At the moment of writing, in Italy, there is an ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its outbreak is leading to severe global socioeconomic disruptions impacting on all economic sectors from tourism, industry and the tertiary sector, up to the operational and opening of public offices, the closure of schools and the organization of families. Measures adopted by the Italian government to deal with the COVID-19 emergency have had direct effects both on people’s daily lives and on the activity of most industrial and commercial production companies. These changes have been unequivocally reflected also on the Italian electricity system, which has shown unprecedented behavior in terms of both energy consumption and volume—and subsequently, in the observed share of renewable and conventional production technologies. The goal of this study is to show the impact on the power industry of all the restrictions and lockdown of the activities in Italy and to discuss the effects of COVID-19 outbreak on the bulk power system and the entire electricity sector. In particular, the consequences on load profiles, electricity consumption and market prices in Italy, including the environmental aspects, are examined.

Islanding is known as a management procedure of the power system that is implemented at the distribution level to preserve sensible loads from outages and to guarantee the continuity in electricity supply, when a high amount of distributed generation occurs. In this paper we study islanding on the level of the transmission grid and shall show that it is a suitable measure to enhance energy security and grid resilience. We consider the German and Italian transmission grids. We remove links either randomly to mimic random failure events, or according to a topological characteristic, their so-called betweenness centrality, to mimic an intentional attack and test whether the resulting fragments are self-sustainable. We test this option via the tool of optimized DC power flow equations. When transmission lines are removed according to their betweenness centrality, the resulting islands have a higher chance of being dynamically self-sustainable than for a random removal. Less connections may even increase the grid’s stability. These facts should be taken into account in the design of future power grids.

The newest Distributed Ledger Technology platforms, which delegate the execution of complex tasks in the form of Smart Contracts, make it possible to devise novel local electricity market frameworks, which are performed in a fully automated fashion. This paper proposes a novel fully automated platform for energy and ancillary service markets in distribution networks, able to run in a decentralized fashion, bypassing the need for a physical central authority. The proposed platform, able to perform the role of Virtual Decentralized Market Authority, shows excellent potential applications in the management of local ancillary service markets in local energy communities of various sizes. The proposed Virtual Decentralized Market Authority showed reasonable running costs and comparable technical management capabilities with respect to a physical, centralized managing authority.

We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas.

The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players’ behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents’ behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data.