Multi-stage optimization flexibility algorithm for demand response in ancillary services. An industrial case study

To ensure that future electrical distribution networks can effectively meet the dynamic demands of the evolving energy landscape due to the penetration of renewable energy sources, the energy-oriented industrial sector has the opportunity to enhance hosting grid capacity in response to short-term requests from system operators. This is achieved by increasing energy resources available to the grid through flexible capacity offers, aiming to prevent periods of system instability. This flexibility has traditionally been provided by large generators on the supply-side, but new opportunities for demand-side flexibility can be integrated into the industrial sector through incentive-based demand response programs. One option is to strategically allocate capacity for balancing service markets through load reduction curves. While large consumers may compete against generators in flexibility-markets, small and medium-sized industries remain largely unexplored. This paper builds on a flexible multi-single machine manufacturing problem and proposes a method for providing day-ahead demand-side flexibility offers combined with price-based real-time pricing demand response. The study is approached from the perspective of a non-intensive industry under an aggregator platform, enabling participation in balancing service auctions. The paper also examines the viability and applicability of flexibility offers within the constraints of low-capacity offers, to determine the optimal flexibility strategy.