Unlocking heat pump flexibility: A multi-objective optimisation approach for self sufficiency and energy costs

The global energy landscape is undergoing a transformative shift towards cleaner, more sustainable, and renewable energy sources. However, the intermittent nature of renewable energy sources, limited storage capacity, and grid transport constraints introduce significant fluctuations in electricity supply and demand. To maintain grid stability and resilience, advanced flexibility measures are required, particularly in medium- to low-voltage networks. Heat pumps, when combined with thermal energy storage, present a promising solution by providing a controllable and adaptive load that aligns with grid conditions. This study explores the theoretical potential of flexible heat pump operation for heating in decentralised energy systems as a strategy for enhancing renewable energy integration and reducing local grid loads. In contrast to previous research that focuses on system design and sizing, this work emphasises optimal operational strategies through a multi-objective optimisation framework. A mixed-integer linear programming based multi-objective optimisation model is developed to simultaneously minimise household energy costs and alleviate strain on the low-voltage grid by optimising the degree of self-sufficiency. The framework incorporates various electrical and thermal synthetic load profiles, building types, living scenarios, photovoltaic system sizes, predefined heat pumps and energy storage capacities. Findings show that leveraging day-ahead energy prices as a demand-response strategy effectively manages price volatility, prevents grid peak loads and consumption, and increases degree of self-sufficiency while reducing energy costs. Results further indicate that the most significant benefits were achieved when using thermal energy storage and heat pumps as primary flexibility measures.