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The household energy management system (HEMS) has become an important system for energy conservation and emission reduction. In this study, home energy management considering carbon quota has been established. Firstly, the household photovoltaic output model, load model of various electrical appliances, battery load model, and charging and discharging of electric vehicles (EVs) model are established. Secondly, the carbon emission and carbon quota of household appliances and EVs are considered in these models. Thirdly, the energy optimization model of minimum the household user’s total comprehensive operation cost with the minimum total electricity consumption, carbon trading cost, battery degradation cost, and carbon quota income are proposed, taking into account constraints such as the comfort of users’ energy use time. Subsequently, the improved particle swarm optimization (IPSO) algorithm is used to tackle the problem. Compared to the standard particle swarm optimization (PSO), the IPSO has significantly improved the optimization effect. By comparing the optimization results in different scenarios, the effectiveness of the strategy is verified, and the influence of different carbon trading prices on optimal energy scheduling has been analyzed. The result shows that the comprehensive consideration of carbon trading cost and total electricity cost can reduce the household carbon emissions and the total electricity cost of the household user. By increasing the carbon trading price, the user’s carbon trading income and the EV carbon quota income increase, and the overall operating cost decreases; the guidance and regulation of carbon trading price can make a valuable contribution to HEMS optimization. Compared to the original situation, the household carbon emissions are reduced by 14.58 kg, a decrease of over 21.47%, while the total comprehensive operation cost are reduced by 14.12%. Carbon quota trading can guide household users to use electricity reasonably, reducing household carbon emissions and the total cost of household electricity.

In view of problem that traditional vector control method is difficult to carry out active heat management for explosion-proof frequency converter, a low loss control method for explosion-proof frequency converter based on model predictive control was proposed. Heat loss model of the explosion-proof converter was established, and conduction loss and switching loss of power devices were deduced and analyzed, and pointed out that the key of low loss control is to reduce the switching frequency. Based on framework of model prediction control system, high-precision prediction model suitable for low-loss control requirements of explosion-proof converter was designed, and then rolling optimization calculation was completed based on value function considering loss characteristics. The proposed method is analyzed and verified based on 1 140 V/2 MW explosion-proof frequency conversion test prototype, the results show that the method can realize multi-objective optimization problem of explosion-proof frequency converter under constraint condition, and rationally allocate multiple optimization objective weight coefficients, and effectively reduce the overall loss of the system under the condition of satisfying dynamic and steady-state performance requirements of explosion-proof frequency converter.

In this study, fifteen participants were exposed in an enclosed environmental chamber to investigate the effects of elevated carbon dioxide (CO2) concentration on their cognitive abilities. Three CO2 conditions (1500 ppm, 3500 ppm, and 5000 ppm) were achieved by constant air supply and additional ultra-pure CO2. All participants received the same exposure under each condition, during which they performed six cognitive tests evaluating human perception, attention, short-term working memory, risky decision making, and executive ability. During each exposure condition, the reaction time (RT) test, speed perception test, visual search (VS), 2-back test, balloon analogue risk test (BART), and Stroop test were successively conducted with rest intervals of approximately 13min. The results showed that there was no statistically-significant difference in the performance of RT tests, speed perception test, and 2-back test. This indicated that the elevated CO2 concentration below 5000 ppm did not affect the participants’ perception and short-term working memory. However, significant increase of response time was observed in the VS test, BART, and Stroop test at 5000 ppm compared with lower exposure concentrations. The slower reaction reflected the negative effects of elevated CO2 concentration on human visual attention, risky decision making, and executive ability. The findings suggest that work performance could be negatively affected by the exposure to CO2 at the current occupational concentration limit.

The prediction of contaminant distribution in multi-zone environment is critical for ensuring indoor personnel health and making an optimistic ventilation strategy. However, the input of uncertainty parameters (flow coefficients, flow exponents, etc.) has a significant impact on the predicted pollutant concentrations. In this study, we proposed a reconstruction method to achieve parameter estimation for the multi-zone model. MATLAB codes was programmed to call CONTAM engine to accomplish pollutant transport simulation in a multi-zone scaled building model. Then a Bayesian inference algorithm compiled in MATLAB codes was applied to determine the unknown parameters iteratively. Finally, multi-zone scaled experiments with different forms of pollutant sources were employed to validate the reconstruction method. The results showed that the predicted concentrations with the reconstructed parameters agreed well with the measured data in the constant source (CS) experiment. While, for the dynamic source (DS) experiment, the predicted concentrations had some discrepancies with the measured data.

In order to improve actual operation efficiency of feeding system of pressure filter, an efficiency optimization method with the maximum torque per ampere applied in direct torque control was proposed. The method adjusts amplitude of stator flux linkage dynamically based on actual changing of electromagnetic torque, so as to achieve the maximum torque output under unit current amplitude. The experimental results show that the method can realize efficiency optimization of the system in the whole load range with smaller stator current under the same electromagnetic torque.

In view of problem of large torque ripple existed in low speed range of direct torque control system of mine hoist, an optimal control method of torque ripple for mine hoist was proposed. Based on prediction model, the method uses zero voltage vector injection method to adjust duty ratio of optimal voltage vector. The minimum torque ripple is taken as design index in calculation process of the duty ratio, the optimal duty ratio is obtained by online calculation. The experimental result shows that the method can effectively reduce torque ripple and obtain excellent torque control performance of motor in low speed.

For traditional permanent magnet synchronous motor (PMSM) flux weakening method, it is easy to cause voltage command saturation and the system lose control. In order to solve this problem, we propose a high speed PMSM anti-saturation regulation method based on hybrid flux weakening technology. The feedforward channel of this method is designed as a two-dimensional table of torque/flux linkage. The expected value of the current current of dq axis is directly checked through the current flux linkage and torque instruction to ensure the dynamic response of the system. In the feedback channel, the voltage instruction compensation link is proposed in this paper. In combination with the output instruction of the current controller, the speed and bus voltage information, the flux instruction required by the feedforward channel is adjusted. Finally, the experimental results verify that the proposed method meets the requirements of high-speed PMSM fast dynamic response, and improves the reliability of the system when it is running at high speed.

The high permeability of household distributed photovoltaic is prevalent after its access. The connection between distributed generation and main network is cut off quickly and the energy storage device is used to realize energy storage. From the point of view of economy and rationality, the above-mentioned operation has become increasingly unable to meet the health of the grid after the access of distributed generation. In this paper, a construction scheme and operation strategy of household micro-grid including household energy efficiency management is designed by using equipment and equipment integration, equipment and system integration, system and system integration of household micro-grid and household energy efficiency management. It adds in-situ absorption capacity of distributed photovoltaic, realizes efficient integration of household energy efficiency management and household microgrid, effectively solves the problems of high permeability of household distributed generation, and has certain application value in the user side.