Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading fau...Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading faults is no longer appropriate.A cascading fault analysis method considering multi-energy coupling characteristics is of vital importance.In this study,an innovative analysis method for cascading faults in integrated heat and electricity systems(IHES)is proposed.It considers the degradation characteristics of transmission and energy supply com-ponents in the system to address the impact of component aging on cascading faults.Firstly,degradation models for the current carrying capacity of transmission lines,the water carrying capacity and insulation performance of thermal pipelines,as well as the performance of energy supply equipment during aging,are developed.Secondly,a simulation process for cascading faults in the IHES is proposed.It utilizes an overload-dominated development model to predict the propagation path of cascading faults while also considering network islanding,electric-heating rescheduling,and load shedding.The propagation of cascading faults is reflected in the form of fault chains.Finally,the results of cascading faults under different aging levels are analyzed through numerical examples,thereby verifying the effectiveness and rationality of the proposed model and method.展开更多
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 combi...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.展开更多
In this paper, we conduct research on the development of mechanical and electrical integration of system function principle and related technologies. Along with the rapid and continuous development of modem science an...In this paper, we conduct research on the development of mechanical and electrical integration of system function principle and related technologies. Along with the rapid and continuous development of modem science and technology, it ＇ s for the penetration and cross of different subjects great push, the more important is caused by technological revolution in the field of engineering and mechanical engineering field under the rapid development of computer technology and microelectronic technology and penetration to the mechanical and electrical integration, which is formed by the mechanical industry lead to trigger a particularly large changes in the mechanical industry management system and mode of production, product and technical structure, composition and function, thus result in industrial production from the previous mechanical electrification progressively electromechanical integration which lead the trend of the current technology.展开更多
Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable e...Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection fluctuates.The gas interchangeability may be adversely affected.To investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel metrics.Then,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen injections.The steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the H-IEGS.Then,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability metrics.Moreover,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative equations.Finally,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.展开更多
Though an accurate discretization approach for gas flow dynamics, the method of characteristics (MOC) is liable to instability for inappropriate step sizes. This letter addresses the numerical stability limitation of ...Though an accurate discretization approach for gas flow dynamics, the method of characteristics (MOC) is liable to instability for inappropriate step sizes. This letter addresses the numerical stability limitation of MOC, in the context of lEGS's optimal scheduling. Specifically, the proposed method enables flexible temporal step sizes without sacrificing accuracy, significantly reducing non-convergence due to numerical oscillations. The effectiveness of the proposed method is validated through case studies in different simulation settings.展开更多
The coupling of electricity and gas systems has been ever-augmented with the wide deployment of gas-fired generators,which facilitates the conception of the integrated electricity and gas system(IEGS).Probabilistic en...The coupling of electricity and gas systems has been ever-augmented with the wide deployment of gas-fired generators,which facilitates the conception of the integrated electricity and gas system(IEGS).Probabilistic energy flow(PEF)analysis is usually conducted to assess the operating status of the IEGS by calculating the probability distribution of state variables(e.g.,gas pressure,gas flow,voltage,and power flow).However,multiform time-variant uncertainties can simultaneously reside in the IEGS,including discrete(e.g.,the component failure or functioning)and continuous ones(e.g.,renewable energy outputs).Existing PEF analysis works cannot completely deal with time-variant multiform uncertainties featured with different mathematical characteristics.This limitation hinders the estimation of potential operating risks of the IEGS.To address this,this paper proposes a generalized framework for analyzing the probabilistic energy flow of the IEGS considering multiform uncertainties.Firstly,both time-varying random working states and variable outputs of components are represented as probabilistic models utilizing the L_(z)-transform technique.The probabilistic model is composed of some representative states depicting possible realizations of the component's performance and corresponding probabilities.On this basis,the optimal energy flow(OEF)operator is defined to aggregate probabilistic models of different components to determine probabilistic models of energy flows in the IEGS.Furthermore,multidimensional indices are constructed to comprehensively explore the probabilistic features of energy flows and the impact of probabilistic energy flows on the system performance.In this paper,the system performance mainly refers to the energy-serving capability of the IEGS.Specifically,probabilistic distribution characteristics of energy flows are explicitly displayed by relevant expectations,standard deviations as well as skewnesses.Indices such as the nodal expected gas and electricity not supplied are adopted to evaluate the influence of the probabilistic energy flow on the system performance.Numerical studies reveal that energy flows through different pipelines or power lines present diversified statistical characteristics,which indicates that they are influenced by multiform uncertainties to different extents.展开更多
We experimentally demonstrate an In P-based hybrid integration of a single-mode DFB laser emitting at around 1310 nm and a tunneling diode. The evident negative differential resistance regions are obtained in both ele...We experimentally demonstrate an In P-based hybrid integration of a single-mode DFB laser emitting at around 1310 nm and a tunneling diode. The evident negative differential resistance regions are obtained in both electrical and optical output characteristics. The electrical and optical bistabilities controlled by the voltage through the tunneling diode are also measured. When the voltage changes between 1.46 V and 1.66 V, a 200-mV-wide hysteresis loop and an optical power ON/OFF ratio of 17 dB are obtained. A side-mode suppression ratio of the integrated device in the ON state is up to 43 dB. The tunneling diode can switch on/off the laser within a very small voltage range compared with that directly controlled by a voltage source.展开更多
Observability analysis(OA)is vital to obtaining the available input measurements of state estimation(SE)in an integrated electricity and heating system(IEHS).Considering the thermal quasi-dynamics in pipelines,the mea...Observability analysis(OA)is vital to obtaining the available input measurements of state estimation(SE)in an integrated electricity and heating system(IEHS).Considering the thermal quasi-dynamics in pipelines,the measurement equations in heating systems are dependent on the estimated results,leading to an interdependency between OA and SE.Conventional OA methods require measurement equations be known exactly before SE is performed,and they are not applicable to IEHSs.To bridge this gap,a scenario-based OA scheme for IEHSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this interdependency.As its core procedure,the observable state identification and observability restoration are formulated in terms of integer linear programming.Numerical tests are conducted to demonstrate the validity and superiority of the proposed formulation.展开更多
The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch ...The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.展开更多
With the implementation of the integrated electricity and gas market(IEGM),the smart energy hubs(SEHs)tend to participate in the market clearing for the optimization of the energy purchase portfolio.Meanwhile,the rene...With the implementation of the integrated electricity and gas market(IEGM),the smart energy hubs(SEHs)tend to participate in the market clearing for the optimization of the energy purchase portfolio.Meanwhile,the renewable energy is mushrooming at different scales of energy systems,which can introduce utility-level and distribution-level uncertainties to the operation of the IEGM and SEHs,respectively.Considering the impacts of divergent uncertainties,there exist complicated interactions between the IEGM clearing and the robust bidding of SEHs.The lack of consideration of such interactions may lead to inaccurate modeling of the IEGM clearing and cause potential market inefficiency.To handle this,a bi-level robust clearing framework of the IEGM considering the robust bidding of SEHs is proposed,which simultaneously considers the impacts of utility-level and distribution-level uncertainties.The proposed framework is partitioned into two levels.The upper level is the robust clearing mechanism of the IEGM.At this level,the uncertainty locational marginal electricity and gas prices are derived considering the utility-level uncertainties and the uncertainty-based bidding of SEHs.Given the price signals deduced in the upper level,the lower-level robust bidding of the SEH seeks the optimal bidding strategies while hedging against distribution-level uncertainties.To address the proposed framework,an effective algorithm combining column-and-constraint generation(C&CG)algorithm with the best-response decomposition(BRD)algorithm is formulated.The devised algorithm can efficiently solve the individual robust optimization model and coordinate the interaction of two levels.Numerical experiments are carried out to verify the effectiveness of the proposed framework.Moreover,the impacts of uncertainties on the market clearing results along with the optimal biddings of SEHs are further demonstrated within the proposed framework.展开更多
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 affecte...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.展开更多
The sharp increase in the total installed capacity of natural gas generators has intensified the dynamic interaction between the electricity and natural gas systems,which could induce cascading failure propagation acr...The sharp increase in the total installed capacity of natural gas generators has intensified the dynamic interaction between the electricity and natural gas systems,which could induce cascading failure propagation across the two systems that deserves intensive research.Considering the distinct time response behaviors of the two systems,this paper discusses an integrated simulation approach to simulate the cascading failure propagation process of integrated electricity and natural gas systems(IEGSs).On one hand,considering instantaneous re-distribution of power flows after the occurrence of disturbance or failure,the steady-state AC power flow model is employed.On the other hand,gas transmission dynamics are represented by dynamic model to capture the details of its transition process.The interactions between the two systems,intensified by energy coupling components(such as gas-fired generator and electricity-driven gas compressor)as well as the switching among the operation modes of compressors during the cascading failure propagation process,are studied.An IEGS composed of the IEEE 30-bus electricity system and a 14-node 15-pipeline gas system is established to illustrate the effectiveness of the proposed simulation approach,in which two energy sub-systems are coupled by compressor and gas-fired generator.Numerical results clearly demonstrate that heterogeneous interactions between electricity and gas systems would trigger the cascading failure propagation between the two coupling systems.展开更多
As the proportion of wind power generation increases in power systems,it is necessary to develop new ways for wind power accommodation and improve the existing power dispatch model.The power-to-gas technology,which of...As the proportion of wind power generation increases in power systems,it is necessary to develop new ways for wind power accommodation and improve the existing power dispatch model.The power-to-gas technology,which offers a new approach to accommodate surplus wind power,is an excellent way to solve the former.Hence,this paper proposes to involve power-to-gas technology in the integrated electricity and natural gas systems(IEGSs).To solve the latter,on one hand,a new indicator,the scale factor of wind power integration,is introduced into the wind power stochastic model to better describe the uncertainty of grid-connected wind power;on the other hand,for quantizing and minimizing the impact of the uncertainties of wind power and system loads on system security,security risk constraints are established for the IEGS by the conditional value-at-risk method.By considering these two aspects,an MILP formulation of a security-risk based stochastic dynamic economic dispatch model for an IEGS is established,and GUROBI obtained from GAMS is used for the solution.Case studies are conducted on an IEGS consisting of a modified IEEE 39-bus system and the Belgium 20-node natural gas system to examine the effectiveness of the proposed dispatch model.展开更多
Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)tech...Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.展开更多
With the growing interdependence between the electricity system and the natural gas system,the operation uncertainties in either subsystem,such as wind fluctuations or component failures,could have a magnified impact ...With the growing interdependence between the electricity system and the natural gas system,the operation uncertainties in either subsystem,such as wind fluctuations or component failures,could have a magnified impact on the reliability of the whole system due to energy interactions.A joint reserve scheduling model considering the cross-sectorial impacts of operation uncertainties is essential but still insufficient to guarantee the reliable operation of the integrated electricity and natural gas system(IEGS).Therefore,this paper proposes a day-ahead security-constrained unit commitment(SCUC)model for the IEGS to schedule the operation and reserve simultaneously considering reliability requirements.Firstly,the multi-state models for generating units and gas wells are established.Based on the multi-state models,the expected unserved energy cost(EUEC)and the expected wind curtailment cost(EWC)criteria are proposed based on probabilistic methods considering wind fluctuation and random failures of components in IEGS.Furthermore,the EUEC and EWC criteria are incorporated into the day-ahead SCUC model,which is nonconvex and mathematically reformulated into a solvable mixed-integer second-order cone programming(MISOCP)problem.The proposed model is validated using an IEEE 30-bus system and Belgium 20-node natural gas system.Numerical results demonstrate that the proposed model can effectively schedule the energy reserve to guarantee the reliable operation of the IEGS considering the multiple uncertainties in different subsystems and the cross-sectorial failure propagation.展开更多
A new singularity extraction technique is presented to calculate accurately the singular integrals in Time Domain Electric Field Integral Equation (TDEFIE).In singularity extraction pro- cedure,through the aid of the ...A new singularity extraction technique is presented to calculate accurately the singular integrals in Time Domain Electric Field Integral Equation (TDEFIE).In singularity extraction pro- cedure,through the aid of the first order Taylor series of time base function including time-retardation,the singularity of the integrand can be removed.The surface current density and backscattered far-field response of a conducting cube illuminated by a Gaussian plane wave is com- puted using the presented technique.Comparisons are made with the results obtained by the Inverse Discrete Fourier Transform (IDFT) of the frequency domain and the results obtained by using Ve- chinski's time averaging technique,which demonstrate that the presented method with this new time domain singularity extraction technique to solve TDEFIE is very accurate and stable.展开更多
In this paper, we summarize some recent activities in the field of metamaterial research at the National University of Singapore (NUS). Integral equations are applied for electromagnetic modelling of supernatural mate...In this paper, we summarize some recent activities in the field of metamaterial research at the National University of Singapore (NUS). Integral equations are applied for electromagnetic modelling of supernatural materials. Some special charac- teristics of the metamaterials are shown. Moreover, quasi-static Lorentz theory and numerical method (i.e., the method of moments for solving the electric field integral equation) and the transmission line theory are both presented to obtain the effective consti- tutive relations of metamaterials, respectively. Finally, feasibility of fabricating metamaterials based on analysis of equivalent transmission line model in the microwave spectrum and even higher is also shown and correspondingly some broad-bandwidth and low-loss metamaterial structures are designed and synthesized.展开更多
Recently, the heat and electricity integrated energy system (HE-IES) has become a hot topic in both industry and academia. In the HE- IES, the potential flexibility of the buildings' thermal loads can be exploited...Recently, the heat and electricity integrated energy system (HE-IES) has become a hot topic in both industry and academia. In the HE- IES, the potential flexibility of the buildings' thermal loads can be exploited to relax the heat power balance constraints and consequently allow a more flexible operation of the combined heat and power units. In this paper, model-driven and data-driven techniques are combined to quantify the demand flexibility of the buildings' thermal loads in a non-instructive way. First, the explicit analytical equivalent thermal parameter (ETP) model of the aggregated buildings is developed. The heat transfer coefficient (k) and thermal inertia coefficient (C) of the ETP model are designated to measure the potential demand flexibility. Second, the Particle Swarm Optimization optimized Radial Basis Function neural network (PSO-RBF) is used to identify the relationship between the values of k and C and the meteorological factors. To obtain the training data, an innovative two-stage regression method based on the adaptive temporal resolution is proposed to extract k and C values from the historical thermal load data. Finally, a flexible thermal load model is built based on the predictions of the meteorological factors, which can be conveniently incorporated into the online dispatch of the HE-IES. A comprehensive simulation environment is designed to verify the accuracy and availability of the proposed technique.展开更多
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...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.展开更多
The electricity and steam integrated energy systems,which can capture waste heat and improve the overall energy efficiency,have been widely utilised in industrial parks.However,intensive and frequent changes in demand...The electricity and steam integrated energy systems,which can capture waste heat and improve the overall energy efficiency,have been widely utilised in industrial parks.However,intensive and frequent changes in demands would lead to model parameters with strong time-varying characteristics.This paper proposes a hybrid physics and data-driven framework for online joint state and parameter estimation of steam and electricity integrated energy system.Based on the physical non-linear state space models for the electricity network(EN)and steam heating network(SHN),relevance vector machine is developed to learn parameters'dynamic characteristics with respect to model states,which is embedded with physical models.Then,the online joint state and parameter estimation based on unscented Kalman filter is proposed,which would be learnt recursively to capture the spatiotemporal transient characteristics between electricity and SHNs.The IEEE 39-bus EN and the 29-nodes SHN are employed to verify the effectiveness of the proposed method.The experimental results validate that the pro-posed method can provide a higher estimation accuracy than the state-of-the-art approaches.展开更多
基金supported by Shanghai Rising-Star Program(No.22QA1403900)the National Natural Science Foundation of China(No.71804106)the Noncarbon Energy Conversion and Utilization Institute under the Shanghai Class IV Peak Disciplinary Development Program.
文摘Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading faults is no longer appropriate.A cascading fault analysis method considering multi-energy coupling characteristics is of vital importance.In this study,an innovative analysis method for cascading faults in integrated heat and electricity systems(IHES)is proposed.It considers the degradation characteristics of transmission and energy supply com-ponents in the system to address the impact of component aging on cascading faults.Firstly,degradation models for the current carrying capacity of transmission lines,the water carrying capacity and insulation performance of thermal pipelines,as well as the performance of energy supply equipment during aging,are developed.Secondly,a simulation process for cascading faults in the IHES is proposed.It utilizes an overload-dominated development model to predict the propagation path of cascading faults while also considering network islanding,electric-heating rescheduling,and load shedding.The propagation of cascading faults is reflected in the form of fault chains.Finally,the results of cascading faults under different aging levels are analyzed through numerical examples,thereby verifying the effectiveness and rationality of the proposed model and method.
基金This work was supported by the Science and Technology Program of State Grid Corporation of China(522300190008).
文摘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.
文摘In this paper, we conduct research on the development of mechanical and electrical integration of system function principle and related technologies. Along with the rapid and continuous development of modem science and technology, it ＇ s for the penetration and cross of different subjects great push, the more important is caused by technological revolution in the field of engineering and mechanical engineering field under the rapid development of computer technology and microelectronic technology and penetration to the mechanical and electrical integration, which is formed by the mechanical industry lead to trigger a particularly large changes in the mechanical industry management system and mode of production, product and technical structure, composition and function, thus result in industrial production from the previous mechanical electrification progressively electromechanical integration which lead the trend of the current technology.
基金supported in part by the Science and Technology Development Fund,Macao SAR(File no.SKL-IOTSC(UM)-2021-2023,File no.0003/2020/AKP,and File no.0117/2022/A3)the Natural Science Foundation of Jiangsu Province,China(Operational reliability evaluation of multi-source and heterogeneous urban multi-energy systems,BK20220261).
文摘Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection fluctuates.The gas interchangeability may be adversely affected.To investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel metrics.Then,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen injections.The steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the H-IEGS.Then,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability metrics.Moreover,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative equations.Finally,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.
文摘Though an accurate discretization approach for gas flow dynamics, the method of characteristics (MOC) is liable to instability for inappropriate step sizes. This letter addresses the numerical stability limitation of MOC, in the context of lEGS's optimal scheduling. Specifically, the proposed method enables flexible temporal step sizes without sacrificing accuracy, significantly reducing non-convergence due to numerical oscillations. The effectiveness of the proposed method is validated through case studies in different simulation settings.
基金supported by the Science and Technology Project of State Grid Corporation of China(5108-202218280A-2-448-XG).
文摘The coupling of electricity and gas systems has been ever-augmented with the wide deployment of gas-fired generators,which facilitates the conception of the integrated electricity and gas system(IEGS).Probabilistic energy flow(PEF)analysis is usually conducted to assess the operating status of the IEGS by calculating the probability distribution of state variables(e.g.,gas pressure,gas flow,voltage,and power flow).However,multiform time-variant uncertainties can simultaneously reside in the IEGS,including discrete(e.g.,the component failure or functioning)and continuous ones(e.g.,renewable energy outputs).Existing PEF analysis works cannot completely deal with time-variant multiform uncertainties featured with different mathematical characteristics.This limitation hinders the estimation of potential operating risks of the IEGS.To address this,this paper proposes a generalized framework for analyzing the probabilistic energy flow of the IEGS considering multiform uncertainties.Firstly,both time-varying random working states and variable outputs of components are represented as probabilistic models utilizing the L_(z)-transform technique.The probabilistic model is composed of some representative states depicting possible realizations of the component's performance and corresponding probabilities.On this basis,the optimal energy flow(OEF)operator is defined to aggregate probabilistic models of different components to determine probabilistic models of energy flows in the IEGS.Furthermore,multidimensional indices are constructed to comprehensively explore the probabilistic features of energy flows and the impact of probabilistic energy flows on the system performance.In this paper,the system performance mainly refers to the energy-serving capability of the IEGS.Specifically,probabilistic distribution characteristics of energy flows are explicitly displayed by relevant expectations,standard deviations as well as skewnesses.Indices such as the nodal expected gas and electricity not supplied are adopted to evaluate the influence of the probabilistic energy flow on the system performance.Numerical studies reveal that energy flows through different pipelines or power lines present diversified statistical characteristics,which indicates that they are influenced by multiform uncertainties to different extents.
基金Supported by the National Key Research and Development Program of China under Grant No 2017YFB0405301the National Natural Science Foundation of China under Grant Nos 61604144 and 61504137
文摘We experimentally demonstrate an In P-based hybrid integration of a single-mode DFB laser emitting at around 1310 nm and a tunneling diode. The evident negative differential resistance regions are obtained in both electrical and optical output characteristics. The electrical and optical bistabilities controlled by the voltage through the tunneling diode are also measured. When the voltage changes between 1.46 V and 1.66 V, a 200-mV-wide hysteresis loop and an optical power ON/OFF ratio of 17 dB are obtained. A side-mode suppression ratio of the integrated device in the ON state is up to 43 dB. The tunneling diode can switch on/off the laser within a very small voltage range compared with that directly controlled by a voltage source.
基金supported by National Natural Science Foundation of China(52177086)Fundamental Research Funds for the Central Universities(2023ZYGXZR063).
文摘Observability analysis(OA)is vital to obtaining the available input measurements of state estimation(SE)in an integrated electricity and heating system(IEHS).Considering the thermal quasi-dynamics in pipelines,the measurement equations in heating systems are dependent on the estimated results,leading to an interdependency between OA and SE.Conventional OA methods require measurement equations be known exactly before SE is performed,and they are not applicable to IEHSs.To bridge this gap,a scenario-based OA scheme for IEHSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this interdependency.As its core procedure,the observable state identification and observability restoration are formulated in terms of integer linear programming.Numerical tests are conducted to demonstrate the validity and superiority of the proposed formulation.
基金supported by State Key Laboratory of HVDC under Grant SKLHVDC-2021-KF-09.
文摘The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.
基金supported by the Science and Technology Project of State Grid Corporation(No.5108-202218280A-2-449-XG)。
文摘With the implementation of the integrated electricity and gas market(IEGM),the smart energy hubs(SEHs)tend to participate in the market clearing for the optimization of the energy purchase portfolio.Meanwhile,the renewable energy is mushrooming at different scales of energy systems,which can introduce utility-level and distribution-level uncertainties to the operation of the IEGM and SEHs,respectively.Considering the impacts of divergent uncertainties,there exist complicated interactions between the IEGM clearing and the robust bidding of SEHs.The lack of consideration of such interactions may lead to inaccurate modeling of the IEGM clearing and cause potential market inefficiency.To handle this,a bi-level robust clearing framework of the IEGM considering the robust bidding of SEHs is proposed,which simultaneously considers the impacts of utility-level and distribution-level uncertainties.The proposed framework is partitioned into two levels.The upper level is the robust clearing mechanism of the IEGM.At this level,the uncertainty locational marginal electricity and gas prices are derived considering the utility-level uncertainties and the uncertainty-based bidding of SEHs.Given the price signals deduced in the upper level,the lower-level robust bidding of the SEH seeks the optimal bidding strategies while hedging against distribution-level uncertainties.To address the proposed framework,an effective algorithm combining column-and-constraint generation(C&CG)algorithm with the best-response decomposition(BRD)algorithm is formulated.The devised algorithm can efficiently solve the individual robust optimization model and coordinate the interaction of two levels.Numerical experiments are carried out to verify the effectiveness of the proposed framework.Moreover,the impacts of uncertainties on the market clearing results along with the optimal biddings of SEHs are further demonstrated within the proposed framework.
基金This work was supported in part by the National Natural Science Foundation of China(NSFC)(51537006)European Union’s Horizon 2020 research and innovation programme(774309,MAGNATUDE),WEFO FLEXIS project.
文摘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.
基金supported by the National Natural Science Foundation of China(No.51777182)the National Natural Science Foundation(No.CMMI1635339)
文摘The sharp increase in the total installed capacity of natural gas generators has intensified the dynamic interaction between the electricity and natural gas systems,which could induce cascading failure propagation across the two systems that deserves intensive research.Considering the distinct time response behaviors of the two systems,this paper discusses an integrated simulation approach to simulate the cascading failure propagation process of integrated electricity and natural gas systems(IEGSs).On one hand,considering instantaneous re-distribution of power flows after the occurrence of disturbance or failure,the steady-state AC power flow model is employed.On the other hand,gas transmission dynamics are represented by dynamic model to capture the details of its transition process.The interactions between the two systems,intensified by energy coupling components(such as gas-fired generator and electricity-driven gas compressor)as well as the switching among the operation modes of compressors during the cascading failure propagation process,are studied.An IEGS composed of the IEEE 30-bus electricity system and a 14-node 15-pipeline gas system is established to illustrate the effectiveness of the proposed simulation approach,in which two energy sub-systems are coupled by compressor and gas-fired generator.Numerical results clearly demonstrate that heterogeneous interactions between electricity and gas systems would trigger the cascading failure propagation between the two coupling systems.
基金This work was supported by National Natural Science Foundation of China(No.51777077)Natural Science Foundation of Guangdong Province(2017A030313304).
文摘As the proportion of wind power generation increases in power systems,it is necessary to develop new ways for wind power accommodation and improve the existing power dispatch model.The power-to-gas technology,which offers a new approach to accommodate surplus wind power,is an excellent way to solve the former.Hence,this paper proposes to involve power-to-gas technology in the integrated electricity and natural gas systems(IEGSs).To solve the latter,on one hand,a new indicator,the scale factor of wind power integration,is introduced into the wind power stochastic model to better describe the uncertainty of grid-connected wind power;on the other hand,for quantizing and minimizing the impact of the uncertainties of wind power and system loads on system security,security risk constraints are established for the IEGS by the conditional value-at-risk method.By considering these two aspects,an MILP formulation of a security-risk based stochastic dynamic economic dispatch model for an IEGS is established,and GUROBI obtained from GAMS is used for the solution.Case studies are conducted on an IEGS consisting of a modified IEEE 39-bus system and the Belgium 20-node natural gas system to examine the effectiveness of the proposed dispatch model.
文摘Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.
基金supported in part by Science&Technology Project of State Grid Corporation of China(No.5100-202199285A-0-0-00)in part by the National Natural Science Foundation China and Joint Programming Initiative Urban Europe Call(NSFC-JPI UE)(No.71961137004).
文摘With the growing interdependence between the electricity system and the natural gas system,the operation uncertainties in either subsystem,such as wind fluctuations or component failures,could have a magnified impact on the reliability of the whole system due to energy interactions.A joint reserve scheduling model considering the cross-sectorial impacts of operation uncertainties is essential but still insufficient to guarantee the reliable operation of the integrated electricity and natural gas system(IEGS).Therefore,this paper proposes a day-ahead security-constrained unit commitment(SCUC)model for the IEGS to schedule the operation and reserve simultaneously considering reliability requirements.Firstly,the multi-state models for generating units and gas wells are established.Based on the multi-state models,the expected unserved energy cost(EUEC)and the expected wind curtailment cost(EWC)criteria are proposed based on probabilistic methods considering wind fluctuation and random failures of components in IEGS.Furthermore,the EUEC and EWC criteria are incorporated into the day-ahead SCUC model,which is nonconvex and mathematically reformulated into a solvable mixed-integer second-order cone programming(MISOCP)problem.The proposed model is validated using an IEEE 30-bus system and Belgium 20-node natural gas system.Numerical results demonstrate that the proposed model can effectively schedule the energy reserve to guarantee the reliable operation of the IEGS considering the multiple uncertainties in different subsystems and the cross-sectorial failure propagation.
文摘A new singularity extraction technique is presented to calculate accurately the singular integrals in Time Domain Electric Field Integral Equation (TDEFIE).In singularity extraction pro- cedure,through the aid of the first order Taylor series of time base function including time-retardation,the singularity of the integrand can be removed.The surface current density and backscattered far-field response of a conducting cube illuminated by a Gaussian plane wave is com- puted using the presented technique.Comparisons are made with the results obtained by the Inverse Discrete Fourier Transform (IDFT) of the frequency domain and the results obtained by using Ve- chinski's time averaging technique,which demonstrate that the presented method with this new time domain singularity extraction technique to solve TDEFIE is very accurate and stable.
文摘In this paper, we summarize some recent activities in the field of metamaterial research at the National University of Singapore (NUS). Integral equations are applied for electromagnetic modelling of supernatural materials. Some special charac- teristics of the metamaterials are shown. Moreover, quasi-static Lorentz theory and numerical method (i.e., the method of moments for solving the electric field integral equation) and the transmission line theory are both presented to obtain the effective consti- tutive relations of metamaterials, respectively. Finally, feasibility of fabricating metamaterials based on analysis of equivalent transmission line model in the microwave spectrum and even higher is also shown and correspondingly some broad-bandwidth and low-loss metamaterial structures are designed and synthesized.
基金supported by the National Natural Science Foundation of China(52107072)International Cooperation and Exchange of NSFC(51861145406).
文摘Recently, the heat and electricity integrated energy system (HE-IES) has become a hot topic in both industry and academia. In the HE- IES, the potential flexibility of the buildings' thermal loads can be exploited to relax the heat power balance constraints and consequently allow a more flexible operation of the combined heat and power units. In this paper, model-driven and data-driven techniques are combined to quantify the demand flexibility of the buildings' thermal loads in a non-instructive way. First, the explicit analytical equivalent thermal parameter (ETP) model of the aggregated buildings is developed. The heat transfer coefficient (k) and thermal inertia coefficient (C) of the ETP model are designated to measure the potential demand flexibility. Second, the Particle Swarm Optimization optimized Radial Basis Function neural network (PSO-RBF) is used to identify the relationship between the values of k and C and the meteorological factors. To obtain the training data, an innovative two-stage regression method based on the adaptive temporal resolution is proposed to extract k and C values from the historical thermal load data. Finally, a flexible thermal load model is built based on the predictions of the meteorological factors, which can be conveniently incorporated into the online dispatch of the HE-IES. A comprehensive simulation environment is designed to verify the accuracy and availability of the proposed technique.
基金supported by the National Natural Science Foundation of China(NSFC)(No.51537006)the China Postdoctoral Science Foundation(No.2019M650675)
文摘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.
基金National Natural Sciences Foundation of China,Grant/Award Numbers:62125302,62203087Sci-Tech Talent Innovation Support Program of Dalian,Grant/Award Number:2022RG03+1 种基金Liaoning Revitalization Talents Program,Grant/Award Number:XLYC2002087Young Elite Scientist Sponsorship Program by CAST,Grant/Award Number:YESS20220018。
文摘The electricity and steam integrated energy systems,which can capture waste heat and improve the overall energy efficiency,have been widely utilised in industrial parks.However,intensive and frequent changes in demands would lead to model parameters with strong time-varying characteristics.This paper proposes a hybrid physics and data-driven framework for online joint state and parameter estimation of steam and electricity integrated energy system.Based on the physical non-linear state space models for the electricity network(EN)and steam heating network(SHN),relevance vector machine is developed to learn parameters'dynamic characteristics with respect to model states,which is embedded with physical models.Then,the online joint state and parameter estimation based on unscented Kalman filter is proposed,which would be learnt recursively to capture the spatiotemporal transient characteristics between electricity and SHNs.The IEEE 39-bus EN and the 29-nodes SHN are employed to verify the effectiveness of the proposed method.The experimental results validate that the pro-posed method can provide a higher estimation accuracy than the state-of-the-art approaches.
