Smart Energy Systems
Motivated by the urgency to move away from conventional fossil fuels to alternatives, we research many diverse aspects of energy systems within the group. These topics cover a large range of scales, from domestic to networked generation plants across entire regions.
Intermittent energy sources (including PV, wind and tidal) pose a great challenge to conventional electrical systems, particularly in the area of balancing supply and demand. Relying on chemical batteries alone to address this problem may be too expensive. Our research is focused on identifying the optimum combination of energy storage technologies for systems ranging from stand alone to conventional grid networks. By using electrochemical technologies alongside alternatives, such as thermal energy storage, a more economic solution may be found. At the small scale, one particular interest is the application of thermal energy storage (latent and sensible heat) to domestic fridges. By implementing a heat recovery system it is possible to exploit the thermal energy that would otherwise be wasted.
We are also concerned with quantifying the performance of energy systems using a wide array of tools: life-cycle-analysis to measure carbon footprint, numerical simulation to aide component selection and cost-function optimization for economic decision-making.
A list of relevant research is as follows:
Demand Side Management
Demand Side Management (DSM) is a key component in the concept of Smart Grid. It is often used by utility companies to optimize the energy consumption at the user end to match the available and planned generation resources. One of the key function for DSM is to shift the load demand from peak time to those of off-peak time, smoothing the demand curve and reducing the peak demand of the day. This can bring two benefits to the network:
- As a power system's capacity is determined by the maximum demand it can take, reducing the peak demand can alleviate the need to upgrade the power system infrastructure to meet the growing demand.
- As the power loss on the power distribution cable increases to the square of current, shifting the peak demand and smoothing the demand curve can result a lower average loss in the distribution system.
While considering DSM planning, understanding the system's stress (how close the demand is to the capacity of the system) condition and maintaining a good power quality are critical. The researchers in EPG have carried out the study of the network stress and load condition based on the high quality power data from the smart metering infrastructure.
Big Data Analysis
Energy utilities are facing ability to store and control the massive load of data accumulating from smart grid. The opportunity to do something with that data is a crucial “big data challenge” and potentially a much bigger market because tools to mine data can continue to evolve to solve problems for utilities and save them money.
Methods for big data analytics are explored to resolve various energy problems of high complexity, due to the diverse nature of source data (smart meters, PVs, EVs, storage, dynamic pricing, utilities, etc) and the need to mine and fuse smart grid information for a real-time decision making.
The environmental consequences of implementing anaerobic digestion (AD) as a sustainable energy and manure management system for dairy farms is being researched in EPG. This process converts organic material into biogas (mixture of methane and carbon dioxide) and digestate (solid residue), useful as fertiliser.