Low-medium temperature geothermal energy is a promising stable renewable resource, yet its utilization is often limited by low conversion efficiency. To address this, a novel Organic Rankine Cycle utilizing Liquefied Natural Gas as a cryogenic heat sink is proposed, enabling deep vacuum condensation (> 90% vacuum atmosphere) to maximize power output. Distinct from previous studies that assume ideal vacuum conditions, this work introduces a rigorous gas-liquid mixture model coupled with Vapor-Liquid Equilibrium analysis to quantify the deterioration mechanisms of Non-Condensable Gases (NCG) leakage on system thermophysical and thermodynamic performance. Genetic algorithm optimization reveals that under a 100 degrees C heat source, the system achieves an exergy efficiency of 24.92%, a 29.79% improvement over conventional systems, with a competitive levelized cost of energy of 23.13 $/MWh. However, the leakage sensitivity analysis uncovers that a mere 0.02 mass fraction of NCG results in a precipitous drop in thermal efficiency and a 35% surge in specific investment cost (to 1.09 $/W), driven by heat transfer degradation and back-pressure elevation.

The rapid growth of AI computing demand is driving higher chip power density and a shift toward multi-chip server architectures to boost IT performance. The inter-chip thermal coupling characteristics are becoming increasingly significant, seriously affecting the heat dissipation performance of multi-chip immersion-cooled servers. However, it remains an open issue regarding its comprehensive thermal evaluation and influencing factors. This study developed a multi-dimensional thermal evaluation framework to characterize server thermal performance in terms of thermal safety, hotspot severity, temperature uniformity, and inter-chip thermal coupling strength. Based on this framework, the influencing factors assessment was conducted to quantify the effects of operating conditions (coolant inlet temperature and velocity) and structural designs (lateral chip offset and flow-guide baffle configurations) and to identify effective coupling-mitigation strategies. A threedimensional numerical model of a heterogeneous multi-chip server was developed for heat dissipation performance analysis and it was first validated against experimental data, achieving a maximum deviation below 4.70 % in average chip temperature. The results indicate that inlet temperature mainly governs the absolute temperature level and hotspot severity with limited influence on thermal coupling, whereas increasing inlet velocity improves overall thermal performance with diminishing gains as a critical velocity is approached. Structurally, moderate lateral chip offset and properly designed baffles enhance bypass-coolant utilization and weaken interchip thermal coupling. Among all configurations, the 90 mm full-set baffle delivers the best overall enhancement, reducing the hotspot temperature, thermal non-uniformity coefficient, and downstream thermal resistance by 9.23 degrees C, 4.13, and 0.012 degrees C/W, respectively.

Although radiative cooling technology has shown potential in various fields, existing materials often face limitations in optical performance, environmental adaptability, or fabrication processes, which hinder their largescale practical application. To address these challenges, this study aims to develop a radiative cooling film with high optical performance, strong environmental adaptability, and simple processing, thereby promoting its efficient deployment in building energy conservation and other scenarios. With the goal of developing a radiative cooling film featuring simple fabrication, broad applicability, and excellent optical, hydrophobic, and cooling performance, this paper successfully designed and fabricated a porous PVDF-HFP polymer-based composite film (referred to as PSA) incorporating Al2O3-SiO2 micro-nano particles. By optimizing the material ratio and processing conditions-specifically with an Al2O3 (50 nm) to SiO2 (2 mu m) mass ratio of 1:2 and a PVDF-HFP concentration of 20%-the resulting PSA film demonstrated outstanding optical properties (solar reflectance of 90.25%, infrared emissivity of 97.33%) and hydrophobicity (contact angle of 120.5 degrees). At the same time, it also has good flexibility. For experimental validation, an outdoor cooling test platform was constructed. Under conditions of solar irradiance at 966 W/m2, humidity of 59%, and wind speed of 1.1 m/s, the PSA film achieved a maximum temperature reduction of 5.3 degrees C, with an average daytime cooling of 3 degrees C. Furthermore, when integrated with common building materials, the film produced temperature drops of 6.7 degrees C on plastic surfaces and 5 degrees C on wooden surfaces, demonstrating good compatibility. To assess its potential for large-scale application, this study further conducted simulations using EnergyPlus (2025) across multiple climate zones in China and globally. The results indicate that the PSA film can achieve significant building energy savings in all Chinese provinces, and the corresponding annual CO2 emission reductions were estimated accordingly. Additionally, simulations for ten representative global cities (such as Shanghai, Mumbai, New York, and Sydney) consistently confirmed its energy-saving effectiveness under diverse climatic conditions. This research not only demonstrates novelty in material formulation and process, but also, through a combination of systematic field measurements and large-scale simulations, clarifies the performance of this film in real-world environments and its global application potential, providing a reliable basis for the promotion and application of radiative cooling technology in the fields of building energy conservation and carbon neutrality.

Compressed air energy storage (CAES) is a promising large-scale energy storage technology. However, in existing CAES systems, heat exchangers for charging and discharging process are always deployed respectively. This configuration leads to heat exchanger idleness, high investment costs and poor system compactness. Consequently, a natural idea is to utilize shared heat exchangers to meet the requirements of air cooling and heating in the process of charging and discharging, while reducing the total number of heat exchangers. Therefore, in order to evaluate the feasibility of this idea, this work takes a AA-CAES system with five compression-cooling stages and four expansion-heating stages as an example. Firstly, under design conditions, heaters and coolers are independently designed by using HTRI software based on the type of hairpin heat exchanger. Then, according to the design results of heaters and coolers, three innovative heat exchanger reuse schemes are proposed: Case 1 (direct reuse of the independently designed heaters), Case 2 (direct reuse of the independently designed coolers), and Case 3 (reusing the independently designed coolers supplemented with newly parallel heaters). By evaluating the thermal performance of each case under charging and discharging conditions, it is found that the discharging heaters can meet the air cooling requirements during the charging stage in Case 1, while the pressure drops of coolers designed in charging process significantly increase under the condition of discharging in Case 2, and there is a particularly large deviation in heat duty at the fourth stage. For Case 3, the combination of reused coolers and added heaters adequately meet the heat transfer requirements for air heating. Finally, performances of the three reuse schemes are compared, and an optimal scheme is determined for each stage based on heat duty, pressure drop, and heat transfer area, so as to minimize the total areas and obtain the best thermal performance. The results indicate that: Case 1 is optimal for the first and second stages heat exchangers. For the third stage heat exchangers, Case 2 is suitable; For the fourth stage, Case 3 is recommended. Compared to using independent heat exchangers, the proposed scheme can reduce the total heat transfer area while meeting the requirements of air cooling and heating. As for the economy, even if considering the additional cost of required valves and pipes, the proposed scheme still has great economy advantages. The above research provides a novel approach for the efficient integration and economic improvement of heat exchangers in AA-CAES systems.

Advanced adiabatic compressed air energy storage (AA-CAES) is a promising long-duration energy storage technology. However, conventional systems rely on separate compressor intercoolers and turbine interheaters, thus leading to significant equipment redundancy. Herein, this study proposes a 100 MW-class AA-CAES system based on shared heat exchangers. Based on this system, off-design datasets of shared heat exchangers are firstly generated using HTRI software to train Backpropagation Neural Network (BPNN) surrogate models for predicting the off-design performance. Subsequently, corresponding quasi-dynamic models are established. On this basis, a Simulink model is constructed for the AA-CAES system with shared heat exchangers. Furthermore, considering both seasonal operating schedules and peak/off-peak electricity prices, three system operation strategies are proposed: spring/autumn case, summer case, and winter case, with the conventional 'one charge one discharge' ideal operation case used for comparison. The results demonstrate that the BPNN models can predict heat exchanger outlet states, with average absolute deviation (AAD) values remaining below 4%. Besides, under the ideal condition, it achieves a round-trip efficiency (RTE) of 63.85% with a daily arbitrage profit of 200,000 CNY. Seasonally, spring and autumn cases yield an RTE of 62.43% and a daily profit of 239,770 CNY; summer cases show an RTE of 62.41% and a daily profit of 175,520 CNY; while winter cases peak at an RTE of 64.76% with a daily profit of 215,700 CNY. Furthermore, compared with the ideal case, implementing an integrated four-season dispatch strategy increases the estimated annual price-arbitrage profit from 73.00 million CNY to 79.41 million CNY.

To mitigate the risk of thermal runaway in lithium-ion batteries under extreme operating conditions, this study designs and fabricates a flame-retardant phase change material (CFPCM) with self-ceramicizing capabilities. The material employs octadecyl acrylate (OA) as the matrix and incorporates glass powder (GP), ceramic-forming filler (CP), and zinc borate (ZB) to construct a high-temperature-induced ceramicization system. Experimental results demonstrate that the self-ceramicizing flame-retardant phase change material (CFPCM3), containing 35 wt% ceramic-forming powder, exhibits excellent thermal performance. It possesses a latent heat of 80.5 J/g, thermal conductivity of 1.09 W/(m & sdot;K), and demonstrates a strong ceramic-forming effect with effective thermal insulation. Its limiting oxygen index (LOI) reaches 31.6, and it achieves the UL-94 vertical burning V-0 rating. Moreover, the material maintains good shape stability after prolonged heating. When applied to a battery module, CFPCM effectively reduces the peak battery temperature by 9.5% and maintains a temperature difference within 3 degrees C during 1-4C charge-discharge cycles, resulting in a more uniform temperature distribution. These results highlight the potential of the self-ceramicizing flame-retardant phase change material for battery thermal management and safety applications, offering a promising strategy for the development of multifunctional flame-retardant systems.

Waste heat released from the sidewalls of aluminum reduction cells represents a largely untapped mediumtemperature energy resource, yet its utilization is hindered by harsh industrial conditions and the lack of field-scale validation. In this study, a field-scale organic Rankine cycle (ORC) system driven by sidewall waste heat was designed, constructed, and experimentally investigated under real industrial conditions.The system employs RC318 as the working fluid and operates with a thermal input of approximately 112 kW, extracted from sidewall heat corresponding to about 79.3% of the available sidewall thermal resource (similar to 141.3 kW). Under steady-state conditions, the system achieves a maximum net power output of 9.5 kW, a thermal efficiency of 8.8%, and an exergy efficiency of 37.7%. The experimental results exhibit good repeatability, with deviations below 1.4%, and heat-balance residuals within +/- 1-2%, confirming data reliability.Parametric analysis shows that increasing evaporation temperature enhances net power output from 3.88 kW to 9.5 kW, while higher condensation temperature significantly reduces performance. Near the critical region, performance improvement exhibits clear diminishing marginal returns. Component-level exergy analysis reveals that the evaporator accounts for approximately 30.04% of total exergy input, representing the dominant source of irreversibility.The results demonstrate that thermodynamic matching between the heat source and working fluid, rather than excessive superheating or high evaporation temperature, governs system performance. This work provides rare field-scale experimental evidence and quantitative insights for ORC systems operating under non-uniform and fluctuating industrial heat sources.

In the development and engineering application of advanced adiabatic compressed air energy storage (AACAES), system performance optimization is essential to get the best energy storage efficiency with the lowest cost. However, in general, thermal and economic performances cannot be simultaneously optimal. To solve this problem, a multi-objective optimization is adopted in this work. Energy and economic models of the AA-CAES system are established to obtain the system performances. On this basis, system performances under basic conditions and the effects of operation parameters are obtained. With the maximum round-trip efficiency (RTE) and the minimum total capital cost (TCC) as the optimization objectives, key system parameters, including pinch point temperature difference (PPTD), compressor outlet temperature and sliding pressure range, are optimized with the Non-Dominated Sorting Genetic Algorithm (NSGA-II). The results indicate that under basic conditions, RTE of the system is 67.64 % and TCC is $13.127 x 107. With the increase of PPTD, RTE decreases, while TCC first decreases and then increases. As the compressor outlet temperature increases, TCC gradually decreases, while RTE increases first and then decreases. Furthermore, every 1 MPa increase of sliding pressure range increases RTE by 0.16 %, and decreases TCC by $1.300 x 107. After multi-objective optimization, the optimal RTE is 67.96 %, and TCC is $11.672 x 107. Compared with the performances under basic conditions, RTE increases by 0.32 % and TCC decreases by $1.455 x 107.

To meet the high heat dissipation requirements of IT equipment, the cooling system requires continuous operation in data centers. However, lack of efficient control strategies poses a dual challenge of high energy consumption and risk of sever downtime due to deviation from thermal environment. This paper proposed an innovative joint optimization method based on model predictive control (MPC-based) for rack-based cooling data centers, which can realize collaborative optimization of cooling system operating parameters and server workload scheduling in rack level. Dynamic heat transfer models were developed to represent the thermal inertia of cooling system and IT equipment, predicting the spatiotemporal variation of thermal environment. The primary objectives are to minimize the energy consumption of the cooling system, and ensure effective control of the thermal environment. The energy management and thermal management performance of the proposed method was comprehensively evaluated through simulation and comparative experiments. The impact of time-delay characteristics on the predictive control performance were first analyzed with different prediction horizons in rack-based cooling data centers. The results show that the proposed joint optimization method has significant advantages in maintaining temperature stability and uniformity, and the energy saving of the cooling system is up to 19.39 %. Further analysis of time-delay characteristics reveals that the thermal inertia of the cooling system and IT equipment affects the control performance. With the extension of the prediction horizon, up to 3.26 % of energy consumption can be further saved for the data center.

Grids with high renewable energy penetration require seasonal energy storage and flexible power generation, creating opportunities for advanced gas turbine combined cycle (GTCC) systems. This study proposes a power-to-gas-to-power pathway, in which aeroderivative gas turbines integrated with a supercritical CO2 cycle (SCC) serve as the discharge unit, utilizing e-methane as the energy carrier. For a deeper understanding of the integrated system, a comprehensive evaluation framework is developed based on a representative system architecture. Extending the waste heat recovery assessment into the exergy domain shows that CO2 flow-splitting not only improves thermal exergy recovery but also enhances the SCC's thermodynamic perfection (from 56.7 % to 61.0 %). The combined cycle exhibits superior overall performance across energy, exergy, economic, and environmental dimensions compared to standalone gas turbines. Without discretization, thermal conductance estimation errors in the recuperator and cooler exceed 50 %, whereas using only 10 segments reduces them to <1 %. Exergoeconomic analysis employing SCC-specific component cost correlations indicates that reducing the temperature difference in the heater and recuperator is economically beneficial, as evidenced by exergoeconomic factors below 40 %. An optimal gas turbine maximum temperature is identified to minimize the levelized cost of electricity, and a CO2 split ratio between 0.65 and 0.68 maximizes system efficiency. Integrated multi-objective optimization further improves the system efficiency to 51.3 %. Moreover, it reveals that the efficiency-cost trade-off is dominated by exhaust gas-related parameters, particularly the gas turbine pressure ratio. The proposed pathway and associated analyses offer insights for advancing next-generation GTCC technologies.

Currently, advanced adiabatic compressed air energy storage (AA-CAES) has been widely used, but the quantitative study of its energy loss is still unresolved. Therefore, the ideal AA-CAES with a round-trip efficiency (RTE) of 100% is defined to quantify the energy losses in the AA-CAES from the aspects of factors and components, so as to clarify the loss mechanism of AA-CAES. First, eight energy loss factors affecting the performances of AA-CAES are identified. Then, based on component type, six components of AA-CAES are identified. After that, to obtain the system energy flow, the corresponding thermodynamic models are developed. Finally, based on the given operating conditions, the energy losses corresponding to each factor and component are obtained sequentially using univariate analysis, and parametric analysis is carried out. The results show that in terms of energy loss factors, the storage device has the greatest impact on system performance with a compression work increment dEcharge of 72.56 MWh and an RTE of 89.21%. In terms of components, the compressors and turbines have the greatest impact on system performance. Furthermore, there is a synergistic effect among the factors. The effect of different factors acting together is greater than the superposition of individual values.

To satisfy the thermal environment requirements, approximately 40% of energy consumption is used for cooling in data centers. The efficient cooling system and workload management can improve heat dissipation, thereby reducing energy consumption. This paper introduced a novel joint optimization strategy (JOS) for cooling parameters and workload distributions designed for rack-based cooling data centers. The primary objective is to improve overall energy efficiency while ensuring the safe operation of the data center. The proposed strategy considers the thermal interaction between information technology (IT) equipment and cooling devices, as well as the heterogeneity among different servers, achieving granular optimization of cooling parameters and workload distributions. The impacts of different cooling parameters optimization on the energy management and thermal management performance were analyzed. The energy-saving potential and temperature field control effect considering server heterogeneity for the proposed JOS were investigated. The results show that, compared to univariate optimization, simultaneous optimization of supplied cold air temperature and airflow rate can achieve at least 4.7% in energy-saving. Furthermore, compared with independent control of the cooling system, the proposed JOS effectively addresses server overcooling, achieving a more uniform temperature distribution and further reducing the cooling energy consumption by 5%. It is noteworthy that the strategy demonstrates high computational efficiency while ensuring energy efficiency.

Lithium-ion batteries are advancing towards high capacity and high power, which inevitably leads to heat accumulation. Immersion cooling (IC) is considered an effective approach to address this issue due to its low contact thermal resistance and high heat dissipation efficiency. In this study, a battery thermal management system based on IC was proposed, and numerical simulation was utilized to explore the effects of IC system structural parameters, operating parameters, and the partitioning management strategy on the thermal performance of the battery pack. The results demonstrated that IC could reduce the maximum temperature of the battery pack to 36.47 degrees C at 3C and improve the temperature uniformity by 66.23 %. In particular, the convective heat transfer coefficient between the dielectric fluid and the battery surface was increased by 147.44 %, which had significantly enhanced the convective heat transfer between the two. Then the sensitivity analysis of each influencing factor was carried out, and it was found that Tin and D play a decisive role in the heat dissipation of the IC system. Finally, a partitioning management strategy was applied to the IC, and dimensional analysis was used to investigate the mechanisms underlying forced convection heat transfer in the IC system. It was found that when the number of partitions was two (P2), the St number of the system increases by 59.2 %, thereby demonstrating high heat dissipation efficiency and significantly reducing the risk of thermal runaway.

To fully recover abundant waste heat and reduce the operation cost in liquid-cooled data centers, a Carnot battery consisting of a heat pump (HP) and organic Rankine cycle (ORC) is proposed. Due to the existence of different cycle states for HPs and ORCs, four different cycle combinations are considered. To evaluate and compare their performances, thermo-economic models are developed. Under the design conditions, the optimal working fluid combinations are first determined for each battery. On this basis, thermodynamic and economic performances of the four batteries are analyzed in detail. The results indicate that the system consisting of a subcritical HP/transcritical ORC achieves the highest round-trip efficiency at 76%. Notably, the round-trip efficiency of the system can exceed 100% at low ORC condensing temperatures. Additionally, the system cost is about 767–796 USD/kW∙h, depending on the cycle combinations. Furthermore, the effects of operating parameters on system performances are also investigated. Finally, with the objective of maximum round-trip efficiency, key parameters of four batteries are optimized. The results reveal that the system with a subcritical HP/subcritical ORC attains a maximum round-trip efficiency of 83% after optimization. These research results contribute to the development of green data centers and the reduction of power costs.

This paper focuses on the flow and heat transfer characteristics of a cooling system that combines thermoelectric cooling technology with ion wind technology. Through experimental exploration and data analysis, the factors affecting the performance of the sawtooth-plate ion wind were first investigated using the orthogonal experimental method. Particle Image Velocimetry (PIV) was employed to visualize the internal flow field and investigate the impact of voltage and plate spacing on the performance of the ion wind generator with a mesh and a parallel plate receiving electrode. Lastly, the heat transfer characteristics of the standalone thermoelectric cooling system and the coupled system were compared. The study found that voltage has the greatest impact on the performance of the ion wind, followed by the spacing of the parallel plate electrodes. Compared to the standalone thermoelectric cooling system, the temperature drop of the heat source in the coupled system increased by 6.7%, and the COP increased by 7.9%, proving that the coupled system has significantly improved heat transfer performance.

Currently, working fluids for adiabatic compressed energy storage primarily rely on CO2 and air. However, it remains an unresolved issue to which of these two systems performs better. Therefore, this paper compares the pros and cons of both systems in terms of thermodynamic and economic performances under the given boundary conditions. To accurately obtain the performance of energy storage systems, quasi-dynamic models are established for key components. On this foundation, corresponding thermal-economic models are developed. The results indicate that at thermal storage temperatures of 120°C, 140°C, and 160°C, a 100MW×5h compressed CO2 energy storage (CCES) system has a higher round-trip efficiency (RTE) than a compressed air energy storage (CAES) system. However, CCES also faces the difficulties of a higher cost and a longer payback period (PBP). Specifically, at a thermal storage temperature 140°C, RTEs of CAES and CCES systems are 59.48% and 65.16% respectively, with costs of $11.54×107 and $13.45×107, and PBPs of 11.86 years and 12.57 years respectively. Compared to CAES system, CCES system has a 9.55% higher RTE, 16.55% higher cost, and a 6% longer PBP. At other thermal storage temperatures, similar phenomenons can be observed for these two systems. After comprehensively considering the obtained thermal and economic performances, it can be concluded the overall performance of CAES system is superior to that of CCES system. In addition, in practical engineering, key components of CAES are more mature than those of CCES, and air has higher safety than CO2.

Currently, working fluids for adiabatic compressed energy storage primarily rely on carbon dioxide and air. However, it remains an unresolved issue to which of these two systems performs better. Therefore, this paper compares the advantages and disadvantages of both systems in terms of thermodynamic and economic performances under the given boundary conditions. To accurately obtain the performance of energy storage systems, quasi-dynamic models are established for key components. On this foundation, corresponding thermodynamic- economic models are developed. The results indicate that at thermal storage temperatures of 120 degrees C, 140 degrees C, and 160 degrees C, 100 MWx5h x5h compressed carbon dioxide energy storage systems have higher round-trip efficiencies than compressed air energy storage systems. However, the compressed carbon dioxide energy storage also faces the difficulties of higher cost and longer payback period. Specifically, at the thermal storage temperature of 140 degrees C, round-trip efficiencies of compressed air energy storage and compressed carbon dioxide energy storage are 59.48 % and 65.16 % respectively, with costs of $11.54 x 107and 7 and $13.45 x 107, 7 , and payback periods of 11.86 years and 12.57 years respectively. Compared to compressed air energy storage system, compressed carbon dioxide energy storage system has 9.55 % higher round-trip efficiency, 16.55 % higher cost, and 6 % longer payback period. At other thermal storage temperatures, similar phenomenons can be observed for these two systems. After comprehensively considering the obtained thermodynamic and economic performances, the overall performance of compressed air energy storage is superior to that of compressed carbon dioxide energy storage. In addition, in practical engineering, key components of compressed air energy storage are more mature than those of compressed carbon dioxide energy storage, and air has higher safety than carbon dioxide. In the future work, the comparison for performances between different types of compressed carbon dioxide energy storage and compressed air energy storage should be taken into account, and dynamic models of the systems should be developed. Additionally, the industry chain of compressed carbon dioxide energy storage should be accelerated to reduce equipment costs, enabling it to compete with compressed air energy storage.

In order to develop the green data center driven by solar energy, a solar photovoltaic (PV) system with the combination of compressed air energy storage (CAES) is proposed to provide electricity for the data center. During the day, the excess energy produced by PV is stored by CAES. During the night, CAES supplies power to the data center, so as to reduce the cost of peak electricity consumption at night. To evaluate the system performances, thermodynamic and economic models are established. Thereafter, system performances under design conditions and the effects of system parameters are analyzed. The results indicate that under design conditions, for the 17.5 MW data center, the required solar PV area is 257075 m(2), and the highest PV power can reach up to 55 MW. The all-day efficiency of the PV system is 18.37 %. In this situation, a CAES system with 17.5 MW x 7.88 h is configured, and the variations of CAES parameters with time are obtained in a day. The round-trip efficiency is 64.88 % and the energy storage density is 5.02 kW.h.m(-3). The total exergy destruction of the whole system within 24 h can be up to 1581001 kW h. For the economic performance, the total cost is $93.87 M and the payback period is 11.84 years.

Recently, supercritical CO2 (S-CO2) has been extensively applied for the recovery of waste heat from flue gas. Although various cycle configurations have been proposed, existing studies predominantly focus on the steady analysis and optimization of different S-CO2 structures under design conditions, and there is a noticeable deficiency in off-design research, especially for the innovative S-CO2 cycles. Thus, in this work aimed at the proposed novel S-CO2 power cycle, off-design characteristics and corresponding control strategies are investigated for the waste heat recovery. Based on the design parameters of the S-CO2 cycle, structural dimensions of printed circuit heat exchangers (PCHEs) and shell-and-tube heat exchangers are determined, and design values of turbines and compressors are specified. On this basis, off-design models for these key components are formulated. By manipulating variables such as cooling water inlet temperature, cooling water mass flow rate, flue gas inlet temperature and flue gas mass flow rate, cycle performances of the system are analyzed under off-design conditions. The simulation results show that when the inlet temperature and the mass flow rate of cooling water vary separately, the thermal efficiency both can reach the maximum value of 28.43% at the design point. For the changes in heat source parameters, the optimum point is slightly deviated from the design condition. Amidst the fluctuations in flue gas inlet temperature, the thermal efficiency optimizes to a peak of 28.56% at 530 °C. In the case of variation in the flue gas mass flow rate, the highest thermal efficiency 28.75% can be obtained. Furthermore, to maintain the efficient and stable operation of the S-CO2 power cycle, the corresponding control strategy of the cooling water mass flow rate is proposed for the cooling water inlet temperature variation. Generally, when the inlet temperature of cooling water increases from 23 °C to 27 °C, the cooling water mass flow should increase from 82.3% to 132.7% of the design value to keep the system running as much as possible at design conditions.