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This chapter presents the fundamentals and state-of-the-art hosting capacity (HC), including its concept, historical development, considerations, applications, impact factors, and technologies for increasing the HC. It discusses the basics and importance of grid HC, the basic flow chart for HC analysis, the use of HC as a component of integrated distribution planning, and the HC as a process encompassing the input data, analysis, and application of results for informing interconnection and planning. Moreover, this chapter depicts two types of HC analysis based on the number of distributed energy resources (DERs) and load conditions (i.e., operating scenarios): static and dynamic HC analysis. It presents feeder and node HC levels based on the number of considered DERs. The main impact factors that influence the HC results and hinder the connection of additional DERs to the grid are also described. These impact factors include grid characteristics, DER characteristics, and other considerations such as time, performance metrics, and HC methods. Several review articles on HC and studies that explore the use of battery energy storage systems, electric vehicles, and smart inverters as strategies to increase HC in power distribution networks are presented. Finally, this chapter outlines the conclusion and future search directions for HC analysis. © 2025 Elsevier Inc. All rights reserved.

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This paper addresses the challenges of integrating large shares of renewable energy sources into the power system, focusing on managing operational reserves in multi-area systems and their long-term adequacy. Unlike previous studies, this paper investigates the long-term impact of procurement and activation of operational reserve in adjacent areas, considering energy scheduling and interconnection line constraints. Three procurement schemes for multi-area energy and reserve exchanges are proposed and analyzed through Sequential Monte Carlo Simulation. These schemes vary in their approach to interconnection line capacity constraints and the simultaneous or phased procurement of energy and synchronized reserve. The mathematical operationalization of these schemes is achieved through simple linear programming models, facilitating the quantification of marginal prices for both products. The impact of these schemes on operational reserve adequacy, marginal prices, and interconnection line utilization is demonstrated using configurations of the IEEE RTS 96 system. This analysis incorporates long-term uncertainty and diverse operational conditions and provides valuable insights into the interplay between energy and reserve procurement strategies in multi-area systems.

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Long-term storage expansion planning has usually employed representative days and intra-annual time series aggregation methodologies to reduce the computation complexity. This paper proposes a shift on the approach to the economic evaluation of these systems by implementing an intra-annual time series cost evaluation that considers different uncertainty trajectories. This methodology aims to determine the best possible investment strategies for the available computational budget using strategy game-based decision-making models, as Monte Carlo tree search. The proof of concept is illustrated by a single-bus equivalent test system and compared to a deterministic evaluation for a limited uncertainty model.