Co-Optimization of Gas-Electricity Integrated Energy Systems Under Uncertainties

In the United States, natural gas-fired generators have gained increasing popularity in recent years due to low fuel cost and emission, as well as the needed large gas reserves. Consequently, it is worthwhile to consider the high interdependency between the gas and electricity networks. In this dissertation, several co-optimization models for the optimal operation and planning of gas-electricity integrated energy systems (IES) are proposed and investigated considering uncertainties from wind power and load demands. For the coordinated operation of gas-electricity IES: 1) an interval optimization based coordinated operating strategy for the gas-electricity IES is proposed to improve the overall system energy efficiency and optimize the energy flow. The gas and electricity infrastructures are modeled in detail and their operation constraints are fully considered. Then, a demand response program is incorporated into the optimization model, and its effects on the IES operation are investigated. Interval optimization is applied to address wind power uncertainty in IES. 2) a stochastic optimal operating strategy for gas-electricity IES is proposed considering N-1 contingencies in both gas and electricity networks. Since gas pipeline contingencies limit the fuel deliverability to gas-fired units, N-1 contingencies in both gas and electricity networks are considered to ensure that the system operation is able to sustain any possible power transmission or gas pipeline failure. Moreover, wind power uncertainty is addressed by stochastic programming. 3) a robust scheduling model is proposed for gas-electricity IES with uncertain wind power considering both gas and electricity N-1 contingencies. The proposed method is robust against wind power uncertainty to ensure that the system can sustain possible N-1 contingency event of gas pipeline or power transmission. Case studies demonstrate the effectiveness of the proposed models. For the co-optimization planning of gas-electricity IES: a two-stage robust optimization model is proposed for expansion co-planning of gas-electricity IES. The proposed model is solved by the column and constraint generation (C&CG) algorithm. The locations and capacities of new gas-fired generators, power transmission lines, and gas pipelines are optimally determined, which is robust against the uncertainties from electric and gas load growth as well as wind power

Dual Carbamoylations on the Polyketide and Glycosyl Moiety by Asm21 Result in Extended Ansamitocin Biosynthesis

SummaryCarbamoylation is one of the post-PKS modifications in ansamitocin biosynthesis. A novel ansamitocinoside with carbamoyl substitution at the C-4 hydroxyl group of the N-β-D-glucosyl moiety was identified from the ansamitocin producer, Actinosynnema pretiosum. Through biotransformation, the carbamoyltransferase gene asm21 was suggested to be responsible for the carbamoylation of the glucosyl moiety. Three new derivatives without the backbone carbamoyl group were isolated from an asm21 mutant and characterized by NMR spectroscopy. Among them, 18-O-methyl-19-chloroproansamitocin was the major product and the preferred substrate for macrolactam C-7 carbamoylation by Asm21. However, Asm21 exhibited higher catalytic efficiency toward the glucosyl moiety. Furthermore, the dual carbamoylations and N-glycosylation were precisely demonstrated in vivo. This work represents the first biochemical characterization of an O-carbamoyltransferase performing dual actions on both a polyketide backbone and a glycosyl moiety during ansamitocin biosynthesis

Building Marginal Pattern Library with Unbiased Training Dataset for Enhancing Model-Free Load-ED Mapping

Input-output mapping for a given power system problem, such as loads versus economic dispatch (ED) results, has been demonstrated to be learnable through artificial intelligence (AI) techniques, including neural networks. However, the process of identifying and constructing a comprehensive dataset for the training of such input-output mapping remains a challenge to be solved. Conventionally, load samples are generated by a pre-defined distribution, and then ED is solved based on those load samples to form training datasets, but this paper demonstrates that such dataset generation is biased regarding load-ED mapping. The marginal unit and line congestion (i.e., marginal pattern) exhibit a unique characteristic called step change in which the marginal pattern changes when the load goes from one critical loading level (CLL) to another, and there is no change of marginal units within the interval of the two adjacent CLLs. Those loading intervals differ significantly in size. The randomly generated training dataset overfills intervals with large sizes and underfits intervals with small sizes, so it is biased. In this paper, three algorithms are proposed to construct a marginal pattern library to examine this bias according to different computational needs, and an enhancement algorithm is proposed to eliminate the bias for the load-ED dataset generation. Three illustrative test cases demonstrate the proposed algorithms, and comparative studies are constructed to show the superiority of the enhanced, unbiased dataset

Cloning and functional analysis of the naphthomycin biosynthetic gene cluster in Streptomyces sp CS

Naphthomycins (NATs) are 29-membered naphthalenic ansamacrolactam antibiotics with antimicrobial and antineoplastic activities. Their biosynthesis starts from 3-amino-5-hydroxy-benzoic acid (AHBA). By PCR amplification with primers for AHBA synthase and amino-dehydroquinate (aDHQ) synthase, a genomic region containing orthologs of these genes was identified in Streptomyces sp. CS. It was confirmed to be involved in naphthomycin biosynthesis by deletion of a large DNA fragment, resulting in abolishment of naphthomycin production. A 106 kb region was sequenced, and 32 complete ORFs were identified, including five polyketide synthase genes, eight genes for AHBA synthesis, and putative genes for modification, regulation, transport or resistance. Targeted inactivation and complementation experiments proved that the halogenase gene nat1 is responsible for the chlorination of C-30 of NATs. The nat1 mutant could also be complemented with asm12, the halogenase gene of ansamitocin biosynthesis. Likewise, an asm12 mutant could be complemented with nat1, suggesting a similar catalytic mechanism for both halogenases. A putative hydroxylase gene, nat2, was also inactivated, whereupon the biosynthesis of NATs was completely abolished with a tetraketide desacetyl-SY4b accumulated, indicating the participation of nat2 in the formation of the naphthalene ring. The information presented here expands our understanding of the biosynthesis of naphthalenic ansamycins, and may pave the way for engineering ansamacrolactams with improved pharmaceutical properties.National Natural Science Foundation of China; Ministry of Science and Technology[973, 863]; Ministry of Education; Shanghai Municipal Council of Science and Technolog

Special Section on Local and Distributed Electricity Markets

Driven by the Goals of Clean Energy and Zero Carbon Emissions, the Power Industry is Undergoing Significant Transformations. the Rapid Growth of Diverse Distributed Energy Resources (DERs) at Grid Edge Such as Rooftop Photovoltaics (PVs) and Electric Vehicles is Transforming the Traditional Centralized Power Grid Management to a Decentralized, Bottom-Up, and Localized Control Paradigm. Establishing Local and Distribution-Level Electricity Markets Provides an Effective Solution to Managing Large Amounts of Small-Scale DERs. New Regulations Such as the Recent FERC Order 2222 in the U.S. Open the Door to DERs in the Wholesale Markets. through Coordinating the Local and Distribution-Level Markets with the Transmission-Level Wholesale Market, the DERs and Prosumers Can Trade Energy and Flexibility Locally with Each Other and Meanwhile Provide Energy, Flexibility and Ancillary Services to the Bulk Power Grid. during This Transition, There Are Many New Technical Challenges to Address, Calling for Innovative Ideas and Interdisciplinary Research in This Promising Direction. Advanced Information and Communication Technologies (ICT) Are Needed, as a Key Enabler, for the Development and Practical Implementation of Local and Distribution Electricity Markets. Research into Local and Distribution Markets is Strongly Interdisciplinary, Involving the State of the Art in Power Engineering, Economics, and Digital/information Technology. a Broad Spectrum of Contributors from Universities, Industry, Research Laboratories and Policy Makers is Sought to Develop and Present Solutions and Technologies that Will Facilitate and Advance Practical Applications and Implementations of Local and Distribution-Level Electricity Markets to Uncover the Values of DERs

Dlmp-based quantification and analysis method of operational flexibility in flexible distribution networks

With high penetration of flexible resources, operational flexibility of flexible distribution networks (FDNs) is important to ensure high-quality electricity services. This paper proposes a value quantification and analysis method for operational flexibility in FDNs based on distribution locational marginal pricing (DLMP). First, flexibility constraints are formulated from the perspective of node integration, branch transfer, and network aggregation of flexibility. Then, a unified analytical framework for quantifying the operational flexibility is established, in which spatial-temporal transfer of flexibility is modeled with the derivation of flexibility sensitivity factors. Further, a DLMP-based flexibility value quantification model is proposed with nodal net power as the unit for flexibility pricing. The obtained flexibility price can not only quantify flexibility value but also be used to guide the flexible resources. Finally, the effectiveness of the proposed method is validated on a modified IEEE 33-node distribution system and a modified IEEE 123-node distribution system. Results verify that the proposed method can quantify the impact of nodal net power on operational flexibility and effectively improve the overall flexibility performance through the guide of flexibility price

Structural and Functional Analysis of Validoxylamine A 7′-phosphate Synthase ValL Involved in Validamycin A Biosynthesis

Validamycin A (Val-A) is an effective antifungal agent widely used in Asian countries as crop protectant. Validoxylamine A, the core structure and intermediate of Val-A, consists of two C7-cyclitol units connected by a rare C-N bond. In the Val-A biosynthetic gene cluster in Streptomyces hygroscopicus 5008, the ORF valL was initially annotated as a validoxylamine A 7′-phosphate(V7P) synthase, whose encoded 497-aa protein shows high similarity with trehalose 6-phosphate(T6P) synthase. Gene inactivation of valL abolished both validoxylamine A and validamycin A productivity, and complementation with a cloned valL recovered 10% production of the wild-type in the mutant, indicating the involvement of ValL in validoxylamine A biosynthesis. Also we determined the structures of ValL and ValL/trehalose complex. The structural data indicates that ValL adopts the typical fold of GT-B protein family, featuring two Rossmann-fold domains and an active site at domain junction. The residues in the active site are arranged in a manner homologous to that of Escherichia coli (E.coli) T6P synthase OtsA. However, a significant discrepancy is found in the active-site loop region. Also noticeable structural variance is found around the active site entrance in the apo ValL structure while the region takes an ordered configuration upon binding of product analog trehalose. Furthermore, the modeling of V7P in the active site of ValL suggests that ValL might have a similar SNi-like mechanism as OtsA

Minimum Information about a Biosynthetic Gene cluster

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.Chemistry and Chemical Biolog