Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

This study presents the potential role of thermal power generation in a future power system with high shares of variable generation while considering different sources of demand side flexibility such as heat pumps and heat storages in district heating, demand response from industries and electric vehicles. The study was carried out using a generation planning model combined with a unit commitment and economic dispatch model. The results from the planning model show a strong shift away from combined cycle gas turbines to open cycle gas turbines and gas engines as the share of wind power and solar photovoltaic increases. Demand side flexibility measures pushed this trend further. The results from the unit commitment and economic dispatch model demonstrate that the flexibility measures decrease the ramping frequency of thermal units, while the ramp rates of thermal units remain largely unchanged or increased. This indicates that the flexibility measures can cover smaller ramps in the net load more cost‐effectively but that thermal power plants are still valuable for larger ramps. Impacts on emissions and electricity prices are also explored.

As power systems evolve towards integrating higher shares of renewables, the demand for additional levels of flexibility is increased. Meanwhile, o‐ther energy consuming sectors, such as transport and heating, could provide flexibility when they move from fossil fuels to electricity. In this paper, the impact of a range of flexibility measures is assessed for the island system of Ireland, with a high share of renewable energy, particularly wind and solar. Flexibility measures studied include hybrid heating in domestic and industrial processes, smart charging of electric vehicles, renewable hydrogen, power to ammonia, peak shaving demand response and batteries. The novelty of this paper lies in directly quantifying the interactions and dependencies between different flexibility measures, with the objective of increasing the operational flexibility of an increasingly renewable energy‐dominated power system. Four different scenarios are modeled to explore this interplay between the different flexibility measures. The costs and benefits of several sector‐coupling measures. The scenarios have also been compared in terms of their influence on system inertia, renewable energy curtailment and non‐synchronous penetration levels. The results indicate the potential importance of electricity‐based heating in the industrial sector, smart charging of electric vehicles, batteries and power‐to‐ammonia, as part of achieving future targets