In the "dual-carbon" strategy, steel enterprises' energy systems meet changeable electricity demand and rigorous carbon emission rules. This study integrates several types and scales of energy storage devices while optimizing a gas–steam–electric multi-energy network. A mixed integer non-linear programming (MINLP) approach is applied to generate an ideal strategy for energy storage arrangement and a dynamic scheduling technique. Four scenarios are evaluated: Scenario C1 serves as the initial optimal design; Scenario C2 builds on C1 by incorporating molten salt (MS) energy storage device (ESD) with a 25 MW generator set; Scenario C3 incorporate thermal conductive oil (TCO) ESD with a combined cycle power plant (CCPP); and Scenario C4 builds upon C2 by coupling MS–ESD of different scales with CCPP. Comparing scenario C4 with C1, it can be concluded that through ESD configuration, single-objective optimization yields monthly economic benefits of 2.45×10 5 CNY. The C2 scenario enhances the high-efficiency unit's operating ratio through dynamic fuel allocation. Scenario C3 reduces the pressure on the power grid during peak electricity consumption periods. Using multi–objective optimization, ESD can achieve a cumulative economic benefit of 3.15×10 7 CNY and an emission reduction of 3.41×10 5 t CO2 during its lifetime. Through detailed analysis of multi-scenario and multi-cycle optimization results, ESD-1 improves energy efficiency through fuel redistribution, and ESD-2 mainly plays the role of power peaking.
Tan et al. (Sun,) studied this question.
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