization and the stability of the grid. Possible solutions for a fully non-synchronous operation of autonomous systems, in terms of dynamic characteristics and frequency stability, are presented and discussed.