Effect of bubble morphology and behavior on power consumption in non-Newtonian fluids’aeration process

Due to a prolonged operation time and low mass transfer efficiency, the primary challenge in the aeration process of non-Newtonian fluids is the high energy consumption, which is closely related to the form and rate of impeller, ventilation, rheological properties and bubble morphology in the reactor. In this perspective, through optimal computational fluid dynamics models and experiments, the relationship between power consumption, volumetric mass transfer rate(kLa) and initial bubble size(d0) was constructed to establish an efficient operation mode for the aeration process of non-Newtonian fluids. It was found that reducing the d0could significantly increase the oxygen mass transfer rate, resulting in an obvious decrease in the ventilation volume and impeller speed. When d0was regulated within 2-5 mm,an optimal kLa could be achieved, and 21% of power consumption could be saved, compared to the case of bubbles with a diameter of 10 mm.

Experimental study of power consumption, local characteristics distributions and homogenization energy in gas–liquid stirred tank reactors

In this paper, the power consumption, the vertical local void fraction and the local gas–liquid interfacial area are investigated in the aerated stirred tank reactors(STRs) equipped with a rigid-flexible impeller. Meanwhile, the regressive correlation based on power consumption and interfacial area is proposed. Then a novel homogenization energy(HE = RSDPtm) expression based on power consumption and local interfacial area is redefined and used to indicate the mixing efficiency. The optimal operating mode is selected based on the change of the HE value. This paper can provide research ideas for structural optimization of stirred reactors.

Multi-model Predictive Control of Ultra-supercritical Coal-fired Power Unit

The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.

Performance Analysis of Induced Draft Fan Driven by Steam Turbine for 1000 MW Power Units

Boiler fan is the main power consumption device in thermal power units and the induced draft fan accounted for the largest proportion. Reducing the energy consumption rate of induced draft fan is the main path to reduce the power consumption rate of thermal power units. The induce fan driven by small turbine is greatly effective for reducing the power consumption rate and the supply coal consumption rate in large thermal power plant. Take 1000 MW power units for example, the selection of steam source for steam turbine were discussed and economic performance of the unit under different steam source was compared in this paper. The result shows that compared with the motor driven method, there is about 1.6 g/kWh decrease in supply coal consumption rate driven by the fourth stage extraction steam;whereas there is about 2.5 g/kWh decrease in supply coal consumption rate driven by the fifth stage extraction steam.

Numerical investigation of granular mixing in an intensive mixer:Effect of process and structural parameters on mixing performance and power consumption

Discrete element method(DEM)simulations of particle mixing process in an intensive mixer were conducted to study the influence of structural and process parameters on the mixing performance and power consumption.The DEM model was verified by comparing the impeller torque obtained from simulation with that from experiment.Impeller and vessel torque,coordination number(CN)and mixing index(Relative standard deviation)were adopted to qualify the particle dynamics and mixing performance with different parameters.A method based on cubic polynomial fitting was proposed to determine the critical mixing time and critical specific input work during the mixing process.It is found that the mixing performance and energy efficiency increases with the decrease of impeller offset.The mixing performance is improved slightly with the increase of blade number and the impeller with 3 blades has the highest energy efficiency due to its low input torque.Results indicate that the energy efficiency and the mixing performance increase with the decrease of filling level when the height of granular bed is higher than that of blade.

Research on the Prediction of Load Regulation Capacity for Supercritical Thermal Power Unit

Both the modeling and the load regulation capacity prediction of a supercritical power plant are investigated in this paper. Firstly, an indirect identification method based on subspace identification method is proposed. The obtained identification model is verified by the actual operation data and the dynamic characteristics of the system are well reproduced. Secondly, the model is used to predict the load regulation capacity of thermal power unit. The power, main steam pressure, main steam temperature and other parameters are simulated respectively when the unit load is going up and down. Under the actual constraints, the load regulation capacity of thermal power unit can be predicted quickly.

No Power Consumption Design of a New-style Mechanical Unit Bathroom

The paper is based on the fact of serious water shortage and the coming of a LC （ low carbon ） lifestyle. The design was guided by demand design and aided by Fluent simulation, it break the normal method of water sav- ing and works out a set of a no power consumption new system of house water saving. The paper makes a detailed presentation of the design ideas and process of a system core ; the simulation result can show the three-dimensional flow and pressure distribution of flow in a system core factuaUy. Consequently, the simulation demonstrates the feasibility and practical applicability of the design.

Effect of the Inclination of Baffles on the Power Consumption and Fluid Flows in a Vessel Stirred by a Rushton Turbine

The role of baffles in mechanically stirred tanks is to promote the stability of power drawn by the impeller and to avoid the fluid swirling, thus enhancing mixing. The present paper numerically investigates the baffles effects in a vessel stirred by a Rushton turbine. The geometric factor of interest is the baffle inclination which is varying between 25°, 32.5°, 45°, 70° and 90° at different impeller rotational speeds. The impeller rotational direction has also been varied. The vortex size and power consumption were evaluated for each geometrical configuration. It was found that the best configuration is the baffle inclination by = 70° at a negative angular velocity.

Power consumption and flow field characteristics of a coaxial mixer with a double inner impeller

A coaxial mixer meeting the actual demand of a system with high and variable viscosity is investigated. It has an outer wall-scraping frame and a double inner impeller consisting of a four-pitched-blade turbine and Rushton turbine. The power consumption and flow field characteristics of the coaxial mixer in laminar and transitional flow are simulated numerically, and then the distribution of velocity field, shear rate and mass flow rate are analyzed. The simulation results indicate that the outer frame has little effect on the power consumption of the double inner impeller whether in laminar or transitional flow, whereas the inner combined impeller has a great effect on the power consumption of the outer frame. Compared with the single rotation mode, the power consumption of the outer frame will decrease in co-rotation mode and increase in counter-rotation mode. The velocity, shear rate and mass flow rate are relatively high near the inner impeller in all operating modes, and only under double-shaft agitation will the mixing performance near the free surface be improved.In addition, these distributions in the co-rotation and counter-rotation modes show little difference, but the co-rotation mode is recommended for the advantage of low power consumption.

Biodegradable and flexible i-carrageenan based RRAM with ultralow power consumption

Transient memories,which can physically disappear without leaving traceable remains over a period of normal operation,are attracting increasing attention for potential applications in the fields of data security and green electronics.Resistive random access memory(RRAM)is a promising candidate for next-generation memory.In this context,biocompatible l-carrageenan(l-car),extracted from natural seaweed,is introduced for the fabrication of RRAM devices(Ag/l-car/Pt).Taking advantage of the complexation processes between the functional groups(C–O–C,C–O–H,et al.)and Ag metal ions,a lower migration barrier of Ag ions and a high-speed switching(22.2 ns for SET operation/26 ns for RESET operation)were achieved,resulting in an ultralow power consumption of 56 fJ.And the prepared Ag/l-car/Pt RRAM devices also revealed the capacities of multilevel storage and flexibility.In addition,thanks to the hydrophilic groups of l-car molecule,the RRAM devices can be rapidly dissolved in deionized(DI)water within 13 minutes,showing excellent transient characteristics.This work demonstrates that l-car based RRAM devices have great potential for applications in secure storage applications,flexible electronics and transient electronics.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

Forecasting increasing rate of power consumption based on immune genetic algorithm combined with neural network

Considering the factors affecting the increasing rate of power consumption, the BP neural network structure and the neural network forecasting model of the increasing rate of power consumption were established. Immune genetic algorithm was applied to optimizing the weight from input layer to hidden layer, from hidden layer to output layer, and the threshold value of neuron nodes in hidden and output layers. Finally, training the related data of the increasing rate of power consumption from 1980 to 2000 in China, a nonlinear network model between the increasing rate of power consumption and influencing factors was obtained. The model was adopted to forecasting the increasing rate of power consumption from 2001 to 2005, and the average absolute error ratio of forecasting results is 13.521 8%. Compared with the ordinary neural network optimized by genetic algorithm, the results show that this method has better forecasting accuracy and stability for forecasting the increasing rate of power consumption.

Optimization of Minimum Power Output for Combined Heat and Power Units Considering Peak Load Regulation Ability

Northern China has rich wind power and photovoltaic renewable resources. Combined Heat and Power (CHP) Units to meet the load demand and limit its peaking capacity in winter, to a certain extent, it results in structural problems of wind-solar power and thermoelectric. To solve these problems, this paper proposes a plurality of units together to ensure supply of heat load on the premise, by building a thermoelectric power peaking considering thermal load unit group dynamic scheduling model, to achieve the potential of different thermoelectric properties peaking units of the excavation. Simulation examples show, if the unit group exists obvious relationship thermoelectric individual differences, the thermal load dynamic scheduling can be more significantly improved overall performance peaking unit group, effectively increase clean energy consumptive.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Three-Level Optimal Scheduling and Power Allocation Strategy for Power System ContainingWind-Storage Combined Unit

To mitigate the impact of wind power volatility on power system scheduling,this paper adopts the wind-storage combined unit to improve the dispatchability of wind energy.And a three-level optimal scheduling and power allocation strategy is proposed for the system containing the wind-storage combined unit.The strategy takes smoothing power output as themain objectives.The first level is the wind-storage joint scheduling,and the second and third levels carry out the unit combination optimization of thermal power and the power allocation of wind power cluster(WPC),respectively,according to the scheduling power of WPC and ESS obtained from the first level.This can ensure the stability,economy and environmental friendliness of the whole power system.Based on the roles of peak shaving-valley filling and fluctuation smoothing of the energy storage system(ESS),this paper decides the charging and discharging intervals of ESS,so that the energy storage and wind power output can be further coordinated.Considering the prediction error and the output uncertainty of wind power,the planned scheduling output of wind farms(WFs)is first optimized on a long timescale,and then the rolling correction optimization of the scheduling output of WFs is carried out on a short timescale.Finally,the effectiveness of the proposed optimal scheduling and power allocation strategy is verified through case analysis.

Low Power Consumption Distributed-Feedback Quantum Cascade Lasers Operating in Continuous-Wave Mode above 90℃ at λ～7.2μm

We report on the design and fabrication of λ-7.2μm distributed feedback quantum cascade lasers lot very high temperature cw operation and low electrical power consumption. The cw operation is reported above 90℃. For a 2-mm-long and 10-μm-wide laser coated with high-reflectivity on the rear facet, more than 170mW of output power is obtained at 20℃ with a threshold power consumption of 2.4 W, corresponding to 30mW with a threshold power consumption of 3.9 W at 90℃. Robust single-mode emission with a side-mode suppression ratio above 25 dB is continuously tunable by the heat sink temperature or injection current.

Optimal Scheduling Strategy of Source-Load-Storage Based onWind Power Absorption Benefit

In recent years,the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing,but the peak regulation capacity of the power grid in the three north regions of China is limited,resulting in insufficient local wind power consumption capacity.Therefore,this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid’s wind power consumption capacity.The objective of the uppermodel is tominimize the peak-valley difference of the systemload,which ismainly to optimize the system load by using the demand response resources,and to reduce the peak-valley difference of the system load to improve the peak load regulation capacity of the grid.The lower scheduling model is aimed at maximizing the system operation benefit,and the scheduling model is selected based on the rolling schedulingmethod.The load-side schedulingmodel needs to reallocate the absorbed wind power according to the response speed,absorption benefit,and curtailment penalty cost of the two DR dispatching resources.Finally,the measured data of a power grid are simulated by MATLAB,and the results show that:the proposed strategy can improve the power grid’s wind power consumption capacity and get a large wind power consumption benefit.

Price prediction of power transformer materials based on CEEMD and GRU

The rapid growth of the Chinese economy has fueled the expansion of power grids.Power transformers are key equipment in power grid projects,and their price changes have a significant impact on cost control.However,the prices of power transformer materials manifest as nonsmooth and nonlinear sequences.Hence,estimating the acquisition costs of power grid projects is difficult,hindering the normal operation of power engineering construction.To more accurately predict the price of power transformer materials,this study proposes a method based on complementary ensemble empirical mode decomposition(CEEMD)and gated recurrent unit(GRU)network.First,the CEEMD decomposed the price series into multiple intrinsic mode functions(IMFs).Multiple IMFs were clustered to obtain several aggregated sequences based on the sample entropy of each IMF.Then,an empirical wavelet transform(EWT)was applied to the aggregation sequence with a large sample entropy,and the multiple subsequences obtained from the decomposition were predicted by the GRU model.The GRU model was used to directly predict the aggregation sequences with a small sample entropy.In this study,we used authentic historical pricing data for power transformer materials to validate the proposed approach.The empirical findings demonstrated the efficacy of our method across both datasets,with mean absolute percentage errors(MAPEs)of less than 1%and 3%.This approach holds a significant reference value for future research in the field of power transformer material price prediction.

Unit Commitment under the Environment of Wind Power and Large-Scale Bilateral Transactions

Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considering the executive priority of different power components to establish a multi-objective coordination unit commitment model. Through an example to verify the effectiveness of the model in promoting wind power consumption, guaranteeing trade execution, and improving power generation efficiency, and analyzed the interactions to each other among the factors of wind power, trading and blocking. According to the results, when wind power causes reverse power flow in the congestion line, it will promote the implementation of contracts, the influence of wind power accommodation to trade execution should be analyzed combined with the grid block, the results can provide reference for wind power planning.

LVP Modeling and Dynamic Characteristics Prediction of A Hydraulic Power Unit in Deep-Sea

A hydraulic power unit （HPU） is the driving ＂heart＂ of deep-sea working equipment. It is critical to predict its dynamic performances in deep-water before being immerged in the seawater, while the experimental tests by simulating deep-sea environment have many disadvantages, such as expensive cost, long test cycles, and difficult to achieve low-temperature simulation, which is only used as a supplementary means for confirmatory experiment. This paper proposes a novel theoretical approach based on the linear varying parameters （LVP） modeling to foresee the dynamic performances of the driving unit. Firstly, based on the varying environment features, dynamic expressions of the compressibility and viscosity of hydranlic oil are derived to reveal the fluid performances changing. Secondly, models of hydraulic system and electrical system are accomplished respectively through studying the control process and energy transfer, and then LVP models of the pressure and flow rate control is obtained through the electro-hydraulic models integration. Thirdly, dynamic characteristics of HPU are obtained by the model simulating within bounded closed sets of varying parameters. Finally, the developed HPU is tested in a deep-sea imitating hull, and the experimental results are well consistent with the theoretical analysis outcomes, which clearly declare that the LVP modeling is a rational way to foresee dynamic performances of HPU. The research approach and model analysis results can be applied to the predictions of working properties and product designs for other deep-sea hydraulic pump.