Tariff-based load shifting for domestic cascade heat pump with enhanced system energy efficiency and reduced wind power curtailment.

• Tank size and temperature set point of 1.2 m3 and 75 °C are optimal system design. • Should charge storage at 3am and 2pm for morning and afternoon demands, respectively. • The best load shifting positively affects the grid. • Achieve running costs and CO 2 savings with the best load shifting, compared to oil boilers. Cascade air-to-water heat pumps may have good potential for retrofitting UK domestic buildings because they can directly replace existing fossil-fuel boilers without the requirement of considerable modifications to heat distribution systems. A widespread uptake of these heat pumps, however, would pose challenges to the grid. Furthermore, wind power generation has increased in the UK to achieve the target of decreasing CO 2 emissions by 2050, but there are high levels of wind curtailment due to the mismatch between electricity supply and demand. In this paper, a load shifting study for cascade heat pumps coupled with thermal energy storage addressing these issues is presented. The main objective is to find the best tariff-based schedule load shifting for cascade heat pumps, which can help to avoid peak demand periods while obtaining enhanced system energy efficiency with minimised running costs and reduced wind energy curtailment. How the retrofit performance of the cascade heat pumps with load shifting is further investigated. TRNSYS was used to simulate the system performance validated against experimental results. Northern Ireland (UK) was selected as the evaluated scenario. Simulation results showed that the tank temperature set point of 75 °C and the storage size of 1.2 m 3 could wholly shift the cascade heat pumps' operation to off-peak periods. The best times to start the cascade heat pumps to charge the storage were at 3 am and 2 pm for the morning and afternoon heating demands, respectively. Compared to oil boilers, the cascade heat pumps with load shifting could obtain lower running costs (16–34%) and carbon emissions (20–37%). [ABSTRACT FROM AUTHOR]