Optimization of a gas-steam-electric system integrated with a solar power tower plant in a steel company

The iron and steel industry, characterized by substantial energy consumption and significant carbon emissions, faces pressing challenges such as overcapacity and the urgent need for technological innovation and transformation. To address these issues, this study proposes an integrated energy solution that combines a sensible heat storage device, a solar power tower plant, and conventional heat-to-electricity conversion units. A multi-material and multi-energy flow optimization model based on a gas–steam–electric system is developed, employing a two-stage optimization design methodology. In the initial stage, the optimal scale of the energy storage system is determined to maximize the financial benefits. In the second stage, a solar power tower plant (SPTP) is integrated with a combined heat and power (CHP) unit to further enhance system efficiency, economic performance, and carbon reduction. Three scenarios are evaluated: Scenario C1 serves as the initial optimal design; Scenario C2 builds on C1 by incorporating energy storage devices of varying capacities with select units; and Scenario C3 builds upon C2 by coupling the solar power tower plant with a CHP unit. Under single-objective optimization, compared with Scenario C1, Scenarios C2 and C3 yield additional profits of 7.46 × 103 and 5.28 × 104 CNY/day, with payback periods of 4.89 and 16.61 y. In multi-objective optimization, compared with C1, scenario C3 can realize a daily income of 5.19 × 105 CNY and reduce carbon emissions by 98.65 t/day. A sensitivity analysis of the solar power tower plant unit indicates that increasing the size of the new energy unit enhances both economic benefits and CO2 emissions reductions. However, expanding the capacity of the energy storage system (ESS) does not consistently yield proportional improvements. This study also explores the synergistic operational dynamics of the integrated energy system and reveals the operational behavior of each device under varying production demands through scenario-based simulations.