Very Short-Term Probabilistic Prediction Method for Wind Speed Based on ALASSO-Nonlinear Quantile Regression and Integrated Criterion

To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage and selection operator (ALASSO) and integrated criterion (IC) is proposed. The ALASSO method is studied for shrinkage of output weights and selection of variables. Furthermore, for the better performance of PIs, composite weighted linear programming (CWLP) is proposed to modify the conventional linear programming cost function of quantile regression (QR), by combining it with Bayesian information criterion (BIC) as an IC to optimize the coefficients of PIs. Then, the multiple fold cross model (MFCM) is utilized to improve the PIs performance. Multistep probabilistic prediction of 15-minute wind speed is performed based on the real wind farm data from the northeast of China. The effectiveness of the proposed approach is validated through the performances' comparisons with conventional methods.

Identification of multiple regulatory genes involved in TGase production in Streptomyces mobaraensis DSM 40587

Microbial transglutaminase(TGase)is a protein that is secreted in a mature form and finds wide applications in meat products,tissue scaffold crosslinking,and textile engineering.Streptomyces mobaraensis is the only licensed producer of TGase.However,increasing the production of TGase using metabolic engineering and heterologous expression approaches has encountered challenges in meeting industrial demands.Therefore,it is necessary to identify the regulatory networks involved in TGase biosynthesis to establish a stable and highly efficient TGase cell factory.In this study,we employed a DNA-affinity capture assay and mass spectrometry analysis to discover several transcription factors.Among the candidates,eight were selected and found to impact TGase biosyn-thesis.Notably,SMDS_4150,an AdpA-family regulator,exhibited a significant influence and was hence named AdpASm.Through electrophoretic mobility shift assays,we determined that AdpASm regulates TGase biosynthesis by directly repressing the transcription of tg and indirectly inhibiting the transcription of SMDS_3961.The latter gene encodes a LytR-family positive regulator of TGase biosynthesis.Additionally,AdpASm exhibited negative regulation of its own transcription.To further enhance TGase production,we combined the overexpression of SMDS_3961 with the repression of SMDS_4150,resulting in a remarkable improvement in TGase titer from 28.67 to 52.0 U/mL,representing an 81.37%increase.This study establishes AdpA as a versatile regulator involved in coordinating enzyme biosynthesis in Streptomyces species.Furthermore,we elucidated a cascaded regulatory network governing TGase production.

浅紫灰链霉菌CQ01819及其次级代谢产物的定向发掘

【目的】采用特征次级代谢产物生物合成的保守功能基因探针,定向分离土壤中产生特征次级代谢产物的菌种资源,借助基因转录分析为导向的培养基优化方法,获得目标次生代谢产物。【方法】首先,根据5种特征次级代谢产物保守的合成功能基因设计简并引物,定向从土壤样品中筛选、分离并纯化菌株。然后,以RT-qPCR为指导开展目标产物的发酵培养基优化;最后,对菌株进行发酵,利用多种色谱技术分离纯化目标天然产物,并结合高分辨质谱与核磁共振等技术对所获得的化合物进行结构鉴定。【结果】从土壤中筛选得到了一株AHBA合酶基因和环氧化酶基因均为阳性的链霉菌菌株(编号为CQ01819),根据转录分析优化发酵培养基,最终从该菌株分离纯化得到了含有AHBA结构单元的丝裂霉素C、聚醚类抗生素莫能霉素A和缬吲霉素。【结论】本研究通过菌株的定向分离纯化,筛选得到了产生预期抗生素的浅紫灰链霉菌菌株CQ01819;基于RT-qPCR指导的发酵培养基优化,确定了菌株的发酵条件;获得发酵粗提物后,采用多种色谱整合技术和光谱分析策略,快速分离并鉴定了目标产物。该研究为目标菌种资源的定向筛选、菌株的发酵条件的快速优化和化合物的定向分离提供了较好的参考。

抗细菌药物默诺霉素的化学生物学研究进展

默诺霉素(moenomycins)家族类化合物主要是由链霉菌产生,属于磷酸糖脂类抗生素。该类化合物通过与细菌细胞壁肽聚糖糖基转移酶(peptidoglycan transferase,PGT)的活性位点结合,可以抑制众多革兰氏阳性细菌细胞壁的合成,具有很强的生物活性和重要的应用开发潜力。本文针对默诺霉素的化学结构、生物活性机制、抗性机制、生物合成研究途径、外排机制和新结构创制等化学生物学方面进行了系统综述,并对默诺霉素化学生物学研究现状以及可能存在的问题进行了总结,旨在为高活性磷酸糖脂类临床药物的研究与开发提供借鉴。

Optimal Energy Flow and Nodal Energy Pricing in Carbon Emission-embedded Integrated Energy Systems

Green energy is driving the evolutions of energy industry and carbon emission is becoming an important concern.Considering the increasing couplings among various energy sectors,this paper investigates multi-period optimal energy flow and energy pricing in carbon-emission embedded integrated energy systems,including electricity,natural gas,and district heating networks.Firstly,an optimal scheduling model of integrated energy systems was proposed in this paper.The models of DC power flow,natural gas pipeline flow and heating network energy flow are presented and linearized for the optimization problem.Natural gas-fired generators and combined heat and power(CHP)units are modeled as coupling components of electricitygas and electricity-heating networks.Then,based on the optimal scheduling model,the locational marginal prices(LMP)for electricity,natural gas and heating network are determined.Moreover,the carbon emission caused by energy production has been taken into account in the optimal scheduling and energy pricing process.Finally,case studies on a combined network consisting of IEEE 39-bus system,Belgium 20-node natural gas system and 6-node heating system demonstrate the effectiveness of the proposed model and the impacts of carbon emission on system scheduling and LMP.

Day-ahead Scheduling of Multi-carrier Energy Systems with Multi-type Energy Storages and Wind Power

The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is proposed in a scenario-based stochastic programming framework.The structure of the IES consists of electricity,natural gas,and heating networks which are all included in the model.Operational constraints for IES incorporating multi-type energy storage devices are also considered.The constraints of the electricity network,natural gas network and heating network are formulated,and non-linear constraints are linearized.The calculation method for the correlation of wind speed between wind farms based on historical data is proposed.Uncertainties of correlated wind power were represented by creating multiple representative scenarios with different probabilities,and this was done using the Latin hyper-cube sampling(LHS)method.The stochastic scheduling model is formulated as a mixed integer linear programming(MILP)problem with the objective function of minimizing the total expected operation cost.Numerical results on a modified PJM 5-bus electricity system with a seven-node natural gas system and a six-node heating system validate the proposed model.The results demonstrate that multi-type energy storage devices can help reduce wind power curtailments and improve the operational flexibility of IES.

Day-ahead optimal scheduling method for grid-connected microgrid based on energy storage control strategy

A day-ahead optimal scheduling method for a grid-connected microgrid based on energy storage(ES)control strategy is proposed in this paper.The proposed method optimally schedules ES devices to minimize the total operating costs while satisfying the load requirements of cold,heat,and electricity in microgrids.By modeling the operating cost function of each stage,the proposed method is able to adapt to different types of electricity markets and pricing mechanisms.The technical characteristics of ES,such as self-discharge and round-trip efficiency,are considered in the control strategy with a multistage process model.An improved dynamic programing method is used to solve the optimization model.Finally,case studies are provided to illustrate the application process and verify the proposed method.

Estimating inter-area dominant oscillation mode in bulk power grid using multi-channel continuous wavelet transform

This paper proposes a novel continuous wavelet transform(CWT) based approach to holistically estimate the dominant oscillation using measurement data from multiple channels. CWT has been demonstrated to be effective in estimating power system oscillation modes.Using singular value decomposition(SVD) technique, the original huge phasor measurement unit(PMU) datasets are compressed to finite useful measurement data which contain critical dominant oscillation information. Further,CWT is performed on the constructed measurement signals to form wavelet coefficient matrix(WCM) at the same dilation. Then, SVD is employed to decompose the WCMs to obtain the maximum singular value and its right eigenvector. A singular value vector with the entire dilation is constructed through the maximum singular values. The right eigenvector corresponding to the maximum singular value in the singular-value vector is adopted as the input of CWT to estimate the dominant modes. Finally, the proposed approach is evaluated using the simulation data from China Southern Power Grid(CSG) as well as the actual field-measurement data retrieved from the PMUs of CSG.The simulation results demonstrate that the proposed approach performs well to holistically estimate the dominant oscillation modes in bulk power systems.

Conversion of the high-yield salinomycin producer Streptomyces albus BK3-25 into a surrogate host for polyketide production

An ideal surrogate host for heterologous production of various natural products is expected to have efficient nutrient utilization,fast growth,abundant precursors and energy supply,and a pronounced gene expression.Streptomyces albus BK3-25 is a high-yield industrial strain producing type-Ⅰ polyketide sahnomycin,with a unique ability of bean oil utilization.Its potential of being a surrogate host for heterologous production of PKS was engineered and evaluated herein.Firstly,introduction of a three-gene cassette for the biosynthesis of ethylmalonyl-CoA resulted in accumulation of ethylmalonyl-CoA precursor and sahnomycin,and subsequent deletion of the sahnomycin biosynthetic gene cluster resulted in a host with rich supplies of common polyketide precursors,including malonyl-CoA,methylmalonyl-CoA,and ethylmalonyl-CoA.Secondly,the energy and reducing force were measured,and the improved accumulation of ATP and NADPH was observed in the mutant.Furthermore,the strength of a series of selected endogenous promoters based on microarray data was assessed at different growth phases,and a strong constitutive promoter was identified,providing a useful tool for further engineered gene expression.Finally,the potential of the BK3-25 derived host ZXJ-6 was evaluated with the introduction of the actinorhodin biosynthetic gene cluster from Streptomyces coelicolor,and the heterologous production of actinorhodin was obtained.This work clearly indicated the potential of the high-yield sahnomycin producer as a surrogate host for heterologous production of polyketides,although more genetic manipulation should be conducted to streamline its performance.

A Dispatching Method for Integrated Energy System Based on Dynamic Time-interval of Model Predictive Control

In integrated energy systems(IESs),traditional fixed time-interval dispatching scheme is unable to adapt to the need of dynamic properties of the transient network,demand response characteristics,dispatching time scales in energy subsystems and renewable power uncertainties.This scheme may easily result in uneconomic source-grid-load-storage operations in IES.In this paper,we propose a dispatching method for IES based on dynamic time-interval of model predictive control(MPC).We firstly build models for energy sub-systems and multi-energy loads in the power-gas-heat IES.Then,we develop an innovative optimization method leveraging trajectory deviation control,energy control,and cost control frameworks in MPC to handle the requirements and constraints over the timeinterval of dispatching.Finally,a dynamic programming algorithm is introduced to efficiently solve the proposed method.Experiments and simulation results prove the effectiveness of the method.

Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-ellipsoidal Uncertainty Set

The large-scale integration of renewable energy sources (RESs) brings huge challenges to the power system. A cost-effective reserve deployment and uncertainty pricing mechanism are critical to deal with the uncertainty and variability of RES. To this end, this paper proposes a novel locational marginal pricing mechanism in day-ahead market for managing uncertainties from RES. Firstly, an improved multi-ellipsoidal uncertainty set (IMEUS) considering the temporal correlation and conditional correlation of wind power forecasting is formulated to better capture the uncertainty of wind power. The dimension of each ellipsoidal subset is optimized based on a comprehensive evaluation index to reduce the invalid region without large loss of modeling accuracy, so as to reduce the conservatism. Then, an IMEUS-based robust unit commitment (RUC) model and a robust economic dispatch (RED) model are established for the day-ahead market clearing. Both the reserve cost and ramping constraints are considered in the overall dispatch process. Furthermore, based on the Langrangian function of the RED model, a new locational marginal pricing mechanism is developed. The uncertainty locational marginal price (ULMP) is introduced to charge the RES for its uncertainties and reward the generators who provide reserve to mitigate uncertainties. The new pricing mechanism can provide effective price signals to incentivize the uncertainty management in the day-ahead market. Finally, the effectiveness of the proposed mechanism is verified via numerous simulations on the PJM 5-bus system and IEEE 118-bus system.

Improving acarbose production and eliminating the by-product component C with an efficient genetic manipulation system of Actinoplanes sp.SE50/110

Theα-glucosidase inhibitor acarbose is commercially produced by Actinoplanes sp.and used as a potent drug in the treatment of type-2 diabetes.In order to improve the yield of acarbose,an efficient genetic manipulation system for Actinoplanes sp.was established.The conjugation system between E.coli carryingØC31-derived integrative plasmids and the mycelia of Actinoplanes sp.SE50/110 was optimized by adjusting the parameters of incubation time of mixed culture(mycelia and E.coli),quantity of recipient cells,donor-to-recipient ratio and the concentration of MgCl2,which resulted in a high conjugation efficiency of 29.4%.Using this integrative system,a cloned acarbose biosynthetic gene cluster was introduced into SE50/110,resulting in a 35%increase of acarbose titer from 2.35 to 3.18 g/L.Alternatively,a pIJ101-derived replicating plasmid combined with the counter-selection system CodA(sm)was constructed for gene inactivation,which has a conjugation frequency as high as 0.52%.Meanwhile,almost all 5-flucytosine-resistant colonies were sensitive to apramycin,among which 75%harbored the successful deletion of targeted genes.Using this replicating vector,the maltooligosyltrehalose synthase gene treY responsible for the accumulation of component C was inactivated,and component C was eliminated as detected by LC-MS.Based on an efficient genetic manipulation system,improved acarbose production and the elimination of component C in our work paved a way for future rational engineering of the acarbose-producing strains.

Comparative functional genomics of the acarbose producers reveals potential targets for metabolic engineering

Theα-glucosidase inhibitor acarbose is produced in large-scale by strains derived from Actinoplanes sp.SE50 and used widely for the treatment of type-2 diabetes.Compared with the wild-type SE50,a high-yield derivative Actinoplanes sp.SE50/110 shows 2-fold and 3–7-fold improvement of acarbose yield and acb cluster transcription,respectively.The genome of SE50 was fully sequenced and compared with that of SE50/110,and 11 SNVs and 4 InDels,affecting 8 CDSs,were identified in SE50/110.The 8 CDSs were individually inactivated in SE50.Deletions of ACWT_4325(encoding alcohol dehydrogenase)resulted in increases of acarbose yield by 25%from 1.87 to 2.34 g/L,acetyl-CoA concentration by 52.7%,and PEP concentration by 22.7%.Meanwhile,deletion of ACWT_7629(encoding elongation factor G)caused improvements of acarbose yield by 36%from 1.87 to 2.54 g/L,transcription of acb cluster,and ppGpp concentration to 2.2 folds.Combined deletions of ACWT_4325 and ACWT_7629 resulted in further improvement of acarbose to 2.83 g/L(i.e.76%of SE50/110),suggesting that the metabolic perturbation and improved transcription of acb cluster caused by these two mutations contribute substantially to the acarbose overproduction.Enforced application of similar strategies was performed to manipulate SE50/110,resulting in a further increase of acarbose titer from 3.73 to 4.21 g/L.Therefore,the comparative genomics approach combined with functional verification not only revealed the acarbose overproduction mechanisms,but also guided further engineering of its high-yield producers.

Hybrid component and configuration model for combined-cycle units in unit commitment problem

This letter proposes a novel hybrid component and configuration model for combined-cycle gas turbines(CCGTs) participating in independent system operator(ISO) markets. The proposed model overcomes the inaccuracy issues in the current configuration-based model while retaining its simple and flexible bidding framework of configuration-based models. The physical limitations—such as minimum online/offline time and ramping rates—are modeled for each component separately, and the cost is calculated with the bidding curves from the configuration modes. This hybrid mode can represent the current dominant bidding model in the unit commitment problem of ISOs while treating the individual components in CCGTs accurately. The commitment status of the individual components is mapped to the unique configuration mode of the CCGTs. The transitions from one configuration mode to another are also modeled. No additional binary variables are added, and numerical case studies demonstrate the effectiveness of this model for CCGT units in the unit commitment problem.

Orbiting Optimization Model for Tracking Voltage Security Region Boundary in Bulk Power Grids

A voltage security region(VSR)is a powerful tool for monitoring the voltage security in bulk power grids with high penetration of renewables.It can prevent cascading failures in wind power integration areas caused by serious over or low voltage problems.The bottlenecks of a VSR for practical applications are computational efficiency and accuracy.To bridge these gaps,a general optimization model for tracking a voltage security region boundary(VSRB)in bulk power grids is developed in this paper in accordance with the topological characteristics of the VSRB.First,the initial VSRB point on the VSRB is examined with the traditional OPF by using the base case parameters as initial values.Then,the rest of the VSRB points on the VSRB are tracked one after another,with the proposed optimization model,by using the parameters of the tracked VSRB point as the initial value to explore its adjacent VSRB point.The proposed approach can significantly improve the computational efficiency of the VSRB tracking over the existing algorithms,and case studies,in the WECC 9-bus and the Polish 2736-bus test systems,demonstrate the high accuracy and efficiency of the proposed approach on exploring the VSRB.