Power systems must constantly maintain a balance between the instantaneous supply and demand for electricity. Coming technologies such as energy storage and demand-side management promise to make a significant contribution to this balancing challenge. The concept of demand-side management involves the ability of power utilities to influence electricity usage at consumers' premises either through direct control via a telecommunications system, or indirectly through incentives which are usually economic such as variable pricing tariffs. An electrical energy storage unit (such as Tesla's recently announced 'Powerwall', a rechargeable lithium-ion battery product for home use which stores electricity for domestic consumption, load shifting, and backup power) is a buffer used principally or exclusively to counteract the power imbalance between supply and demand. Energy storage technologies are typically reliable and always available, but this is not necessarily true for demand-side management solutions. The proposed research will explore the dynamic, multi-player, economic and operational 'games' arising when energy storage and demand-side management technologies are applied to power system balancing. We will use a game-theoretical approach to model this, combined with useful mathematical techniques borrowed from the statistical mechanics of complex systems and techniques developed for the analysis of complex networks. The operators of these technologies, as well as the entity responsible for balancing, are treated as agents within one or more markets for electricity. An important concept of solution in the study of these non-zero sum dynamic games is the so-called Nash equilibrium, in which no single player can improve their outcome by altering their decision unilaterally. In other words, a Nash equilibrium is a state in which no player can improve their situation by changing to another strategy. Equilibria are desirable in this context of balancing because they represent sustainable and stable setups. We will investigate the properties of these equilibrium states for a variety of stochastic models relevant in the load balancing context. By studying dynamic games we will address two fundamental research questions: firstly, how the operators of such new technologies should optimally act, and secondly how they should be appropriately rewarded in order to produce a suitable dynamic equilibrium in the balancing service they can provide. Further, by appropriately extending these games to networks we will explore how the dynamic equilibria change when such technologies are aggregated through third parties. In the most ambitious part of this proposal we will explore the effect of multiplex and evolving network topology when, for example, participation in load balancing is influenced by the participation of peers.

Smart local energy systems offer the new opportunity to unlock valuable demand flexibility from owners of distributed energy technologies, such as electric vehicles, home batteries and heat-pumps. When combined with consumer-level ICT infrastructure, these resources allow previously passive consumers to become 'prosumers' - consumers who can proactively manage their consumption, production and storage of energy. The smart local energy system demonstrators are expected to generate a range of local energy markets and platforms, offering new opportunities for prosumers to actively engage with the energy system. A wide variety of designs and business models for these markets and platforms are possible. Platforms are already operating that aggregate groups of prosumers and offer balancing services to National Grid. New markets for local flexibility services could enable prosumers to help manage voltage and thermal constraints, contributing to distribution system resilience. Markets for direct peer-to-peer energy trading have also been proposed, which would offer a win-win for prosumers, and the system as a whole, by facilitating the use of flexible resources to help match local supply and demand. To ensure local energy markets create value locally, and can successfully scale up, energy market and regulatory arrangements will need adjustment. The major opportunity is for local energy markets to be integrated at the national scale, with clean local energy and flexibility reducing the need for large investments in generation and transmission infrastructure. Achieving this scale-up will require new market design frameworks and supporting technologies, with prosumer preferences and behaviours of central importance. The project aims to answer the research question: "How can local and system-level energy markets be designed to successfully integrate local clean energy systems at the national scale?" High performance computing will be used for large-scale simulation, to study the interactions between local energy markets operating in parallel at different time scales and physical scales. This will facilitate the design of new local and system-level coordination mechanisms and policies, and allow their impact to be evaluated. The project will enhance the value offered by the Energy Revolution Research Consortium by providing novel insights and quantitative evidence which can be shared with the smart local energy system demonstrators as well as policy-makers.

The aim of this fellowship is to answer a key research question for power systems engineering: "As the UK and other countries move towards transport electrification, how can potentially millions of electric vehicles be successfully integrated into power system operations?" Electric vehicles have become increasingly cost competitive, due to the cost of lithium-ion battery packs falling by approximately 77% over the last 6 years. The UK has over 100,000 electric vehicles, but it is estimated 26 million will be needed to meet 2050 emissions targets. The UK government is strongly supporting this, announcing a ban on the sale of diesel and petrol cars and vans after 2040, and the Faraday Challenge, £246 million towards electric vehicle battery development. If electric vehicle charging is left uncoordinated, the large-scale adoption of electric vehicles is expected to cause significant power system challenges. Peak demand is expected to increase on the order of 20GW (approximately a 40% increase), necessitating new power plants and large-scale transmission infrastructure upgrades. A significant impact is also expected at the local distribution network level. The My Electric Avenue project identified that without smart charging, transport electrification will necessitate new investment to reinforce 32% of UK low voltage distribution network feeders (312,000 feeders). This motivates the need for smart charging - coordinated scheduling of the charging times and powers of electric vehicles. However, existing strategies do not facilitate or incentivise this coordination, particularly at the local distribution network level. Top-down regimes that directly curtail charging impose an external cost on electric vehicle owners and manufacturers, and will slow adoption. Mechanisms that instead incentivise coordination are a promising approach, but require careful engineering design, since they influence power system operation in real time. Through this fellowship, a networked market platform will be designed which can incentivise aggregate and localised coordination between millions of electric vehicles, while managing local power network voltage and thermal constraints in real time. This will be achieved by combining recent advances in multi-agent control, power engineering and networked matching market theory, to design new algorithms suitable for large-scale implementation. The project is supported by two industry partners, EDF Energy, the second largest electricity supplier in the UK with over 5 million customers, and Upside Energy, a UK virtual demand side response aggregator. The proposed market platform has the potential to provide significant value by alleviating the need for generation and transmission infrastructure investments, increasing network efficiency and increasing energy security.

The aim of this fellowship is to answer a key research question for power systems engineering: "As the UK and other countries move towards transport electrification, how can potentially millions of electric vehicles be successfully integrated into power system operations?" Electric vehicles have become increasingly cost competitive, due to the cost of lithium-ion battery packs falling by approximately 77% over the last 6 years. The UK has over 100,000 electric vehicles, but it is estimated 26 million will be needed to meet 2050 emissions targets. The UK government is strongly supporting this, announcing a ban on the sale of diesel and petrol cars and vans after 2040, and the Faraday Challenge, £246 million towards electric vehicle battery development. If electric vehicle charging is left uncoordinated, the large-scale adoption of electric vehicles is expected to cause significant power system challenges. Peak demand is expected to increase on the order of 20GW (approximately a 40% increase), necessitating new power plants and large-scale transmission infrastructure upgrades. A significant impact is also expected at the local distribution network level. The My Electric Avenue project identified that without smart charging, transport electrification will necessitate new investment to reinforce 32% of UK low voltage distribution network feeders (312,000 feeders). This motivates the need for smart charging - coordinated scheduling of the charging times and powers of electric vehicles. However, existing strategies do not facilitate or incentivise this coordination, particularly at the local distribution network level. Top-down regimes that directly curtail charging impose an external cost on electric vehicle owners and manufacturers, and will slow adoption. Mechanisms that instead incentivise coordination are a promising approach, but require careful engineering design, since they influence power system operation in real time. Through this fellowship, a networked market platform will be designed which can incentivise aggregate and localised coordination between millions of electric vehicles, while managing local power network voltage and thermal constraints in real time. This will be achieved by combining recent advances in multi-agent control, power engineering and networked matching market theory, to design new algorithms suitable for large-scale implementation. The project is supported by two industry partners, EDF Energy, the second largest electricity supplier in the UK with over 5 million customers, and Upside Energy, a UK virtual demand side response aggregator. The proposed market platform has the potential to provide significant value by alleviating the need for generation and transmission infrastructure investments, increasing network efficiency and increasing energy security.

This project aims to model demand-side flexibility coming from aggregation of a large number of residential and small and medium-size commercial end-users in the distribution network (DN). The algorithms developed through this project will facilitate more flexible operation of the DN by assessing the time varying capacity available from flexible loads, in response to flexible services currently procured by the distribution system operator (DSO), namely: Sustain, Secure, Dynamic and Restore. The aggregate flexibility will be described as the amount of available capacity and its duration, as a result of aggregating individual loads with different operating modes, start times, maximum deferral times, etc., driven by the end-users' daily behaviour and constrained by their comfort. Such flexibility profiling, corresponding to that of larger flexible resources already employed in practice (e.g., distributed generators or storage), will make provision of multiple flexible services accessible to small and medium-size end-users. This will result in increased flexibility of the DN as a whole. Furthermore, harnessing flexibility potential of residential and commercial users would have significant environmental implications, as these contribute to a large share to both, electrical usage and global greenhouse gas emissions. The findings of the project could be further complemented with smart meter data to develop tariffs and incentives for residential and commercial users, supporting more coordinated procurement of flexibility by reducing uncertainty of efficiency and outcome of the demand response (DR) programmes. The main beneficiaries of the research would be DSOs, aggregators and other DR responsible parties at the DN level. The question of flexibility modelling is not only important for reporting DR potential at the demand side (commonly, an aggregator's role), but also for more confident estimation of the outcome of DR programmes, tariff design and flexibility assessment, which are highly relevant to DSOs. One of the main benefits for DSOs brought by this project would be in supporting decision making when investing into incentives and infrastructure allowing network-wide control of flexible loads.