Filipe Joel Soares

Abstract
This chapter explores the potential of thermal energy storage (TES) systems towards the decarbonization of industry and energy networks, considering its coordinated management with electrochemical energy storage and renewable energy sources (RES). It covers various TES technologies, including sensible heat storage (SHS), latent heat storage (LHS), and thermochemical energy storage (TCS), each offering unique benefits and facing specific challenges. The integration of TES into industrial parks is highlighted, showing how these systems can optimize energy manage-ment and reduce reliance on external sources. A district heating use case also demonstrates the economic and environmental advantages of a multi-energy management strategy over single-energy approaches. Overall, TES technologies are presented as a promising pathway to greater energy effi-ciency and sustainability in industrial processes.

Abstract
Electric vehicles (EVs) are expected to accelerate the decarbonization of transport while also becoming a highly distributed and flexible resource for power systems. By coupling substantial battery storage with long parking times, EVs can support higher shares of renewable generation through controlled charging and, where available, bidirectional operation (e.g., V1G/V2G and related concepts). At the same time, large-scale EV uptake can increase peak demand, aggravate congestion and losses, and trigger voltage issues (particularly if charging remains unmanaged) potentially leading to costly network reinforcements. This chapter reviews the main EV types, charging modes and technologies (including fast and emerging wireless solutions), and the underlying storage technologies. It then discusses grid-integration architectures and operational strategies, from uncontrolled charging and time-of-use incentives to coordinated “smart charging” and V2G, highlighting their impacts on distribution networks and the requirements for communication, aggregation and system operator interaction. Finally, it outlines a future vision where EV flexibility is integrated with other distributed energy resources to provide local voltage support (active and reactive power), congestion management and frequency regulation services, enabled by appropriate standards, market mechanisms, and regulatory frameworks. © Springer Nature Switzerland AG 2026.

Abstract
Energy Storage Systems (ESSs) are an important source of flexibility in power systems with high penetration of Renewable Energy Sources (RESs). When installed at transmission-distribution interface nodes, shared ESSs can support both Transmission System Operators (TSOs) and Distribution System Operators (DSOs), but their long-term planning remains challenging because investment decisions depend on coordinated operation under uncertainty and battery degradation over time. This paper proposes a degradation-aware planning framework for shared battery ESSs in coordinated TSO-DSO operation. The problem is formulated as a bi-level stochastic optimization model in which the upper level determines siting, sizing, and staged investment decisions under investment-cost uncertainty, while the lower level evaluates these decisions through coordinated system operation. To preserve tractability, the framework combines Benders' decomposition for long-term planning with an Alternating Direction Method of Multipliers (ADMM)-based decentralized coordination mechanism for short-term operation. The framework is evaluated on integrated IEEE transmission-distribution test systems over a 15-year planning horizon. Relative to uncoordinated operation, coordinated operation with shared ESSs reduces operating costs by up to 18.25% and RES curtailment by up to 92.16% in the later years of the planning horizon, while eliminating voltage violations. The results also show that degradation materially affects ESS valuation and that temporal discretization can influence siting and sizing decisions.

Abstract
The increasing reliance of modern power systems on heterogeneous renewable energy and decreasing contribution of inertial thermal resources necessitates the availability of planning tools to ensure the continued operational stability of these systems. The abundance of historical data allows the estimation of behaviour during contingencies in common network configurations, but overlooks feasible but rare combinations of generation. Surveys of operation levels at regular intervals can ignore critical areas of operation without high resolution, which requires a significant computational overhead. This paper seeks to address the need for reliable dynamic security assessment to inform grid operator decisions on contingency planning. The aim is to demonstrate the creation of an off-line database that surveys the possible network operation configurations drawing on statistical historical analysis and efficient generic sampling. A high degree of accuracy is achieved in identifying energy mixes that can be expected to result in unstable operation during an unanticipated network outage through the implementation of importance sampling.

Abstract
This paper proposes a stochastic optimization model for industrial hubs to enable their participation in energy markets. The model aims to leverage the resources of multi-energy systems to minimize energy costs in the day-ahead market. It accounts for uncertainties in photovoltaic generation, electrical and heat demand, and outdoor temperatures. A comparison is made with a deterministic approach, along with an analysis of the impact of thermal storage and reserve market participation on costs and bidding strategies. The results show that the stochastic approach is more conservative than the deterministic, while the integration of thermal storage and reserve services help decrease costs.