Multienergy systems (MES), in which multiple energy vectors are integrated and optimally operated, are key assets in low-carbon energy systems. Multienergy interactions of distributed energy resources via different energy networks generate the so-called distributed MES (DMES). While it is now well recognized that DMES can provide power system flexibility by shifting across different energy vectors, it is essential to have a systematic discussion on the main features of such flexibility. This article presents a comprehensive overview of DMES modeling and characterization of flexibility applications. The concept of “multienergy node” is introduced to extend the power node model, used for electrical flexibility, in the multienergy case. A general definition of DMES flexibility is given, and a general mathematical and graphical modeling framework, based on multidimensional maps, is formulated to describe the operational characteristics of individual MES and aggregate DMES, including the role of multienergy networks in enabling or constraining flexibility. Several tutorial examples are finally presented with illustrative case studies on current and future DMES practical applications.

Multienergy systems (MES) can optimally deploy their internal operational flexibility to use combinations of different energy vectors to meet the needs of end-users and potentially support the wider system. Key relevant applications of MES are multienergy districts (MEDs) with, for example, integrated electricity and gas distribution and district heating networks. Simulation and optimization of MEDs is a grand challenge requiring sophisticated techno-economic tools that are capable of modeling buildings and distributed energy resources (DERs) across multienergy networks. This article provides a tutorial-like overview of the state-of-the-art concepts for techno-economic modeling and optimization of integrated electricity-heat-gas systems in flexible MEDs, also considering operational uncertainty and multiple grid support services. Relevant mixed integer linear programming (MILP) formulations for two-stage stochastic scheduling of buildings and DER, iteratively soft-coupled to nonlinear network models, are then presented as the basis of a practical network-constrained MED energy management tool developed in several projects. The concepts presented are demonstrated through real-world applications based on The University of Manchester MED case study, the details of which are also provided as a testbed for future research.

Power systems have typically been designed to be reliable to expected, low-impact high-frequency outages. In contrast, extreme events, driven for instance by extreme weather and natural disasters, happen with low-probability, but can have a high impact. The need for power systems, possibly the most critical infrastructures in the world, to become resilient to such events is becoming compelling. However, there is still little clarity as to this relatively new concept. On these premises, this paper provides an introduction to the fundamental concepts of power systems resilience and to the use of hardening and smart operational strategies to improve it. More specifically, first the resilience trapezoid is introduced as visual tool to reflect the behavior of a power system during a catastrophic event. Building on this, the key resilience features that a power system should boast are then defined, along with a discussion on different possible hardening and smart, operational resilience enhancement strategies. Further, the so-called ΦΛEΠ resilience assessment framework is presented, which includes a set of resilience metrics capable of modeling and quantifying the resilience performance of a power system subject to catastrophic events. A case study application with a 29-bus test version of the Great Britain transmission network is carried out to investigate the impacts of extreme windstorms. The effects of different hardening and smart resilience enhancement strategies are also explored, thus demonstrating the practicality of the different concepts presented.