Optimal Operation of Integrated Heat and Electricity Systems:A Tightening McCormick Approach

Combined heat and electricity operation with variable mass flow rates promotes flexibility,economy,and sustainability through synergies between electric power systems(EPSs)and district heating systems(DHSs).Such combined operation presents a highly nonlinear and nonconvex optimization problem,mainly due to the bilinear terms in the heat flow model—that is,the product of the mass flow rate and the nodal temperature.Existing methods,such as nonlinear optimization,generalized Benders decomposition,and convex relaxation,still present challenges in achieving a satisfactory performance in terms of solution quality and computational efficiency.To resolve this problem,we herein first reformulate the district heating network model through an equivalent transformation and variable substitution.The reformulated model has only one set of nonconvex constraints with reduced bilinear terms,and the remaining constraints are linear.Such a reformulation not only ensures optimality,but also accelerates the solving process.To relax the remaining bilinear constraints,we then apply McCormick envelopes and obtain an objective lower bound of the reformulated model.To improve the quality of the McCormick relaxation,we employ a piecewise McCormick technique that partitions the domain of one of the variables of the bilinear terms into several disjoint regions in order to derive strengthened lower and upper bounds of the partitioned variables.We propose a heuristic tightening method to further constrict the strengthened bounds derived from the piecewise McCormick technique and recover a nearby feasible solution.Case studies show that,compared with the interior point method and the method implemented in a global bilinear solver,the proposed tightening McCormick method quickly solves the heat–electricity operation problem with an acceptable feasibility check and optimality.

Effects of topiramate versus other antiepileptic drugs on the cognitive function of patients with epilepsy

BACKGROUND： Only very large dose of topiramate has neurotoxicity, indicating that topiramate has low neurotoxicity and high safety. The residual rate of topiramate is affected by many cognitive-related adverse effects. Patients who take topiramate often accompany with thought slowness, difficulty in finding words, dyscalculia, blunt reaction, attention decreasing, memory deterioration, etc. OBJECTIVE： To compare the effects of topiramate with traditional anti-epileptic drugs （including carbamazepine and Valproic acid （VPA） on cognitive function of patients with epilepsy. DESIGN： Observational experiment, self-control and intergroup comparison. SETTING： Sichuan Academy of Medical Science. PARTICIPANTS： Eighty-seven inpatients and outpatients with newly diagnosed epilepsy who received preliminary diagnosis and follow-up in the Department of Neurology, Sichuan People＇s Hospital between January 2004 and June 2006 were involved in this survey. They were diagnosed according to disease history and electroencephalogram （EEG）. The onset type was diagnosed following the definition of epilepsy and epileptic syndrome in 1989 International Anti-epileptic League. The involved patients and their relatives were informed of detection and therapeutic regimen. The patients were assigned into two groups according to table of random digit： traditional antiepileptic drugs group （AEDs group, n =44） and topiramate （TPM） group （n =43）. METHODS： （1）Among the patients in AEDs group, carbamazepine was the first choice for 21 patients with partial seizures or partial secondarily generalized seizures, and VPA for 23 patients with generalized seizures. The initial dose of carbamazepine was 300 mg/d, and that of VPA was 500 mg/d. Patients in the TPM group took TPM with the initial dose of 25 mg/d, increased by 25 mg/d each week to target dose 150 mg/d within 8 weeks. （2） Curative effect was graded into 4 degrees： markedly effective, effective, ineffective and aggravated. Total effective rate was calculated. （3） Cognitive function of patients was tested before and 6 months after administration by using Wechsler Adult Intelligence Scale（WAIS） or Wechsler Intelligence Scale for Children （WISC, Chinese edition）, （Higher scores indicated better cognitive function）, Stroop color word interference, test of memory of past numbers, test of telling the names of fruits and vegetables within 1 minute （Shorter time for reading word, telling color and memory of past numbers demonstrated better cognitive function. Less errors in reading words, telling colors and memory of past numbers, numbering and telling the names of fruits and vegetables within 1 minute indicated better cognitive function）, etc. totally 22 items. （4） t test and paired t test were used for measurement data. MAIN OUTCOME MEASURES： Clinical curative effects and adverse reactions as well as neurological tests. RESULTS： Eighty-four pationts praticipated final analysis and 3 dropped out. （1） Inthe AEDS group and TPM group, total effective rate was 86% and 99%, respectively. （2） In the AEDs group, there were no significant changes in the scores of each test of WIS before and after treatment （P 〉 0.05）. In the TPM group, total IQ, word scores, verbal IQ and digit span scores were significantly decreased （ t =2.097 - 4.423, P 〈 0.05 - 0.01 ） .Following treatment, the time for reading word and telling color for patients in the AEDs group was prolonged in Stroop color interference test （ t = - 2.304, - 2.454, P 〈 0.05 ）, and time for reading word and memory of past numbers for patients in the topiramate group was significantly prolonged （ t = - 3.054, 2.272, P 〈 0.01, 0.05 ）. （3）There were no significant differences in scores of WIS before and after treatment in AEDs group and TPM group （P 〉 0.05）. Following treatment, verbal IQ, word scores, total IQ, digit span of patients in the TPM group were significantly lower than those in the AEDs group （t =2.052 - 3.297, P 〈 0.05- 0.01 ） .There were no significant differences in Stroop color word interference, memory of past numbers and telling the names of fruits and vegetables within 1 minute before and after treatment in AEDs group and TPM group （P 〉 0.05）. CONCLUSION： （1） Moderate and small doses of both TPM and AEDs may lead to mild cognitive function impairment of patients, mainly presenting delayed reaction and decreased sensitivity. （2）TPM mainly influences attention, language comprehension ability and fluency, while AEDs cause delayed reaction easily, but influence executive function mainly.

Real-time analysis of inflammatory cytokines and regulatory gene expression in tissues surrounding the hematoma after intracerebral hemorrhage

BACKGROUND： Secondary lesions can occur in tissues surrounding the hematoma following intracerebral hemorrhage, with the presence of inflammatory reactions, cytokine expression and apoptosis These have been confirmed in animal studies. Our study sought to determine whether these could be detected in human tissues surrounding the hematoma following intracerebral hemorrhage. OBJECTIVE： To investigate expression of inflammatory cytokines, Bax and Bcl-x, and identify neural cell apoptosis in tissues surrounding the hematoma, and to analyze the correlation between them and pathological damage in intracerebral hemorrhage patients. DESIGN, TIME AND SETTING： This histopathology, controlled study was performed at the Department of Neurosurgery, Sichuan People＇s Hospital, China, from January 2003 to January 2005. PARTICIPANTS： Brain tissues 1 cm from the hematoma in 30 intracerebral hemorrhage patients served as the experimental group. Brain tissues located away from the hematoma in 7 patients served as the control group. METHODS： TUNEL was used to detect neural cell apoptosis. Immunohistochemistry （labeled dextran polymer） and RT-PCR were used to measure tumor necrosis factor- α, interleukin-1 β, interleukin-6, Bax and Bcl-x protein and mRNA expression. Pathological changes in brain tissues surrounding the hematoma were observed following HE staining. MAIN OUTCOME MEASURES： Neural cell apoptosis, inflammatory cytokines, Bax and Bcl-x protein and mRNA expression, pathological changes in brain tissues surrounding the hematoma. RESULTS： Brain tissues surrounding the hematoma were mildly damaged within 6 hours, severely damaged at 24-72 hours, and significantly improved 1 week following intracerebral hemorrhage. Expression of tumor necrosis factor- α protein and mRNA, interleukin-1β and interleukin-6 mRNA was not significant in tissues surrounding the hematoma, which was identical to the control group within 6 hours after intracerebral hemorrhage. This expression was significantly higher compared with the control group from 12-72 hours, and gradually decreased after 72 hours. The number of apoptotic neural cells reached a peak between 12- 72 hours. Tumor necrosis factor-α protein and mRNA, interleukin-1β and interleukin-6 mRNA levels were positively correlated with apoptosis, Bax protein and mRNA levels （P 〈 0.01 ）. CONCLUSION： Tumor necrosis factor-α, interleukin-1β, and interleukin-6 levels are highly correlated with apoptosis. With the decrease in tumor necrosis factor-α, interleukin-1β and interleukin-6 levels, the number of apoptotic cells gradually reduced.

Study on Approach of Static Security Assessment Accounting for Electro-thermal Coupling

A static security assessment approach considering electro-thermal coupling of transmission lines is proposed in this paper. Combined with the dynamic thermal rating technology and energy forecasting, the approach can track both the electrical variables and transmission lines’ temperature varying trajectory under anticipated contingencies. Accordingly, it identifies the serious contingencies by transmission lines’ temperature violation rather than its power flow, in this case the time margin of temperature rising under each serious contingency can be provided to operators as warning information and some unnecessary security control can also be avoided. Finally, numerical simulations are carried out to testify the validity of the proposed approach.

Synergistic antitumor activity of artesunate and HDAC inhibitors through elevating heme synthesis via synergistic upregulation of ALAS1 expression

Artemisinin and its derivatives(ARTs) were reported to display heme-dependent antitumor activity. On the other hand, histone deacetylase inhibitors(HDACi) were known to be able to promote heme synthesis in erythroid cells. Nevertheless, the effect of HDACi on heme homeostasis in nonerythrocytes remains unknown. We envisioned that the combination of HDACi and artesunate(ARS)might have synergistic antitumor activity through modulating heme synthesis. In vitro studies revealed that combination of ARS and HDACi exerted synergistic tumor inhibition by inducing cell death. Moreover, this combination exhibited more effective antitumor activity than either ARS or HDACi monotherapy in xenograft models without apparent toxicity. Importantly, mechanistic studies revealed that HDACi coordinated with ARS to increase 5-aminolevulinate synthase(ALAS1) expression, and subsequent heme production, leading to enhanced cytotoxicity of ARS. Notably, knocking down ALAS1 significantly blunted the synergistic effect of ARS and HDACi on tumor inhibition, indicating a critical role of ALAS1 upregulation in mediating ARS cytotoxicity. Collectively, our study revealed the mechanism of synergistic antitumor action of ARS and HDACi. This finding indicates that modulation of heme synthesis pathway by the combination based on ARTs and other heme synthesis modulators represents a promising therapeutic approach to solid tumors.

Energy Management of Price-maker Community Energy Storage by Stochastic Dynamic Programming

In this paper,we propose an analytical stochastic dynamic programming(SDP)algorithm to address the optimal management problem of price-maker community energy storage.As a price-maker,energy storage smooths price differences,thus decreasing energy arbitrage value.However,this price-smoothing effect can result in significant external welfare changes by reduc-ing consumer costs and producer revenues,which is not negligible for the community with energy storage systems.As such,we formulate community storage management as an SDP that aims to maximize both energy arbitrage and community welfare.To incorporate market interaction into the SDP format,we propose a framework that derives partial but sufficient market information to approximate impact of storage operations on market prices.Then we present an analytical SDP algorithm that does not require state discretization.Apart from computational efficiency,another advantage of the analytical algorithm is to guide energy storage to charge/discharge by directly comparing its current marginal value with expected future marginal value.Case studies indicate community-owned energy storage that maximizes both arbitrage and welfare value gains more benefits than storage that maximizes only arbitrage.The proposed algorithm ensures optimality and largely reduces the computational complexity of the standard SDP.Index Terms-Analytical stochastic dynamic programming,energy management,energy storage,price-maker,social welfare.

Optimal Time-of-use Pricing for Renewable Energy-powered Microgrids: A Multi-agent Evolutionary Game Theory-based Approach

While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited by its high costs.In this study,we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system,that comprises a government agent,local utility company agent,and different types of consumer agents.In the proposed model,we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward induction.Two pricing strategies,namely,the TOU seasonal pricing and TOU monthly pricing,are evaluated and compared with traditional fixed pricing.The numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed pricing.Additionally,TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.

Energy Internet:Redefinition and categories

The concept of‘Energy Internet’(EI)has been widely accepted by both academic and industry experts after more than a decade of development.Since it was proposed,EI has been discussed and applied to many technical works in power and energy areas.Some specific definitions were proposed for EI by those who have applied it to respective fields of engineering,but a comprehensive and widely accepted definition of EI is still being debated.In this paper,we propose the redefinition of EI,based on a comprehensive literature review,some latest trends and driving forces in the global energy industry,as well as its development in the past decade.In addition,we summarise the EI framework and features for future applications,where EI is categorised by its scale into local‐and wide‐area applications to manifest its effectiveness in power and energy.

Multi‐energy system horizon planning:Early decarbonisation in China avoids stranded assets

An appropriate decarbonisation pathway is crucial to achieving carbon neutrality in China before 2060.This paper studies decarbonisation pathways for China's energy system between 2020 and 2060 using an open,provincial,and hourly resolved,networked model within the context of multi‐period planning with myopic investment foresight.Two representative decarbonisation pathways are compared,with particular attention to the synergies of coupling the electricity and heating sectors.An early and steady path in which emissions are strongly reduced in the first decade is more cost‐effective than following a late and rapid path.Early decarbonisation in the electricity sector avoids stranded in-vestments in fossil infrastructure and preserves the carbon budget for later emissions in the difficult‐to‐decarbonise heating sector.Retrofitting the existing coal power plants by adding carbon capture facilities is cost‐effective in both decarbonisation pathways.The hourly and non‐interrupted resolution for a full weather year reveals the balancing strategies of highly renewable,sector‐coupled systems.The significant seasonal variation of heat demand dominates long‐term storage behaviours.

Fully privacy-preserving distributed optimization in power systems based on secret sharing

With the increasing development of smart grid,multi-party cooperative computation between several entities has become a typical characteristic of modern energy systems.Traditionally,data exchange among parties is inevitable,rendering how to complete multi-party collaborative optimization without exposing any private information a critical issue.This paper proposes a fully privacy-preserving distributed optimization framework based on secure multi-party computation(SMPC)with secret sharing protocols.The framework decomposes the collaborative optimization problem into a master problem and several subproblems.The process of solving the master problem is executed in the SMPC framework via the secret sharing protocols among agents.The relationships of agents are completely equal,and there is no privileged agent or any third party.The process of solving subproblems is conducted by agents individually.Compared to the traditional distributed optimization framework,the proposed SMPC-based framework can fully preserve individual private information.Exchanged data among agents are encrypted and no private information disclosure is assured.Furthermore,the framework maintains a limited and acceptable increase in computational costs while guaranteeing opti-mality.Case studies are conducted on test systems of different scales to demonstrate the principle of secret sharing and verify the feasibility and scalability of the proposed methodology.

YTH Domain： A Family of N^6-methyladenosine (m^6A) Readers

Like protein and DNA, different types of RNA molecules undergo various modifications. Accumulating evidence suggests that these RNA modifications serve as sophisticated codes to mediate RNA behaviors and many important biological functions. N^6-methyladenosine （m^6A） is the most abundant internal RNA modification found in a variety of eukaryotic RNAs, including but not limited to mRNAs, tRNAs, rRNAs, and long non-coding RNAs （lncRNAs）. In mammalian cells, m^6A can be incorporated by a methyltransferase complex and removed by demethy- lases, which ensures that the m^6A modification is reversible and dynamic. Moreover, m^6A is recognized by the YT521-B homology （YTH） domain-containing proteins, which subsequently direct different complexes to regulate RNA signaling pathways, such as RNA metabolism, RNA splicing, RNA folding, and protein translation. Herein, we summarize the recent progresses made in understanding the molecular mechanisms underlying the m^6A recognition by YTH domaincontaining proteins, which would shed new light on m^6A-specific recognition and provide clues to the future identification of reader proteins of many other RNA modifications.

Current developments in pharmacological therapeutics for chronic constipation

Chronic constipation is a common gastrointestinal disease severely affecting the patient's quality of life. The traditional treatment of constipation is the use of laxatives. Recently, several new drugs including lubiprostone, linaclotide and prucalopride have been approved for treatment of chronic constipation. However, a significant unmet medical need still remains, particularly among those patients achieving poor results by current therapies. The 5-EF1'1 receptor modulators velusetrag and naronapride, the guanylate cy-clase C agonist plecanatide and die deal bile acid transporter inhibitor elobixibat are recognized as the most promising drugs under investigation. Herein, we give a comprehensive review on the pharmacological therapeutics for the treatment of chronic constipation, with the purpose of reflecting the drug development trends in this field. (C) 2015 Chinese Pharmaceutical Association and Institute of Materia Medica, Chinese Academy of Medical Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.orgicenses/by-ne-rid/4.0/).

Quasi-dynamic Interactions and Security Control of Integrated Electricity and Heating Systems in Normal Operations

Coupling between electricity systems and heating systems are becoming stronger,leading to more flexible and more complex interactions between these systems.The operation of integrated energy systems is greatly affected,especially when security is concerned.Steady-state analysis methods have been widely studied in recent research,which is far from enough when the slow thermal dynamics of heating networks are introduced.Therefore,an integrated quasi-dynamic model of integrated electricity and heating systems is developed.The model combines a heating network dynamic thermal model and the sequential steady-state models of electricity networks,coupling components,and heating network hydraulics.Based on this model,a simulation method is proposed and quasi-dynamic interactions between electricity systems and heating systems are quantified with the highlights of transport delay.Then the quasi-dynamic interactions were applied using security control to relieve congestion in electricity systems.Results show that both the transport delay and control strategies have significant influences on the quasi-dynamic interactions.

Active Dynamic Aggregation Model for Distributed Integrated Energy System as Virtual Power Plant

Distributed integrated multi-energy systems(DIMSs)can be regarded as virtual power plants to provide additional flexibility to the power system.This paper proposes a robust active dynamic aggregation model for the DIMSs to describe the maximum feasible region.The aggregation model includes the power constraints,energy constraints,and ramping constraints to aggregate different types of resources in the DIMSs.The proposed generator-like and storage-like model does not depend on the ancillary service market and can be directly incorporated into the economic dispatch model of the power system.A novel algorithm based on the column-and-constraint generation algorithm and convex-concave procedure is proposed to solve the two-stage robust optimization problem,which is more efficient than the KKT-based algorithms.Finally,a case study of an actual DIMS is developed to demonstrate the effectiveness of the proposed model.

A Hybrid State Estimation Approach for Integrated Heat and Electricity Networks Considering Time-scale Characteristics

State estimation(SE)usually serves as the basic function of the energy management system(EMS).In this paper,the time-scale characteristics of the integrated heat and electricity networks are studied and an SE model is established.Then,a two-stage iterative algorithm is proposed to estimate the time delay of heat power transportation in the pipeline.Meanwhile,to accommodate the measuring resolutions of the integrated network,a hybrid SE approach is developed based on the two-stage iterative algorithm.Results show that,in both steady and dynamic processes,the two-stage estimator has good accuracy and convergence.The hybrid estimator has good performance on tracking the variation of the states in the heating network,even when the available measurements are limited.

Application of Modified Progressive Hedging for Stochastic Unit Commitment in Electricity-Gas Coupled Systems

The increasing number of gas-fired units has significantly intensified the coupling between electric and gas power networks.Traditionally,nonlinearity and nonconvexity in gas flow equations,together with renewable-induced stochasticity,resulted in a computationally expensive model for unit commitment in electricity-gas coupled integrated energy systems(IES).To accelerate stochastic day-ahead scheduling,we applied and modified Progressive Hedging(PH),a heuristic approach that can be computed in parallel to yield scenario-independent unit commitment.Through early termination and enumeration techniques,the modified PH algorithm saves considerable com,putational time for certain generation cost settings or when the scale of the IES is large.Moreover,an adapted second-order cone relaxation(SOCR)is utilized to tackle the nonconvex gas flow equation.Case studies were performed on the IEEE 24.bus system/Belgium 20-node gas system and the IEEE 118-bus system/Belgium 20-node gas system.The computational efficiency when employing PH is 188 times that of commercial software,and the algorithm even outperforms Benders Decomposition.At the same time,the gap between the PH algorithm and the benchmark is less than 0.01% in both IES systems,which proves that the solutions produced by PH reach acceptable optimality in this stochastic UC problem.

Very Short-term Spatial and Temporal Wind Power Forecasting: A Deep Learning Approach

In power systems that experience high penetration of wind power generation,very short-term wind power forecast is an important prerequisite for look-ahead power dispatch.Conventional univariate wind power forecasting methods at presentonly utilize individual wind farm historical data.However,studies have shown that forecasting accuracy canbe improved by exploring both spatial and temporal correlations among adjacent wind farms.Current research on spatial-temporal wind power forecasting is based on relatively shallow time series models that,to date,have demonstrated unsatisfactory performance.In this paper,a convolution operation is used to capture the spatial and temporal correlations among multiple wind farms.A novel convolution-based spatial-temporal wind power predictor(CSTWPP)is developed.Due to CSTWPP’s high nonlinearity and deep architecture,wind power variation features and regularities included in the historical data can be more effectively extracted.Furthermore,the online training of CSTWPP enables incremental learning,which makes CSTWPP non-stationary and in conformity with real scenarios.Graphics processing units(GPU)is used to speed up the training process,validating the developed CSTWPP for real-time application.Case studies on 28 adjacent wind farms are conducted to show that the proposed model can achieve superior performance on 5-30 minutes ahead wind power forecasts.

Security Analysis of a Park-level Agricultural Energy Network Considering Agrometeorology and Energy Meteorology

China’s industrial manufacturing industry is well developed,but its agriculture is primitive.The only way to solve this problem is to improve through modern agriculture.The cross integration of new energy development and modern agriculture is becoming more and more critical.However,the research on the interaction between the meteorological disaster of facility agriculture and the power supply security of the integrated energy supply system has not formed a systematic theoretical system,which challenges the collaborative security of the facility agriculture and energy system.In this paper,energy meteorology and agrometeorology are considered and modeled,and the static security of a park-level agricultural energy network is simulated and analyzed under different weather conditions.

Combined Electric and Heat System Testbeds for Power Flow Analysis and Economic Dispatch

In combined electric and heat systems,selecting a suitable testbed for power flow analysis or economic dispatch is not easy:a large number of existing testbeds are not opensource,while others are difficult to be reused by other researchers due to the particularity of system scale,topology,and data.In this paper,we present three open-source testbeds with different scales based on practical combined electric and heat systems.To satisfy researchers"specific demands on the system topology and data,we also discuss how to modify testbeds based on existing topologies and data.Researchers can use the testbeds presented in this paper to test their innovative methods for power flow analysis and economic dispatch,and can also design their own testbeds based on the methodology in this paper,using published topologies and data.

Testbeds for Integrated Transmission and Distribution Networks: Generation Methodology and Benchmarks

For future power systems with high penetration of distributed energy resources(DER),the coordination of the transmission system(TS)and distribution system(DS)is quite essential.In this paper,multiple testbeds that consist of various sizes of TS and DS models are designed for power flow(PF)and optimal power flow(OPF)analysis of the integrated transmission and distribution(T&D)systems.Several benchmarks with characteristics for applications are proposed and their simulation results are presented in this paper.Researchers can use the testbeds designed in this paper to build their specific cases with published data,and they can also compare the results of their new approaches or algorithms with those obtained by the proposed benchmarks in this paper.