Techno-economic and business case assessment of multi-energy microgrids with co-optimization of energy, reserve and reliability services

Abstract

In this work a new techno-economic framework to model and assess business cases for energy, reserve and novel reliability services provided by Microgrids (MGs) is presented. The framework combines a bespoke Transactive Energy (TE) approach that aims at co-optimizing these potentially conflicting services. In this context, MGs aggregate, coordinate and exploit flexibility from emerging distributed energy resources and multiple energy vectors (e.g., electricity, heat and gas) as a means to partake in different services in response to price signals associated with markets and network needs. For example, MGs can provide reliability services to both the distribution network and their internal customers, owing to their ability to ride through contingencies by operating as islands. Further, MGs could coordinate with the network restoration scheme to reconnect to the network after a contingency occurs, and use their spare generation capacity to restore ‘blocks’ of other affected customers outside the MG. This novel application for MGs to improve network reliability has not yet been quantified from an economic perspective, especially in a TE context where conflicts with other services may arise. In this regard, it is clear that energy, reserve and reliability services may be economically attractive under specific conditions when assessed in isolation. However, their business case is still unclear in a pragmatic context where the provision of given services affects the economic operation of MGs, and may keep them from partaking in other services. On the above premises, this paper proposes a framework that combines a bespoke Mixed Integer Linear Programming (MILP) model for the operation of MGs, and a stochastic approach for simulating nonlinear and dynamic reliability price signals in light of MG reliability contributions assessed through Monte Carlo simulation. The framework is demonstrated on case studies based on pragmatic energy information, a real UK distribution network, sets of price signals for co-optimization of different services, and multi-energy MGs designed with Combined Heat and Power (CHP) units, Photovoltaic (PV) panels, Gas Boilers (GBs). Thermal Energy Storage (TES) and/or Battery Energy Storage (BES). The results demonstrate that, even though the operation schedule of devices within aMG can change based on the different technologies and price signals under consideration, the services are largely synergistic. This is a key finding, as it demonstrates that, for example, even without price signals from a reliability service the MG will have significant spare export capacity which, if accessible to the DNO, can improve the reliability of customers outside the MG.