Presentation on theme: "Energy Demand and Energy Networks Energy Academy, School of Energy, Geosciences, Infrastructure and Society 9th September 2014 Dr David Jenkins and Dr."— Presentation transcript:
Energy Demand and Energy Networks Energy Academy, School of Energy, Geosciences, Infrastructure and Society 9th September 2014 Dr David Jenkins and Dr Joel Chaney
Urban Energy Research Group Active since 2004 Multi-disciplinary group Core research topics of: Energy demand data profiling Adaptation to future climates Energy systems and networks Building performance simulation/modelling Fuel poverty Life-cycle carbon analysis @HWUrbanEnergy
ARIES Project Adaptation and Resilience In Energy Systems University of Edinburgh (supply-side) and Heriot-Watt University (demand-side) Modelling the effect of climate and future conditions on energy demand, supply and infrastructure What problems might occur that are caused or exacerbated by climate change?
Energy Supply Transmission/ Distribution Energy Demand Change of resource (e.g. wind/tidal/solar) Ability of generation portfolio to react Effect of climate shocks on system Reduced heating Increased cooling New technologies Change in peak demand
The effect of scenarios on demand...
Energy efficient lighting, e.g. LED ?
Charge cycle of electric vehicles?
Continuing rise in consumer electronics?
APAtSCHE Project- UK EPSRC Project Enabling the elderly to access energy innovation
Improved Occupancy sensing and Smart Thermostats If you can predict when people are in the house you can dynamically tune their programmable thermostat setting for them as the season and their habits and schedules change. Combine multiple low cost sensor hardware (examples only) Use machine learning based time-sequence pattern recognition in order to classify activity detected. Determine change in occupancy Occupancy probability function
ORIGIN Project Programmed setting by occupant Occupancy probability function Modified schedule ON OFF ON OFF ON OFF
ORIGIN Project- EU FP7 Project Orchestration of Renewable Integrated Generation In Neighbourhoods
Weather Prediction Forecast and observation data for c37 sites Capture local data and from weather direction Every hour predict next 24 hours weather at hourly precision Multiple linear regression
Knapsack modelling approach
Available expertise Understanding of energy demand and networks: Demand response Effect of technology change Climate change Occupancy sensing Using machine learning to identify patterns in energy behaviour. Energy sensing and control Energy user interface design