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.

Control effect and optimization scheme of combined rockboltecable support for a tunnel in horizontally layered limestone:A case study

This study focused on the mechanical behavior of a deep-buried tunnel constructed in horizontally layered limestone,and investigated the effect of a new combined rockboltecable support system on the tunnel response.The Yujingshan Tunnel,excavated through a giant karst cave,was used as a case study.Firstly,a multi-objective optimization model for the rockboltecable support was proposed by using fuzzy mathematics and multi-objective comprehensive decision-making principles.Subsequently,the parameters of the surrounding rock were calibrated by comparing the simulation results obtained by the discrete element method(DEM)with the field monitoring data to obtain an optimized support scheme based on the optimization model.Finally,the optimization scheme was applied to the karst cave section,which was divided into the B-and C-shaped sections.The distribution range of the rockboltecable support in the C-shaped section was larger than that in the B-shaped section.The field monitoring results,including tunnel crown settlement,horizontal convergence,and axial force of the rockboltecable system,were analyzed to assess the effectiveness of the optimization scheme.The maximum crown settlement and horizontal convergence were measured to be 25.9 mm and 35 mm,accounting for 0.1%and 0.2%of the tunnel height and span,respectively.Although the C-shaped section had poorer rock properties than the B-shaped section,the crown settlement and horizontal convergence in the C-shaped section ranged from 46%to 97%of those observed in the B-shaped section.The cable axial force in the Bshaped section was approximately 60%of that in the C-shaped section.The axial force in the crown rockbolt was much smaller than that in the sidewall rockbolt.Field monitoring results demonstrated that the optimized scheme effectively controlled the deformation of the layered surrounding rock,ensuring that it remained within a safe range.These results provide valuable references for the design of support systems in deep-buried tunnels situated in layered rock masses.

Optimization and Characterization of Combined Degumming Process of Typha angustata L. Stem Fibers

Plant derived natural fibers have been widely investigated as alternatives to synthetic fibers in reinforcing polymers.Researchers over the years have explored many plant fibers using different extraction processes to study their physical,chemical,and mechanical properties.In this context,the present study relates to the extraction,characterization,and optimization of Typha angustata L.stem fibers.For this purpose,desirability functions and response surface methodology were applied to simultaneously optimize the diameter(D),linear density(LD);yield(Y),lignin fraction(L),and tenacity(T)of Typha stem fibers.Typha stems have been subjected to both alkali(NaOH)and enzymatic(pectinex ultra-SPL)treatments.Three levels of process variables including enzyme concentration(10,15,and 20 ml/L)and treatment duration(10,15,and 20 days)were used to design the experiments according to the factorial design.Experimental results were examined by analysis of variance and fitted to second order polynomial model using multiple regression analysis.The Derringer’s desirability function released that the values of process variables generating optimized diameter,linear density,yield,lignin ratio and tenacity are 20 ml/L and 20 days for concentration of pectinex ultra-SPL enzyme and treatment duration,respectively.Confirmation was performed and high degree of correlation was found between the experimental and statistical values.Moreover,the morphological structure has been investigated by the scanning electron microscope,showing a crenelated structure of ultimate fiber bundles of cellulose composing the Typha fiber.Compared to Typha stem non-treated fibers(TSNTF),Typha stem combined treated fibers(TSCTF),brings to improve mechanical properties.This change in mechanical properties is affected by modifying the fiber structure showing alpha cellulose of(66.86%)and lignin ratio of(10.83%)with a crystallinity index of(58.47%).

Developing high-efficiency base editors by combining optimized synergistic core components with new types of nuclear localization signal peptide

The clustered regularly interspaced short palindromic repeats(CRISPR)–CRISPR-associated protein(Cas) system has been widely used for genome editing. In this system, the cytosine base editor(CBE) and adenine base editor(ABE) allow generating precise and irreversible base mutations in a programmable manner and have been used in many different types of cells and organisms. However, their applications are limited by low editing efficiency at certain genomic target sites or at specific target cytosine(C) or adenine(A) residues. Using a strategy of combining optimized synergistic core components, we developed a new multiplex super-assembled ABE(sABE) in rice that showed higher base-editing efficiency than previously developed ABEs. We also designed a new type of nuclear localization signal(NLS) comprising a FLAG epitope tag with four copies of a codon-optimized NLS(F4NLS^(r2)) to generate another ABE named F4NLS-sABE. This new NLS increased editing efficiency or edited additional A at several target sites. A new multiplex super-assembled CBE(sCBE) and F4NLS^(r2) involved F4NLS-sCBE were also created using the same strategy. F4NLS-sCBE was proven to be much more efficient than sCBE in rice. These optimized base editors will serve as powerful genome-editing tools for basic research or molecular breeding in rice and will provide a reference for the development of superior editing tools for other plants or animals.

OPTIMAL COMBINING PREDICTION FOR BLENDING EFFICIENCY

By means of analysing the mechanism of blending materials,a general blending efficiency model was proposed.Applying this general model to an example 9 a suitable formula of blending efficiency which is more accurate than those in papers[2-3]was obtained.Finally,a high-precision optimal combining prediction formula for calculating blending efficiency was proposed.

A Subdivision-Based Combined Shape and Topology Optimization in Acoustics

We propose a combined shape and topology optimization approach in this research for 3D acoustics by using the isogeometric boundary element method with subdivision surfaces.The existing structural optimization methods mainly contain shape and topology schemes,with the former changing the surface geometric profile of the structure and the latter changing thematerial distribution topology or hole topology of the structure.In the present acoustic performance optimization,the coordinates of the control points in the subdivision surfaces fine mesh are selected as the shape design parameters of the structure,the artificial density of the sound absorbing material covered on the structure surface is set as the topology design parameter,and the combined topology and shape optimization approach is established through the sound field analysis of the subdivision surfaces boundary element method as a bridge.The topology and shape sensitivities of the approach are calculated using the adjoint variable method,which ensures the efficiency of the optimization.The geometric jaggedness and material distribution discontinuities that appear in the optimization process are overcome to a certain degree by the multiresolution method and solid isotropic material with penalization.Numerical examples are given to validate the effectiveness of the presented optimization approach.

Robust optimal dispatch strategy of integrated energy system considering CHP-P2G-CCS

Integrated energy systems(IESs)can improve energy efficiency and reduce carbon emissions,essential for achieving peak carbon emissions and carbon neutrality.This study investigated the characteristics of the CHP model considering P2G and carbon capture systems,and a two-stage robust optimization model of the electricity-heat-gascold integrated energy system was developed.First,a CHP model considering the P2G and carbon capture system was established,and the electric-thermal coupling characteristics and P2G capacity constraints of the model were derived,which proved that the model could weaken the electric-thermal coupling characteristics,increase the electric power regulation range,and reduce carbon emissions.Subsequently,a two-stage robust optimal scheduling model of an IES was constructed,in which the objective function in the day-ahead scheduling stage was to minimize the start-up and shutdown costs.The objective function in the real-time scheduling stage was to minimize the equipment operating costs,carbon emission costs,wind curtailment,and solar curtailment costs,considering multiple uncertainties.Finally,after the objective function is linearized with a ψ-piecewise method,the model is solved based on the C&CG algorithm.Simulation results show that the proposed model can effectively absorb renewable energy and reduce the total cost of the system.

OPTIMAL MODEL OF COMBINED PHASE CENTER FOR HORN FEEDS AND ITS COMPUTATIONAL METHOD

A definition of combined phase center for horn feeds is given.Formulas of E-planeand H-plane combined phase center for conical horns and the corresponding Optimal model arepresented,and a fast optimization method for solving this model is described.By using thismethod,the phase center of corrugated horn is discussed and calculated,and the variation of thephase center with distance and operating frequency is given.

Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

Aiming at the problems of large-scale wind and solar grid connection,how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations,a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed.Firstly,the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output,obtains the optimal output value under the economic conditions of each new energy station,and then obtains the maximum consumption space of the new energy station.Secondly,based on the optimization results of the first stage,the second stage dispatching model uses the dispatching method of fuzzy comprehensive ranking priority to prioritize the new energy stations,and then makes a fair allocation to the dispatching of the wind and solar stations.Finally,the analysis of a specific example shows that themodel can take into account the fairness of active power distribution of new energy stations on the basis of ensuring the economy of system operation,make full use of the consumption space,and realize the medium and long-term fairness distribution of dispatching plan.

Applying Convex Optimal Power Flow to Combined Economic and Emission Dispatch

This paper addresses the problem of reducing CO2 emissions by applying convex optimal power flow model to the combined economic and emission dispatch problem. The large amount of CO2 emissions in the power industry is a major source of global warming effect. An efficient and economic approach to reduce CO2 emissions is to formulate the emission reduction problem as emission dispatch problem and combined with power system economic dispatch (ED). Because the traditional optimal power flow (OPF) model used by the economic dispatch is nonlinear and nonconvex, current nonlinear solvers are not able to find the global optimal solutions. In this paper, we use the convex optimal power flow model to formulate the combined economic and emission dispatch problem. The advantage of using convex power flow model is that global optimal solutions can be obtained by using mature industrial strength nonlinear solvers such as MOSEK. Numerical results of various IEEE power network test cases confirm the feasibility and advantage of convex combined economic and emission dispatch (CCEED).

Prediction of a maximum pull-out load of anchor bolts using an optimal combination model

The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.

Optimal Control of Combined Sewer Overflows

Combined sewer networks carry wastewater and stormwater together.Capacity limitation of these sewer networks results in combined sewer overflows(CSOs)during high-intensity storms.Untreated CSOs when directly discharged to the nearby natural water bodies cause many environmental problems.Controlling existing urban sewer networks is one possible way of addressing the issues in urban wastewater systems.However,it is still a challenge,when considering the receiving water quality effects.This paper presents an evolutionary constrained multi-objective optimization approach to control the existing combined sewer networks.The control of online storage tanks was taken into account when controlling the combined sewer network.The developed multi-objective approach considers two important objectives,i.e.the pollution load to the receiving water from CSOs and the cost of the wastewater treatment.The proposed optimization algorithm is applied here to a realistic interceptor sewer system to demonstrate its effectiveness.

Optimization of Hybrid Combination and an Application Example for Strawberry Breeding

This study was conducted to select new strawberry cultivars with early maturity, disease resistance and high quality, by optimizing the hybrid combinations of Benihoppe, a Japanese strawberry cultivar, which is extensively planted but not resistant to anthrax. The reciprocal crosses were performed using Benihoppe, as the female parent, four disease-resistant European cultivars Albion, Camino Real, Ven- tana and Virginia, and one Japanese cultivar Meiho as the male parent. Then, the seedling propagation coefficient, disease resistance, fruit quality and yield of F1 gen- eration of the combinations were detected and compared. Besides, the breeding and traits of a new cultivar F1-40 developed from the cross between Benihoppe and Mei- ho were introduced as an instance to prove the feasibility of the combinations/lines.

A Financial Approach to Evaluate an Optimized Combined Cooling, Heat and Power System

Iran’s removing subsidy from energy carrier in four years ago leads to spike electricity price dramatically. This abrupt change increases the interest on distributed generation (DG) because of its several benefits such as lower electricity generation price. In Iran among all type of DGs, because of wide natural gas network infrastructure and several incentives that government legislated to support combined cooling, heat and power (CCHP) investors, this type of technology is more prevalent in comparison with other technologies. Between existing CCHP technologies, certain economic choices are to be taken into account. For different buildings with different load curves, suitable size and operation of CCHP should be calculated to make the project more feasible. If CCHP does not well suited for a position, then the whole energy efficiency would be plunged significantly. In this paper, a model to find the optimal size and operation of CCHP and auxiliary boiler for any users is proposed by considering an integrated view of electricity and natural gas network using GAMS software. Then this method is applying for a hospital in Tehran as a real case study. Finally, by applying COMFAR III software, useful financial parameters and sensitivity analysis are calculated.

Combined model based on optimized multi-variable grey model and multiple linear regression

The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.

A Hybrid Multi-Objective Evolutionary Algorithm for Optimal Groundwater Management under Variable Density Conditions

In this paper, a new hybrid multi-objective evolutionary algorithm （MOEA）, the niched Pareto tabu search combined with a genetic algorithm （NPTSGA）, is proposed for the management of groundwater resources under variable density conditions. Relatively few MOEAs can possess global search ability contenting with intensified search in a local area. Moreover, the overall searching ability of tabu search （TS） based MOEAs is very sensitive to the neighborhood step size. The NPTSGA is developed on the thought of integrating the genetic algorithm （GA） with a TS based MOEA, the niched Pareto tabu search （NPTS）, which helps to alleviate both of the above difficulties. Here, the global search ability of the NPTS is improved by the diversification of candidate solutions arising from the evolving genetic algorithm population. Furthermore, the proposed methodology coupled with a density-dependent groundwater flow and solute transport simulator, SEAWAT, is developed and its performance is evaluated through a synthetic seawater intrusion management problem. Optimization results indicate that the NPTSGA offers a tradeoff between the two conflicting objectives. A key conclusion of this study is that the NPTSGA keeps the balance between the intensification of nondomination and the diversification of near Pareto-optimal solutions along the tradeoff curves and is a stable and robust method for implementing the multi-objective design of variable-density groundwater resources.

Strengthening pelletization of manganese ore fines containing high combined water by high pressure roll grinding and optimized temperature elevation system

Pelletization is one of useful processes for the agglomeration of iron ore or concentrates. However, manganese ore fines are mainly agglomerated by sintering due to its high combined water which adversely affects the roasting performance of pellets. In this work, high pressure roll grinding(HPRG) process and optimization of temperature elevation system were investigated to improve the strength of fired manganese ore pellets. It is shown that the manganese ore possesses good ballability after being pretreated by HPRG twice, and good green balls were produced under the conditions of blending 2.0% bentonite in the feed, balling for 7 min at 16.00% moisture. High quality roasted pellets with the compressive strength of 2711 N per pellet were manufactured through preheating at 1050 °C for 10 min and firing at 1335 °C for 15 min by controlling the cracks formation. The fired manganese pellets keep the strength by the solid interconnection of recrystallized pyrolusite grains and the binding of manganite liquid phase which filled the pores and clearance among minerals. The product pellets contain high Mn grade and low impurities, and can be used to smelt ferromanganese, which provides a possible way to use imported manganese ore fines containing high combined water to produce high value ferromanganese.

Optimization principle of combined surface and underground mining and its applications

The pit limit optimization is discussed, which is one of the most important problems in the combined min-ing method, on the basis of the economic model of ore-blocks. A new principle of the limit optimization is put for-ward through analyzing the limitations of moving cone method under such conditions. With a view to recovering asmuch mineral resource as possible and making the maximum profit from the whole deposit, the new principle is tomaximize the sum of gain from both open-pit and underground mining. The mathematical models along the horizon-tal and vertical directions and modules for software package (DM&MCAD) have been developed and tested inTonglushan Copper Mine. It has been proved to be rather effective in the mining practice.

Optimal Operation and Size for an Energy Hub with CCHP

The interest in distributed generation has been increasing in recent years, especially due to technical devel- opment on generation systems that meet environmental and energy policy concerns. One of the most impor- tant distributed energy technologies is Combined Cooling, Heat and Power (CCHP) systems. CCHP is a small and self-contained electric, heating and cooling generation plant that can provide power for households, commercial or industrial facilities. It can reduce power loss and enhance service reliability in distribution systems. The proposed method in this paper determines the optimal size and operation of CCHP, auxiliary boiler and also heat storage unit as elements of an energy hub, for users by an integrated view of electricity and natural gas network. Authors apply cost and benefit analysis in the optimization. To confirm the proposed method, the optimum sizes of these elements are determined for a hotel in Tehran as a case study.

On units combination and commitment optimization for electric power production

Electric power system is one of the most important and complex engineering in modern society, supplying main and general power for social production and social life. Meanwhile, since it is a productive system with both high input and output, it has an obvious economic significance to improve its operating efficiency. For an example, an unit is 10 GW scale, if its standard coal consumption can be decreased with 1 g/kW·h, it can save about 5 000 tons standard coal per year. It will be discussed mainly that how to establish optimization model and its numerical algorithm for operating management of the electric power system. The idea on establishing optimization model is how to dispatch work state of units or power plants, so that total cost of fuel consumption for generation is reduced to the minimum. Here the dispatch is to decide which unit or plant to operate, which unit or plant to stop running, how much power should be generated for those operating units or plants at each given time interval.