Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.

Research on the cooperative train control method in the metro system for energy saving

Purpose–To address the problem that the current train operation mode that train selects one of several offline pre-generated control schemes before the departure and operates following the scheme after the departure,energy-saving performance of the whole metro system cannot be guaranteed.Design/methodology/approach–A cooperative train control framework is formulated to regulate a novel train operation mode.The classic train four-phase control strategy is improved for generating specific energy-efficient control schemes for each train.An improved brute force(BF)algorithm with a two-layer searching idea is designed to solve the optimisation model of energy-efficient train control schemes.Findings–Case studies on the actual metro line in Guangzhou,China verify the effectiveness of the proposed train control methods compared with four-phase control strategy under different kinds of train operation scenarios and calculation parameters.The verification on the computation efficiency as well as accuracy of the proposed algorithm indicates that it meets the requirement of online optimisation.Originality/value–Most existing studies optimised energy-efficient train timetable or train control strategies through an offline process,which has a defect in coping with the disturbance or delays effectively and promptly during real-time train operation.This paper studies an online optimisation of cooperative train control based on the rolling optimisation idea,where energy-efficient train operation can be realised once train running time is determined,thus mitigating the impact of unpredictable operation situations on the energy-saving performance of trains.

Energy model based sensorless estimation method for operational temperature of braking resistor onboard metro vehicles

Purpose–This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking resistor(BR)onboard the vehicle,which overcomes the vulnerability of having conventional temperature sensor.Design/methodology/approach–In this study,the energy model based sensorless estimation method is developed.By analyzing the structure and the convection dissipation process of the BR onboard the vehicle,the energy-based operational temperature model of the BR and its cooling domain is established.By adopting Newton’s law of cooling and the law of conservation of energy,the energy and temperature dynamic of the BR can be stated.To minimize the use of all kinds of sensors(including both thermal and electrical),a novel regenerative braking power calculation method is proposed,which involves only the voltage of DC traction network and the duty cycle of the chopping circuit;both of them are available for the traction control unit(TCU)of the vehicle.By utilizing a real-time iterative calculation and updating the parameter of the energy model,the operational temperature of the BR can be obtained and monitored in a sensorless manner.Findings–In this study,a sensorless estimation/monitoring method of the operational temperature of BR is proposed.The results show that it is possible to utilize the existing electrical sensors that is mandatory for the traction unit’s operation to estimate the operational temperature of BR,instead of adding dedicated thermal sensors.The results also validate the effectiveness of the proposal is acceptable for the engineering practical.Originality/value–The proposal of this study provides novel concepts for the sensorless operational temperature monitoring of BR onboard rolling stocks.The proposed method only involves quasi-global electrical variable and the internal control signal within the TCU.

HYBRID WAVELET PACKET-TEAGER ENERGY OPERATOR ANALYSIS AND ITS APPLICATION FOR GEARBOX FAULT DIAGNOSIS

把包基于小浪分解(WPD ) 算法和 Teager 精力操作员(TEO ) ，新奇齿轮框差错察觉和诊断方法被建议。在 WPD 和 TEO 调整的原则分别地被介绍以后，它的过程是 expatiated。preprocessed 信号与立方的花键功能被插入内推，然后在选择基础小浪上膨胀了。基于最小的熵标准组织它信号的小浪包部件，插入内推的信号能与将近不同的差错频率内容被分解成它的主导的部件。提取每个主导的部件的解调信息， TEO 被使用。建议方法的性能在从在一辆重卡车上装的齿轮框收集的颤动信号上借助于几测试被估计。混合 WPD-TEO 方法为检测并且诊断局部性的齿轮盒子差错有效、柔韧，这被证明。

Optimal scheduling of a township integrated-energy system using the adjustable heat-electricity ratio model

With the expansion and implementation of rural revitalization strategies,there is a constant need for new energy sources for the construction of new townships.Consequently,integrated energy systems with the interconnection and interaction of multiple energy sources are developing rapidly.Biomass energy,a renewable green energy source with low pollution and wide distribution,has significant application potential in integrated energy systems.Considering the application of biomass energy in townships,this study established an integrated biomass energy system and proposed a model to optimize its operation.Lowest economic cost and highest clean energy utilization rate were considered as the objective functions.In addition,a plan was suggested to adjust the heat-electricity ratio based on the characteristics of the combined heat and power of the biomass.Finally,a simulation analysis conducted for a town in China was discussed,demonstrating that the construction of a township integrated-energy system and the use of biomass can significantly reduce operating costs and improve the energy utilization rate.Moreover,by adjusting the heat-electricity ratio,the economic cost was further reduced by 6.70%,whereas the clean energy utilization rate was increased by 5.14%.

NEW DEMODULATION TECHNOLOGY OF OPTIMIZING ENERGY OPERATOR AND APPLICATION TO GEAR FAULT DIAGNOSIS

Although many methods have been applied to diagnose the gear fault currently, the sensitivity of them is not very good. In order to make the diagnosis methods have more excellent integrated ability in such aspects as precision, sensitivity, reliability and compact algorithm, and so on, and enlightened by the energy operator separation algorithm (EOSA), a new demodulation method which is optimizing energy operator separation algorithm (OEOSA) is presented. In the algorithm, the non-linear differential operator is utilized to its differential equation:Choosing the unit impulse response length of filter and fixing the weighting coefficient for inportant points. The method has been applied in diagnosing tooth broden and fatiguing'crack of gear faults successfully. It provides demodulation analysis of machine signal with a new approach.

Solving Energy Levels for SSH Hamiltonian Describing Peierls Phase Transition by Virtue of Invariant Eigen-operator Method

<Abstract>We show that the recently proposed invariant eigen-operator (lEO) method can be successfully applied to solving energy levels for SSH Hamiltonian describing Peierls phase transition.The electronic energy band of compound lattice is also studied by IEO method.

Time and Energy Operators in Quantum Mechanics

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Deriving Energy-Level Gap of a System in Presence of a Kerr-like Medium by Virtue of Invariant Eigen-operator Method

<正> In this paper,we find the invariant eigen-operators(IEOs)and the energy-level gap of a system with atwo-level atom interacting with single mode cavity field through multi-photon transition in the presence of a Kerr-likemedium.From this work,one can see that the IEO method in many cases is simpler and easier on obtaining theenergy-level gap formula than the usual way.

Speech Endpoint Detection in Noisy Environments Using EMD and Teager Energy Operator

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

Energy Level of Three-Mode Harmonic Oscillator for Coordinate Operators Satisfying Cyclic Commutative Relations Obtained by IEO Method

Eigenvalue-solution to those Hamiltonians involving non-commutative coordinates is not easily obtained.In this paper we apply the invariant eigen-operator(IEO)method to solving the energy spectrum of the three-modeharmonic oscillator in non-commutative space with the coordinate operators satisfying cyclic commutative relations,[X_1,X_2]=[X_2,X_3]=[X_3,X_1]=iθ,and this method seems effective and concise.

Pseudo-invariant Eigen-operator for Deriving Energy-Level Gap for Jaynes-Cummings Model

我们通过分析标准 Jaynes-Cummings 模型扩大不变的 eigen 操作员的概念到 pseudo-invarianteigen-operator 大小写。我们以这个模型的超级对称的发电机发现 thepseudo 不变的 eigen 操作员，哪个到为 Jaynes-Cummings Hamiltonian 的精力级的差距的 diretlyleads。

Invariant operator theory for the single-photon energy in time-varying media

After the birth of quantum mechanics, the notion in physics that the frequency of light is the only factor that determines the energy of a single photon has played a fundamental role. However, under the assumption that the theory of Lewis-Riesenfeld invariants is applicable in quantum optics, it is shown in the present work that this widely accepted notion is valid only for light described by a time-independent Hamiltonian, i.e., for light in media satisfying the conditions, (t) = (0), μ(t) = μ(0), and σ(t) = 0 simultaneously. The use of the Lewis-Riesenfeld invariant operator method in quantum optics leads to a marvelous result: the energy of a single photon propagating through time-varying linear media exhibits nontrivial time dependence without a change of frequency.

Deriving Energy-Gap of Some Nonlinear Hamiltonians by Invariant Eigen-operator Method

By virtue of the invariant eigen-operator method we search for the invariant eigen-operators for someHamiltonians describing nonlinear processes in particle physics.In this way the energy-gap of the Hamiltonians can benaturally obtained.The characteristic polynomial theory has been fully employed in our derivation.

基于Teager-Kaiser能量算子Rife-Vincent窗频谱校正的电压闪变测量

分析了Teager-Kaiser能量算子的构成和Rife-Vincent窗的旁瓣特性,通过Teager-Kaiser算子快速提取电压闪变包络,将包络参数进行Rife-Vincent窗改进FFT谱分析与校正,简化IEC推荐的闪变测量过程,提出并建立了基于Teager-Kaiser能量算子Rife-Vincent窗频谱校正的电压闪变测量算法。仿真试验结果表明,本文提出的算法能有效克服单一频率调幅波频率变化、多频率成分调幅波、电网基波频率波动、谐波与间谐波以及白噪声对检测结果的影响,与传统电压闪变检测方法相比,设计实现简单、计算量小,测量结果精确、稳定,可用于电压闪变参数的在线监测。

A Stochastic Programming Strategy in Microgrid Cyber Physical Energy System for Energy Optimal Operation

This paper focuses on the energy optimal operation problem of microgrids(MGs) under stochastic environment.The deterministic method of MGs operation is often uneconomical because it fails to consider the high randomness of unconventional energy resources.Therefore,it is necessary to develop a novel operation approach combining the uncertainty in the physical world with modeling strategy in the cyber system.This paper proposes an energy scheduling optimization strategy based on stochastic programming model by considering the uncertainty in MGs.The goal is to minimize the expected operation cost of MGs.The uncertainties are modeled based on autoregressive moving average(ARMA) model to expose the effects of physical world on cyber world.Through the comparison of the simulation results with deterministic method,it is shown that the effectiveness and robustness of proposed stochastic energy scheduling optimization strategy for MGs are valid.

Wind power operation capacity credit assessment considering energy storage

Research on wind power capacity credit at the operational level plays an important role in power system dispatching.With the popularity of energy storage devices,it is increasingly necessary to study the impact of energy storage devices on wind power operational capacity credit.The definition of wind power operational capacity credit is given.The available capacity model of different generators and the charging and discharging model of the energy storage are established.Based on the above model,the evaluation method of wind power operation credible capacity considering energy storage devices is proposed.The influence of energy storage on the wind power operation credible capacity is obtained by case study,which is of great help for the power system dispatching operation and wind power accommodation.

Optimization operation model of electricity market considering renewable energy accommodation and flexibility requirement

The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumption and improve power system flexibility,a bi-level optimal operation model of the electricity market is proposed.A probabilistic model of the flexibility requirement is established,considering the correlation between wind power,photovoltaic power,and load.A bi-level optimization model is established for the multi-markets;the upper and lower models represent the intra-provincial market and inter-provincial market models,respectively.To efficiently solve the model,it is transformed into a mixed-integer linear programming model using the Karush–Kuhn–Tucker condition and Lagrangian duality theory.The economy and flexibility of the model are verified using a provincial power grid as an example.

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.