• Energy Research

Abstract The boiler superheater undergoes load cycling transients, once the thermal power plant participates in peak shaving. Thermodynamic optimization of a superheater is carried out by optimizing the flowrate/temperature matches between the hot and cold fluids during switching the load rate from 0.75 to 1.00. On the basis of a dynamic model of the superheater, the transient thermal performance is presented. Furthermore, the exergy delivery efficiency of the superheater was analyzed. The superheater outlet temperatures of hot fluid, metal wall, and cold fluid are highly affected when regulating work fluid inlet flowrates/temperatures. During switching the load transient, when increasing the hot fluid flowrate amplitude and variation rate by 50%, the average exergy efficiency (ηE,avg) of the superheater can improve by 1.04% and 0.13%, respectively. When increasing the cold fluid inlet temperature by 5%, ηE,avg can improve by 1.16%. When increasing the hot fluid inlet temperature by 5%, ηE,avg decreases by 0.74%. The exergy efficiency of the superheater is more sensitive to regulating temperature match than the flowrate match during switching the load transient process.

Abstract The boiler superheater undergoes load cycling transients, once the thermal power plant participates in peak shaving. Thermodynamic optimization of a superheater is carried out by optimizing the flowrate/temperature matches between the hot and cold fluids during switching the load rate from 0.75 to 1.00. On the basis of a dynamic model of the superheater, the transient thermal performance is presented. Furthermore, the exergy delivery efficiency of the superheater was analyzed. The superheater outlet temperatures of hot fluid, metal wall, and cold fluid are highly affected when regulating work fluid inlet flowrates/temperatures. During switching the load transient, when increasing the hot fluid flowrate amplitude and variation rate by 50%, the average exergy efficiency (ηE,avg) of the superheater can improve by 1.04% and 0.13%, respectively. When increasing the cold fluid inlet temperature by 5%, ηE,avg can improve by 1.16%. When increasing the hot fluid inlet temperature by 5%, ηE,avg decreases by 0.74%. The exergy efficiency of the superheater is more sensitive to regulating temperature match than the flowrate match during switching the load transient process.

Abstract Reversible solid-oxide cells (SOCs) are a promising technology for mitigating the fluctuation of power from renewable sources. Mode switching between electrolysis and fuel cells occurs frequently and is necessary for an SOC stack. Herein, a dynamic SOC-stack model was developed and validated against experimental data. Subsequently, we extensively studied the stack temperature (Ts), voltage (Vs), and reversible efficiency ( η r e ) with different designing and operating parameters, including stack heat capacity (Cs), inlet hydrogen fraction ( x H 2 ), stack operational pressure (p), inlet work medium temperature (Tin), current density (I), and mode switching frequency (f). For an actual SOC plant, the stack may work in a nearly adiabatic environment. Our calculation results show that with x H 2 increasing from 0.2 to 0.6, the variation in ΔTs decreases by 25%, Vs increases by 10%, and ηre increases by 2.9%. With fourfold increasing in CS and p, ΔTs decreases by 75% and 25% and ηre increases by 0.47% and 1.8%, respectively, whereas, Vs is nearly unaffected. ΔTs and ΔVs almost proportionally increase with I. In relation to Tin or f, ΔTs is unaffected, ΔVs decreases, and ηre slightly increases. Overall, this work identified the most critical stack designing and operating factors affecting the transient behavior of an SOC stack during mode switching processes. The results can serve as guidelines for SOC-stack design and operation-strategy optimization.

Abstract Reversible solid-oxide cells (SOCs) are a promising technology for mitigating the fluctuation of power from renewable sources. Mode switching between electrolysis and fuel cells occurs frequently and is necessary for an SOC stack. Herein, a dynamic SOC-stack model was developed and validated against experimental data. Subsequently, we extensively studied the stack temperature (Ts), voltage (Vs), and reversible efficiency ( η r e ) with different designing and operating parameters, including stack heat capacity (Cs), inlet hydrogen fraction ( x H 2 ), stack operational pressure (p), inlet work medium temperature (Tin), current density (I), and mode switching frequency (f). For an actual SOC plant, the stack may work in a nearly adiabatic environment. Our calculation results show that with x H 2 increasing from 0.2 to 0.6, the variation in ΔTs decreases by 25%, Vs increases by 10%, and ηre increases by 2.9%. With fourfold increasing in CS and p, ΔTs decreases by 75% and 25% and ηre increases by 0.47% and 1.8%, respectively, whereas, Vs is nearly unaffected. ΔTs and ΔVs almost proportionally increase with I. In relation to Tin or f, ΔTs is unaffected, ΔVs decreases, and ηre slightly increases. Overall, this work identified the most critical stack designing and operating factors affecting the transient behavior of an SOC stack during mode switching processes. The results can serve as guidelines for SOC-stack design and operation-strategy optimization.

Abstract Double reheat is a potential technique to increase the efficiency of coal-fired power plants. Large penetration of renewable power requires coal-fired power plants to operate flexibly. The thermal inertia of a double-reheat boiler is extremely high due to its complicated flow, strong coupling and numerous devices, which seriously restrict the operational flexibility of double-reheat coal-fired power plants. In this study, dynamic simulation models and temperature control systems of a double-reheat boiler are developed via GSE software and then validated to understand the heat storage change law. An improved control model considering heat storage changes is proposed. The flexibility of original and improved control strategies is compared. It turns out that steam temperatures in the boiler system with the original control exceed the allowable ranges when the load cycling rate is 1.5% Pe0 min−1. By contrast, steam temperatures in the boiler system with the improved control remain within the allowable ranges when the load cycling rate is 3.0% Pe0 min−1. The response time with the improved control is shorter than that with the original control. This study is expected to provide a detailed reference for improving the flexibility of double-reheat power plants.

Abstract Double reheat is a potential technique to increase the efficiency of coal-fired power plants. Large penetration of renewable power requires coal-fired power plants to operate flexibly. The thermal inertia of a double-reheat boiler is extremely high due to its complicated flow, strong coupling and numerous devices, which seriously restrict the operational flexibility of double-reheat coal-fired power plants. In this study, dynamic simulation models and temperature control systems of a double-reheat boiler are developed via GSE software and then validated to understand the heat storage change law. An improved control model considering heat storage changes is proposed. The flexibility of original and improved control strategies is compared. It turns out that steam temperatures in the boiler system with the original control exceed the allowable ranges when the load cycling rate is 1.5% Pe0 min−1. By contrast, steam temperatures in the boiler system with the improved control remain within the allowable ranges when the load cycling rate is 3.0% Pe0 min−1. The response time with the improved control is shorter than that with the original control. This study is expected to provide a detailed reference for improving the flexibility of double-reheat power plants.

Abstract Electricity generated from renewable energy source fluctuates heavily and can hardly be predicted. The peak shaving (or load cycling) operation of conventional thermal power plants is an effective means to mitigate the mismatch between electricity demands and supplies. Therefore, determining how thermal power plants can operate in a flexible and effective mode is an urgent issue that should be addressed. For thermal power plants, new methods and strategies need to be proposed to face the challenge of the integrating flexibility and energy saving into transient processes. Dynamic performances of thermal power plants during load cycling processes are affected by the coupling of the thermal system and the control system. Feasible approaches from optimizing the coordinated control system (CCS) may radically enhance the peak shaving capacity of thermal power plants. The heat storage in a coal-fired power plant, including heating surface metals and work media, varies with the load rate of the plant. During cycling load operations, the real-time heat storage value of one unit differs from that of the corresponding steady state load command rate. This difference hinders the flexibility of one unit and affects its economic performances during cycling processes. In this paper, a revised water fuel ratio (WFR) control strategy based on heat storage difference was proposed and tested on established coal-fired power plant models. Results show that the accumulation deviations of load rate command and real-time load rate are considerably reduced during load cycling processes when the proposed WFR control strategy is introduced. The revised WFR control strategy diminishes the difference between the target and the actual total power output. When the load cycling rate varies from 10 to 30 MW min−1 between 50% and 100% THA, the standard coal consumption variation rate (Δbs) decreases by 0.31–1.01 g kW−1 h−1 during loading up processes, and decreases by 0.26–1.69 g kW−1 h−1 during loading down processes.

Abstract Electricity generated from renewable energy source fluctuates heavily and can hardly be predicted. The peak shaving (or load cycling) operation of conventional thermal power plants is an effective means to mitigate the mismatch between electricity demands and supplies. Therefore, determining how thermal power plants can operate in a flexible and effective mode is an urgent issue that should be addressed. For thermal power plants, new methods and strategies need to be proposed to face the challenge of the integrating flexibility and energy saving into transient processes. Dynamic performances of thermal power plants during load cycling processes are affected by the coupling of the thermal system and the control system. Feasible approaches from optimizing the coordinated control system (CCS) may radically enhance the peak shaving capacity of thermal power plants. The heat storage in a coal-fired power plant, including heating surface metals and work media, varies with the load rate of the plant. During cycling load operations, the real-time heat storage value of one unit differs from that of the corresponding steady state load command rate. This difference hinders the flexibility of one unit and affects its economic performances during cycling processes. In this paper, a revised water fuel ratio (WFR) control strategy based on heat storage difference was proposed and tested on established coal-fired power plant models. Results show that the accumulation deviations of load rate command and real-time load rate are considerably reduced during load cycling processes when the proposed WFR control strategy is introduced. The revised WFR control strategy diminishes the difference between the target and the actual total power output. When the load cycling rate varies from 10 to 30 MW min−1 between 50% and 100% THA, the standard coal consumption variation rate (Δbs) decreases by 0.31–1.01 g kW−1 h−1 during loading up processes, and decreases by 0.26–1.69 g kW−1 h−1 during loading down processes.