Our Research

Our research spans power and energy system modelling (transmission and distribution), techno-economic modelling, integration of low-carbon technologies, and Smart Grids. Key research work streams include:

Techno-Economic Modelling and Optimisation of Integrated Energy Systems

We develop state-of-the-art models and tools that address optimal operation and planning of future energy systems from technical and economic perspectives. These include:

  • operational modelling of multi-energy systems: electricity, gas, hydrogen, heat, cooling, water and transport
  • planning under the uncertainty of large-scale integrated energy systems
  • multi-commodity co-optimisation, business case assessment and market analysis for energy technology portfolios such as community energy systems, smart districts, grid-connected and distributed energy storage, demand response, microgrids, and virtual power plants
  • large-scale multi-market clearing, for example, of energy, frequency control ancillary services, and fast frequency response provided by distributed energy resources.

Smart Grids: Grid Integration of Distributed Energy Resources (DER)

The distribution network supplies electricity directly from the transmission system to end users and has been historically designed for unidirectional power flows and with very limited observability. This infrastructure that delivers electricity to our houses, shops, buildings, etc, will need to undergo significant developments to cope with the increased levels of small-to-medium scale distributed energy resources (DER) such as solar PV systems, wind farms, storage, and electric vehicles, and to make the most of large amounts of data.

From the highly granular and detailed modelling of medium and low voltage networks and DER technologies, to the stochastic quantification of whole-network impacts due to high DER penetrations, to the exploitation and, more importantly, the identification of the most cost-effective integration solutions for both network operators and end users, we are positioned as one of the strongest groups worldwide. Working directly with electric distribution companies, we provide academic expertise and facilities to test and develop solutions to bring electricity distribution networks into the low-carbon future.

Smart Grids: Data-Driven Approaches for the Operation and Planning of DER-Rich Distribution Networks

Residential distributed energy resources (DER) such as solar PV systems, batteries, and electric vehicles are installed behind the meter of mainly single-phase customers connected to three-phase low voltage (LV) feeders (eg, 400V line-to-line). This means that for distribution companies to adequately quantify the impacts from reverse power flows due to excess solar PV generation or much higher demand due to electric vehicles, the corresponding electrical models are required. These models are critical when calculating voltages given the non-linear and unbalance nature of LV feeders. However, the task of producing electrical models of thousands of LV feeders is already a significant challenge for distribution companies around the world, which, in turn, makes the operation and planning of PV-rich LV networks even more challenging. It is in this context that the exploitation of historical smart meter data can not only help distribution companies with their modelling tasks but also provide radical alternatives to how they operate and plan future DER-rich LV networks.

Working directly with electric distribution companies and taking advantage of historical smart meter data, we are at the forefront of demonstrating that is possible to capture the physics of three-phase LV circuits and create a model-free approach to calculate voltages. These model-free calculations can be used to estimate the maximum power exports or imports of individual customers (also known as operating envelopes) as well as to assess the impacts (or hosting capacity) of residential solar PV or electric vehicles.

Multilevel Power Electronics Converters

Multilevel converters play a pivotal role in the burgeoning field of high-power grid applications, encompassing renewable power plants, energy storage, FACTS, HVDC, and more. Our research delves into modulation strategies and operational aspects of prominent multilevel converter topologies, including cascaded H-bridge, flying capacitor, diode-clamped, and modular multilevel converters. We are curious about control challenges associated with operating converters under extreme conditions of reduced inertia, aiming to minimise size and cost. Some of the challenges stem from non-negligible ripple components on DC capacitors, necessitating the use of advanced model-based control techniques to ensure stable operation. Notably, we are leading the research on low-capacitance cascaded H-bridge StatCom systems.

Grid-Friendly Photovoltaic Power Plants

Traditionally PV power plants have been viewed as unwanted disturbances, posing challenges to power system stability. The responsibility for power system stability has long been shouldered by conventional power plants. However, with the ever-increasing share of PV generation, they are gradually assuming a more significant role in ensuring grid stability. Accordingly, PV power plants control is evolving from uncontrolled maximum power point tracking to a more flexible reserve power point tracking. Maintaining some dispatchable reserve power is crucial to effectively respond to power grid contingencies. Our research explores algorithms for rapidly controlling PV power output, whether with or without energy storage, paving the way for the implementation of inverter control with grid support functionalities.

Optimal Operation and Control of Low-Carbon Power Systems

Most renewable energy sources are highly variable and partly unpredictable, and low-carbon technologies (including storage and electric vehicles) are typically asynchronously connected to the system. This introduces active and reactive supply-demand challenges to ensure secure power system operation over different time scales, from sub-second to minutes and hours. New operational models and tools are needed to run low-carbon, low-inertia power systems and markets. We work at the interface between control, power systems, and energy markets, developing models such as:

  • resource scheduling with pseudo-dynamic security constraints in low-inertia networks
  • scenario-based optimal power flows with model predictive control and chance constraints
  • provision of dynamic services from aggregation of new technologies, including FACTS and HVDC
  • distributed optimisation-based frequency control with centralised and highly decentralised technologies, such as thermostatic loads and energy storage devices

Reliability and Resilience of Future Energy Infrastructure

Low-carbon power systems require new technologies and approaches to provide reliable services that were traditionally supplied by conventional power plants. In addition, there is an increasing need to incorporate high-impact low-probability events in operation and planning of future energy infrastructure, to cope with extreme events, such as weather events from climate change. Our research aims to systematically model the risk profile of future systems—comprising renewables and smart grid technologies—to assess their reliability and resilience and how new concepts, such as microgrids and virtual power plants, can support renewables-based power systems.

Smart Grids: Future Distribution System Operators (DSOs)

For Smart Grids to truly emerge, traditional electric distribution companies need to evolve into engaged, flexible Distribution System Operators (DSOs) in which network elements and participants (consumers, generators, and those that do both) are actively managed to fulfill technical, economic, and environmental objectives. This requires advanced Distribution Network Management Systems as well as adequate operational architectures to ensure coordination across the whole power system.

We are leading in this area by investigating the large-scale applicability of centralised and hierarchical real-time control techniques, including the use of multi-voltage level unbalanced Optimal Power Flow. Our research is also looking at the diverse interactions and unexpected consequences (eg, network issues) resulting from the future provision of bottom-up services, ie, end users with flexible elements (such as storage) providing services (eg, energy, active/reactive power, voltage regulation) to the national system operator or even the DSO. Understanding these interactions will be key to determining the most adequate architecture for the implementation of future DSOs.