In light of the advancing energy transition and an increasing amount of intermittent renewable energy to be integrated, flexibility from distributed energy resources will be key. In this paper, the Italian UVAM (Unità Virtuali Abilitate Miste, i.e., virtually aggregated mixed units) project, one of the biggest pilots in Europe to serve this purpose, is critically reviewed and mapped after two years of operation. The pilot is analyzed on a global level as well as the individual participant level. Based on the extensive analysis of actual market data, different strategies of participating companies to obtain capacity in accordance with the pilot project’s design are identified. Furthermore, the specific bidding strategies of individual participating units on the balancing market are outlined. Alongside this, the overall pilot project’s market integration, in terms of offered and accepted bids, is depicted. The thorough data analysis, therefore, serves as an input and fundamental building block for future electricity market modeling. Comprehending specific data from the coronavirus disease 2019 (COVID-19) pandemic, provides insights for future high renewable-energy scenarios. Based on the analysis findings, valuable deliverables are devised for both policy-makers and decision-makers who aim to leverage the flexibility potential of distributed resources.

The diffusion of distributed energy resources in distribution networks requires new approaches to exploit the users’ capabilities of providing ancillary services. Of particular interest will be the coordination of microgrids operating as an aggregate of demand and supply units. This work reports a model predictive control (MPC) application in microgrids for the efficient energy management of energy storage systems and photovoltaic units. The MPC minimizes the economic cost of aggregate prosumers into a prediction horizon by forecasting generation and absorption profiles. The MPC is compared in realistic conditions with a heuristic strategy that acts in a instant manner, without taking into account signals prediction. The work aims at investigating the effect that different types of energy tariffs have in enhancing the end-users’ flexibility, based on three examples of currently applied tariffs, comparing the two storage control modes. The MPC always achieves a better solution than the heuristic approach in all considered scenarios from the cost minimization point of view, with an improvement that is amplified by increasing the energy price variations between peak and off-peak periods. Furthermore, the MPC approach provides a cost saving when compared to the case considering a microgrid endowed with only photovoltaic units, in which no storage is installed. Findings in this work confirm that storage units better perform when some knowledge of future demand and supply trends is provided, ensuring an economic cost saving and an important service for the overall community.

The promotion of electric mobility is a key objective of energy transition, and it is aimed at significantly reducing greenhouse gas emissions, with road transport being understood as a major contributor. Despite its potential, the adoption of electric vehicles (EVs) in logistics faces critical challenges, including limited battery range, charging time, and the availability of charging infrastructure. Moreover, deploying charging stations must be carefully coordinated with the public grid to ensure seamless integration. This paper proposes a novel methodology for the optimal design and management of EV fleets in logistics. Our approach introduces innovations such as leveraging self-produced electricity and incorporating time-varying energy prices that can be tailored to individual nodes. This marks an important step toward a comprehensive interdisciplinary framework that integrates technical solutions with public policy considerations. Through case studies, we explore how various parameters and resource distributions influence optimal decisions. The findings demonstrate significant potential for cost reduction and enhanced efficiency when applying this methodology to EV-based logistics, thereby offering actionable insights for advancing sustainable transportation.

The growth of distributed energy resources (DER) connected at distribution network level and the current legislation concerning the participation of DER to the energy and ancillary services markets, are a huge opportunity to get flexibility services from these resources but at the same time a great challenge from the technical point of view. According to the latest indications from EU Directives, demand response and generation flexibility are encouraged in order to meet network balancing needs, but a new actor is required: the aggregator. This new participant has the duty to aggregate consumption and generation in order to offer flexibility products in the ancillary services market, while ensuring the technical feasibility and assuring revenues for its clients and itself. This work focuses on the structure and the business model of aggregators and discusses the technical implication that such role has on the distribution network.