Understanding to what extent the emergence of prosumers and prosumagers organized in energy communities can impact the organization and operation of power grids has been one of the major recent research avenues at the European level. In renewable-based communities aiming to reach some level of energy self-sufficiency, a key issue to be addressed is assessing how the presence of end-users playing different roles in the system (self-consuming, producing and trading, performing demand management, etc.) can influence the overall system performance. In this setting, this paper combines Distributed Artificial Intelligence and optimization approaches to assess how prosumagers and consumers pursuing different goals can influence the energy self-sufficiency of a local energy community. The residential demand is accurately modeled, and the agents’ preferences are considered in the modeling to represent a smart community. The results show that although energy community members may have conflicting individual goals, the overall system self-sufficiency can be maximized with economic benefits for all stakeholders, thus illustrating the advantages of energy communities.

Power systems have undergone major changes, mainly due to the increasing penetration of renewable distributed generation and levels of automation. Prosumers have the capability to become (almost) independent of the grid and can exchange energy with other community members. In this setting, it is relevant to exploit generation/demand flexibility from an energy community perspective, including multiple agents that exchange and manage the available energy resources in an integrated manner. Agent-based modeling (ABM) tools have been increasingly used to model complex energy systems, since they are especially suited to model systems influenced by social interactions between agents that are flexible, autonomous and proactive. This paper aims to present the initial development stage of a modelling approach to simulate energy trading between two energy community members capable of exchanging information and energy between them. Particular attention is paid to the influence of end-users' behaviors on demand-side flexibility.

The evolution of the construction sector over the years has been marked by the replacement of high thermal inertia mass constructions by increasingly lighter solutions that are subject to greater thermal fluctuations and, consequently, thermal discomfort. To minimize these effects, energy demanding space conditioning technologies are implemented, contributing significantly to the sector’s share of global energy consumption. Enhanced constructive solutions involving phase-change materials have been developed to respond to the constructive thermal inertia loss, influencing buildings’ thermal and energy performance. This work aims to model the evolution of the construction over the last decades to understand to what extent constructive characteristics influence the occupants’ thermal comfort. For this purpose, typical and enhanced solutions representing distinct constructive periods were simulated using the EnergyPlus^® software through its graphical interface DesignBuilder^® and the thermal comfort of the different solutions was evaluated using the adaptive model for thermal comfort EN16798-1. The main results reveal that more restraining regulatory requirements are indeed mitigating thermal discomfort situations. However, overheating phenomena can rise, creating worrying consequences in the short-medium term. Thus, countries with mild climates such as Portugal, must pay special attention to these effects, which may be aggravated by climate change.

The emergence of energy communities is expected to reshape the design of the electricity system at the same time as peer-to-peer (P2P) trading is transforming the traditional utilities business models. In this setting, this work proposes a multiagent framework endowed with optimization tools to model P2P electricity trading within an energy community. Emphasis is given to the inclusion of vulnerable consumers and the economic outcomes of P2P transactions for community members, while fairness concerns are considered in the distribution of the existing energy resources.