Distributed energy resources are an ideal candidate for the provision of additional flexibility required by the power system to support the increasing penetration of renewable energy sources. The integrating large number of resources in the existing market structure, particularly in the light of providing flexibility services, is envisioned through the concept of virtual power plant (VPP). To this end, it is crucial to establish a clear methodology for VPP flexibility modelling. In this context, this paper first puts forward the need to clarify the difference between feasibility and flexibility potential of a VPP, and then propose a methodology for the evaluation of relevant operating regions. Similar concepts can also be used to modelling TSO/DSO interface operation. Several case studies are designed to reflect the distinct information conveyed by feasibility and flexibility operating regions in the presence of slow and fast responding resources for a VPP partaking in the provision of energy and grid support services. The results also highlight the impact of flexible load and importantly network topology on the VPP feasibility (FOR) and flexibility (FXOR) operating regions.Index Terms-Active distribution networks, flexibility, frequency control ancillary services, TSO/DSO interface, virtual power plant. arXiv:1906.05472v1 [eess.SY]

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

The increasing uptake of residential PV-battery systems is bound to significantly change demand patterns of future power systems and, consequently, their dynamic performance. In this paper, we propose a generic demand model that captures the aggregated effect of a large population of price-responsive users equipped with small-scale PV-battery systems, called prosumers, for market simulation in future grid scenario analysis. The model is formulated as a bi-level program in which the upper-level unit commitment problem minimizes the total generation cost, and the lower-level problem maximizes prosumers' aggregate self-consumption. Unlike in the existing bi-level optimization frameworks that focus on the interaction between the wholesale market and an aggregator, the coupling is through the prosumers' demand, not through the electricity price. That renders the proposed model market structure agnostic, making it suitable for future grid studies where the market structure is potentially unknown. As a case study, we perform steady-state voltage stability analysis of a simplified model of the Australian National Electricity Market with significant penetration of renewable generation. The simulation results show that a high prosumer penetration changes the demand profile in ways that significantly improve the system loadability, which confirms the suitability of the proposed model for future grid studies.

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