Multi-objective energy management for modern distribution power systems considering industrial flexibility mechanisms

Abstract

Increasing energy generation from variable and uncertain renewable resources leads to high demand for flexibility procurement from different energy sectors to maintain supply/demand balance in distribution power systems. Industrial energy systems are rapidly emerging as the primary contributor in providing the bulk of said flexibility to the electrical power systems due to their energy capacity, reliable infrastructure, and potential financial benefits. However, there is a lack of available energy management models that help integrate industrial flexibility into the fold and can solve for an optimal operation of the distribution power system. This paper proposes an efficient energy management model that solves a distributed multi-objective optimal power flow for a modern distribution grid, including industrial prosumers and distributed generation resources. We generate two distinct kinds of flexible industrial load profiles: one uses optimal peak shaving with an energy storage system, and the other employs process optimization in the industrial grid. The obtained results show that the proposed energy management model can solve for optimal operation of all involved participants while maintaining data privacy between them. Industrial prosumers save up to 4.85% in financial expenses and 18.6% in energy exchange with the grid. Further, the grid operator can reduce its CO 2 emissions by 4.6%. • Multi-objective distributed optimal power flow as an energy management function for modern distribution power systems connected to distributed energy resources and industrial prosumers. • Generation of flexible industrial load profiles using optimal peak shaving and energy storage systems. • Modelling of voltage-dependent flexible industrial load profiles optimizing industrial production processes.