Xiaobo Cui

To develop a biomass and power-to-gas (BPtG) process for renewable electricity storage and sustainable synthetic natural gas (SNG) production, this work investigated five BPtG processes integrated with different electricity-driven gasification technologies based on simulation data. These processes were evaluated for SNG composition and yield, life-cycle energy and exergy efficiencies, life-cycle carbon emissions, and the equivalent unit production cost. The results show that the energy and exergy efficiencies of SNG from those processes range between 53.1 and 58.6% and 36.4 and 41.1%, respectively. Based on the energy allocation method, the carbon emissions without and with CO₂ capture ranges from 22.0 to 34.8 and from −43.4 to −17.6, respectively, in gCO₂e/MJ_SNG. These BPtG processes can produce low-carbon SNG and even achieve negative carbon emissions with CO₂ capture. Both feedstock and electricity costs have significant influences on the profitability of the processes. The BPtG process integrated with resistance heating gasification, plasma-assisted gasification, and moderate water electrolysis are recommended for their compromise of multi-perspective performances. This paper provided the orders of the five processes based on these indicators and recommendations for different applicable scenarios.

Gas turbines play a core role in clean energy supply and construction of comprehensive energy system, and the control performance of primary frequency modulation (PFM) of gas turbine has a great impact on the frequency control of the power grid. However, there are some control difficulties in the PFM control of gas turbines, such as the coupling effect of fuel control loop and speed control loop, slow tracking speed and large variation of operating conditions. To relieve the above difficulties, a control strategy based on the fuzzy-modified active disturbance rejection control (F-MADRC) proposed in this paper. Based on the analyses of the parameter stability region for active disturbance rejection control (ADRC), fuzzy tuning rules of parameters for F-MADRC are designed. Finally, the proposed F-MADRC is applied to the PFM system of MS6001B heavy-duty gas turbine. The simulation results show that the gas turbine unit with the proposed method can obtain the best control performance of the PFM with strong ability to deal with system uncertainties. The proposed method shows good engineering application potential.

The drum water level plays a crucial role in the safety and economy of heat recovery boilers. However, the control of the drum water level faces many challenges, such as external disturbances and system uncertainties. To enhance the control performance of the drum water level, a modified active disturbance rejection control (MADRC) optimized with sensitivity constraint is proposed in this paper. Firstly, the control structure of the three-element control system for the drum water level is introduced and analyzed. Based on the regular active disturbance rejection control (ADRC) structure, the structure of the MADRC is introduced and the convergence of the proposed MADRC is proven. Then a modified whale optimization algorithm (MWOA) with sensitivity constraint is applied to optimize the parameters of the MADRC. With different sensitivity constraints, the parameters of the MADRC and comparative controllers are obtained, and their control performance for tracking and disturbance rejection abilities is compared. Moreover, the ability to handle system uncertainties is analyzed. Simulation results and performance indexes show that the proposed MADRC can obtain the best tracking and disturbance rejection abilities with satisfactory robustness. The satisfactory control performance shows that the proposed MADRC has wide application potential for heat recovery boilers and other industrial processes.

Gas turbines play core roles in clean energy supply and the construction of comprehensive energy systems. The control performance of primary frequency modulation of gas turbines has a great impact on the frequency control of the power grid. However, there are some control difficulties in the primary frequency modulation control of gas turbines, such as the coupling effect of the fuel control loop and speed control loop, slow tracking speed, and so on. To relieve the abovementioned difficulties, a control strategy based on the desired dynamic equation proportional integral (DDE-PI) is proposed in this paper. Based on the parameter stability region, a parameter tuning procedure is summarized. Simulation is carried out to address the ease of use and simplicity of the proposed tuning method. Finally, DDE-PI is applied to the primary frequency modulation system of an MS6001B heavy-duty gas turbine. The simulation results indicate that the gas turbine with the proposed strategy can obtain the best control performance with a strong ability to deal with system uncertainties. The proposed method shows good engineering application potential.

The high-quality operation of a superheated steam temperature (SST) system is a core fact of the safety, economy, and stability of thermal power units. How to improve the control performance of an SST system under large-varying operating conditions is becoming a research hotspot. To solve this challenge, this paper proposes a proportional integral derivative (PID) control strategy based on integral gain scheduling. Based on the introduction of the SST system and classical model under typical operating conditions, the control difficulties of the SST system are analyzed theoretically. Then, a PID control strategy, based on integral gain scheduling, is introduced for the cascade control structure, and the stability of the proposed control strategy is analyzed by calculating the PID stability region. Finally, the effectiveness of the proposed method is verified under nominal and uncertain conditions, where the proposed method could obtain satisfactory tracking and disturbance rejection control performance. Simulation results show the valuable application prospects of the proposed method.

Chemical looping biomass gasification is a novel technology converting biomass into syngas, and the selection of oxygen carrier is key for efficient tar conversion. The performance of LaFe_1-xNi_x as a robust catalytic oxygen carrier was investigated in the chemical looping conversion of toluene (tar model compound) into syngas in a fixed bed. LaM (M = Fe, Ni, Mn, Co, and Cu) was initially compared to evaluate the effect of transition metal on toluene conversion. LaFe (partial oxidation) and LaNi (catalytic pyrolysis) exhibited better performance in promoting syngas production than other oxygen carriers. Therefore, Ni-substituted ferrite LaFe_1-xNi_x (x = 0, 0.2, 0.4, 0.6, 0.8 and 1) was further developed. The effects of Ni-substitution, steam/carbon ratio (S/C), and temperature on toluene conversion into C₁ and H₂ were evaluated. Results showed that the synergistic effect of Fe and Ni promoted toluene conversion, improving H₂ yield yet with serious carbon deposition. Steam addition promoted toluene steam reforming and carbon gasification. With S/C increasing from 0.8 to 2.0, the C₁ and H₂ yield increased from 73.9% to 97.5% and from 197.7% to 269.6%, respectively. The elevated temperature favored toluene conversion and C1 yield. LaFe_0.6Ni_0.4 exhibited strong reactivity stability during toluene conversion at S/C = 1.6 and 900 °C.

An energy efficiency monitoring method of the steam turbine system is studied in this paper. Multivariate state estimation technique (MSET) is utilized to compare the actual monitoring parameters and the healthy data of the equipment in normal working condition with a multi parameter estimation model. Due to the limitation of a single heat rate index in evaluating energy efficiency variation, the energy efficiency deviation degree combined with improved information entropy weight is proposed to judge the steam turbine’s operation condition levels. The index value in the modified weight method has been searched for more steady weight values calculated by information entropy values with small variation. Taking a 600 MW unit as an example, the energy efficiency levels of the unit under a 550 MW normal working condition are clustered into four groups, testifying the MSET model correctness and calculating the deviation degree value. Then, the energy efficiency status monitoring model is utilized to record residuals of actual data and estimated data during abnormal energy efficiency period. The residuals over deviation degree are then marked and judged as related with the abnormal data. The results show that the MSET model can timely and accurately judge the change of unit operation state, and the deviation degree calculated by the modified information entropy weight method can provide earlier warnings for the abnormal energy efficiency working conditions.

The nonlinear problem of system cannot be well solved using traditional power regulation system, which causes regulation lag and insufficient output and poor accuracy of the actual performance of the primary frequency regulation (PFR) on thermal power units. In order to further improve PFR performance of thermal power units, a multi-model predictive control method is adopted to optimize and improve the traditional steam turbine power control system. A PFR optimal control strategy is proposed, which improves the regulation performance and robustness of the power control system. The simulation results show that the proposed optimization algorithm can overcome the nonlinear problem of the steam turbine governing valve, and the regulating process is stable and fast without overshoot. This research is of great significance to improve the contribution rate of PFR of thermal power units and to better satisfy the assessment of power grid PFR, thereby to stabilize the frequency of power grid.