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This study delved into the creation of a composite phase-change material (PCM), named SBNSC, for potential application in cold storage air-conditioning systems (8–16°C). The composite PCM was formulated using sodium sulfate decahydrate (Na2SO4·10H2O) as the primary PCM, borax as a nucleating agent, ammonium chloride (NH4Cl) as a temperature control additive, sodium hexametaphosphate as a crystal modifier and carboxymethylcellulose as a thickening agent. The D-optimal mixture design was employed to optimize the composition, and this resulted in the identification of an optimal formulation characterized by the most desirable properties. The thermal properties were evaluated using differential scanning calorimetry and revealed a phase-change temperature of 15.40°C. X-ray diffraction analysis confirmed the crystalline nature of the composite PCM. After 100 cooling and heating cycles, the crystallization temperature was 9.50°C, the melting temperature was 15.50°C and the supercooling degree was 0.70°C. The enthalpy values showed an 11.22% decrease, indicating reliable thermal performance. The study concluded that the optimal formulation (SBNSC) exhibits commendable thermophysical properties, demonstrating its potential for effective application in phase-change cold storage air-conditioning systems.

A new concept called virtual inertia scheduling (VIS) is proposed to efficiently handle the increasing penetration of inverter-based resources (IBRs) in power systems. VIS is an inertia management framework that targets security-constrained and economy-oriented inertia scheduling and generation dispatch with a large scale of renewable generations. Specifically, it determines the appropriate power setpoint and reserved capacity of synchronous generators and IBRs, as well as the control modes and control parameters of IBRs to provide secure and cost-effective inertia support. First, a uniform system model is employed to quantify the frequency dynamics of IBR-penetrated power systems after disturbances. Leveraging this model, the s-domain and time-domain analytical responses of IBRs with inertia support capability are derived. Then, VIS-based real-time economic dispatch (VIS-RTED) is formulated to minimize generation and reserve costs, with full consideration of dynamic frequency constraints and the derived inertia support reserve constraints. The virtual inertia and damping of IBRs are formulated as decision variables. A deep learning-assisted linearization approach is further employed to address the non-linearity of dynamic constraints. Finally, VIS-RTED is demonstrated on a two-machine system and a modified IEEE 39-bus system. A full-order time-domain simulation is performed to verify the scheduling results.