Energies

This paper presents a case study of a Home Energy Management System (HEMS) integrating photovoltaic (PV) generation, battery energy storage (BES), thermal storage, and a heat pump in a single-family household operating under a dynamic electricity tariff. The analysis is based on real operational data and focuses on system performance under varying solar generation conditions. The results show that during sunny days, the battery storage absorbs the entire surplus PV generation until reaching full capacity, i.e., 10 kWh, effectively preventing curtailment and maximizing self-consumption. On days with limited solar production, the system actively utilizes the available storage capacity by shifting energy use in time and, when economically justified, temporarily charging the battery from the grid during low-price periods. This strategy reduces electricity purchases during peak-price hours and stabilizes household energy costs. For the analyzed case, daily PV generation self-consumption exceeded 70% on high-generation days, while the application of storage-based load shifting under dynamic tariffs reduced daily electricity costs by up to 30% compared to a fixed-rate tariff. The study confirms that the economic and operational performance of residential energy systems under dynamic pricing depends primarily on adaptive storage control rather than on PV capacity alone, highlighting the central role of battery energy storage in year-round energy optimization.

Road transport decarbonization remains a strategic priority in the context of the global climate emergency. Between 2013 and 2024, most economic sectors in the European Union reduced emissions, whereas the transport and storage sector increased them by 14%, largely driven by road freight demand. This review provides an updated overview of the decarbonization status of the road transport fleet across all segments, with particular focus on heavy-duty freight, which remains 97.9% fossil-fuel dependent. It examines short- and medium-term decarbonization pathways for the existing fleet, highlighting liquid biofuels as an immediately deployable option where full electrification is constrained by technological and economic barriers. Among these options, fatty acid methyl ester (FAME) and hydrotreated vegetable oil (HVO) stand out due to their compatibility with current engines and fuel distribution infrastructure, but each presents specific limitations. Biodiesel raises concerns over long-term engine durability, while HVO requires further evidence on its impact on NO_x emissions and fuel lubricity. When these sustainable fuels are used with or without fossil diesel, there are still several unanswered questions. The emerging use of HVO/FAME blends is therefore discussed as a promising route to mitigate the drawbacks of each fuel, and a research agenda is proposed to support accelerated decarbonization of heavy-duty road freight in the EU.

Hybrid renewable energy systems (HRESs), mixing conventional and renewable power sources and occasionally storage units, have become the norm regarding electricity generation. Robust long-term planning of such systems requires stakeholders to test different layouts and system configurations, while their operational management relies on forecasting surpluses and deficits to achieve optimal decision making. However, both tasks, which in fact constitute a flow allocation problem across power networks, are subject to multiple peculiarities, arising from the nonlinear dynamics of the underlying processes, subject to numerous technical and operational constraints. Interestingly, a mutual problem emerges in water resource systems, also comprising network-type storage, abstraction and conveyance components. In this vein, triggered from well-established simulation approaches from the water domain, we introduce a generic (i.e., topology-free) and time-agnostic framework, the key methodological elements of which are: (a) the graph-based representation of the power fluxes; (b) the effective handling of energy uses and constraints through virtual nodes and edges; (c) the implementation of priorities via proper assignment of virtual costs across all graph components; and (d) the configuration of the overall problem as a network linear programming context, which allows the use of exceptionally fast solvers. Specific adjustments are required to address highly complex issues within HRESs, particularly the representation of conventional thermal and pumped-storage hydropower units, as well as the power losses across transmission lines. The modeling approach is stress-tested by means of configuring a hypothetical HRES in a non-interconnected Aegean island, i.e., Sifnos, Greece.