Incentivising and Activating Multi-Purpose Flexibility for the Future Power System

The green transition and the electrification that comes along with it, call for huge investments in infrastructure. Traditional energy systems are operated and planned such that the production follows the demand. Similarly, investment needs in e.g., distribution grids, are typically planned according to the future electricity demand, the number of electric vehicles, and the renewable capacity connected to the distribution grid. However, in the era of high penetration of intermittent renewable energy supply, the focus has to shift towards demand-side flexibility. A pivotal development refers to harnessing and integrating the available flexibility of virtually all types of end-users on all aggregation levels, including from other sectors (cf. the energy-water nexus). Such unprecedented levels of complexity call for massive digitalization of energy systems using data-sharing
principles, AI, big data analytics, data-driven digital twins, cloud-fog-edge computing, systems-of-systems, IoT, resilience and user-involvement using apps and Smart Energy Management systems. This paper outlines the large economical benefits of demand-side flexibility both with respect to direct savings related to infrastructure investment and indirect savings for the consumers through cheaper electricity prices and lower grid costs. It is argued that one of the main barriers for the green transition and for achieving these benefits is the existing regulatory framework and most importantly the existing tariffs and energy taxes. Another challenge is the conventional market design which is a barrier for activating flexibility both locally at DSO-levels and in multi-energy carrier settings. The paper will outline principles for proper tariffs and energy taxes as well as new disruptive methodologies needed for integrating flexible assets into energy markets. It will be argued that for a bulk part of the flexible assets, we need to use dynamic pricing, and the actual price should be linked to the real operational challenges and costs of e.g., the distribution grids. A key element is the so-called flexibility function for describing the flexibility of the assets. The methodologies are embedded into the Smart-Energy Operating System (OS), which is a hierarchical framework for coherent digitalization of energy systems consisting of aggregation, forecasting, control and optimization. The framework represents new solutions for activating local flexibility. The framework can seamlessly accommodate different behind-the-meter resources (e.g., electric vehicles, heat pumps, etc.), as the distributed flexibility is activated indirectly simply by broadcasting a dynamically changing price signal, overarching the nature of the distributed resources. This ensures simplicity and transparency while keeping the users in control. The intention is not to replace existing methods for direct activation, but to enrich them through indirect, efficient, and scalable activation of distributed flexibility.