Operational optimisation of a heat pump system with sensible thermal energy storage using genetic algorithm

• Main Authors: Schellenberg Christoph, Lohan John, Dimache Laurentiu
• Format: Article
• Language: English
• Published: VINCA Institute of Nuclear Sciences 2018-01-01
• Series: Thermal Science
• Subjects: electrification; smart energy; heat pump; demand flexibility; thermal storage; optimisation
• Online Access: http://www.doiserbia.nb.rs/img/doi/0354-9836/2018/0354-98361800272S.pdf

Heating and cooling account for 50% of global energy consumption and 40% of energy related CO2 emissions. Progress towards renewable heating has been slow, and Ireland is expected to miss European Union 2020 emission reduction and renewable energy targets. While increased wind penetration since 2005 has reduced the carbon intensity of Ireland’s electricity by 29%, carbon intensity per used floor area is more than twice the European average, amplifying air pollution, climate change, and energy security issues. The heating and electricity sectors can benefit from the successful transition to cleaner, lower carbon electricity by electrifying heating. Electricity-driven heat pumps deliver 3-4 units of heat per unit of electricity consumed, there by offering a 76% emission reduction compared with fossil-fuelled heating. This research offers an opportunity to minimise both running cost and emissions, assisting the end user and the environment. This is achieved using the smart grid to charge a thermal store during favourable low-cost times and discharge as required later. Smart, information and communication technology-integrated, adaptive control with artificial intelligence optimises the heat pump schedule based on information from forecasting services and/or predictions of heat demand, heat pump source quality, stored heat and day-ahead electricity prices. Another opportunity is the potential to assist the electricity grid by reducing peak electricity demand as smart control favours low electricity prices and low CO2 intensity that coincide with the availability of cheap (wind) electricity. Demand is shifted from expensive peak demand periods, enabling the electrification of heating in a smart energy system.