ABSTRACT. Accurate battery internal temperature estimation is a key for safe battery operation of electric vehicles. In this paper, a novel hybrid data-driven method combining a linear neural network (NN) model and an extended Kalman filter (EKF) is developed to estimate the internal temperature of a LiFePo4 battery. In order to select the proper input terms of the linear NN model and estimate the associated parameters, a fast recursive algorithm (FRA) is firstly used. Then an EKF with a battery lumped thermal model as the state function is used to filter out the outliers and reduce the errors in estimating the internal temperature based on the linear NN model. The test results from two different experiment data demonstrate that the hybrid method can achieve good estimation accuracy, and the method can be easily applied to other type of batteries.

ABSTRACT. The electric variable transmission in hybrid electric vehicle is a new electromagnetic energy transmission system, which combines the output power from the inner machine and outer machine of electric variable transmission to propel hybrid electric vehicle. This paper focuses on the comparison analysis of power management. The switching strategy and the power follower strategy control the transmission ratio of the electric variable transmission. Making full use of the structural advantages of the electric variable transmission, the engine and road load are isolated to make the engine works in the high efficiency area, thus improving the fuel economy of the vehicle. Then, this paper discusses the dynamic allocation based on the instantaneous optimization strategy, and the optimization algorithm is realized by using the forward dynamic programming. The simulation results demonstrate the feasibility of the proposed strategy, and it can be taken as a new theory and method for the study of hybrid electric vehicle based on electric variable transmission.

ABSTRACT. Charging load modeling for electric vehicles is a fundamental work for most studies related to EVs. However, it is a challenge due to its complexity. This paper proposes a novel EVs charging load model which is applied Bayes method to correct the distribution of the number of EVs start charging and predict the number of EVs start charging. The aggregation impendence model for EVs charging fit for accurate simulation is built. Finally, a study case of a station in Beijing is applied to verify the proposed model. The results shows that the model has satisfactory accuracy.

ABSTRACT. This paper aims to obtain the natural charging behavior characteristic (NCBC) of plug-in electric vehicles (PEVs) via stochastic simulation. To this end, a novel stochastic simulating methodology is proposed. Compared to earlier studies, advantages of the proposed methodology are: 1) it does not need sophisticated transportation datasets; 2) it simulates the charging behaviors of aggregated PEVs more convincingly for a long time window (multi weeks). Then, two parameters are defined to characterize the natural charging behaviors of the large scale aggregated PEVs. And the time-varying pattern of these two NCBC-parameters are analyzed by using the proposed simulating methodology. Finally, the results of NCBC-parameters for large scale heterogeneous PEVs are simulated. These results can be used to evaluate the demand response flexibility of the aggregated charging load (ACL), which is the key to design smart charging schemes.

ABSTRACT. EVs (electric vehicles) can be used as controllable loads and distributed storage devices. On the basis of power batteries, EVs can response to the power grid signals rapidly and accurately. They can provide ancillary services, such as peak shaving, frequency regulation services, etc. In this paper, the cycle life model of EV batteries is established based on four factors: ambient temperature, cycle-index, current and depth of charge/discharge. Besides, in consideration of battery safety, frequency control loop of EVs is obtained. According to simulation results, the stability of power grid can be improved a lot when EVs provide frequency regulation services with traditional generating units. Depending on load category and economical efficiency, frequency regulation is classified into primary, secondary and tertiary. Based on stability of power grid, capacity fade and electrical energy consumption of EV batteries, different strategies are investigated.

ABSTRACT. This paper researches on modeling and design of quasi-Z-source inverter (q-ZSI) applied for PMSM drive system.Using state-space average method, the small-signal model and steady model are builded. Based on the mathematical model of PMSM and q-ZSI, the control systems of dc-link voltage and stator current are designed. The bandwidth of dc-link system is limited to reduce the interference between them. Stability and dynamic characteristics of systems are analyzed using bode diagram. The simulation and experiment indicate that the desgined systems have good dynamic characteristic and anti-interference characteristic.

ABSTRACT. Due to the significant non-linearity of power system, thus linear time-delay model is unable to characterize its dynamics. This paper brings up a novel modeling method, in which we design the controller of time-delay power system, including excitation controller and turbine valve controller of steam turbine generator unit in one machine-infinity bus, based on non-linear control theory. The simulation shows that the designed excitation controller and turbine valve controller by this method have insensitivity on time-delay and robustness, which perform well in depressing external disturbance.

ABSTRACT. This paper investigates the load frequency control (LFC) for multi-area power systems with modeling uncertainties and communication topology changes. A group of convex polytopes is firstly employed to model the uncertainty of power systems. Since the topology variant events are barely impossible to be explicitly detected in reality, the dynamic topology scenario is described as a finite switching set with two kinds of time-varying switching signals, i.e., a random sequence, and a transition probability unknown Markov chain. Based on the above descriptions, a distributed robust control law is proposed to reduce the frequency deviation of each sub-power system. For further alleviating the controller burden, an event-triggered command updating scheme is designed. The proposed LFC strategies not only guarantee the exponential stability of each subsystem but also coordination with the overall power grid. Moreover, only seldom necessary control commands are updated while the rest commands are suspended, meanwhile, the convergent rate of overall power system is also specifiable. Numerical examples are provided to demonstrate the effectiveness of the proposed methods.

ABSTRACT. Reliability is foremost considered in aircraft safety-critical equipment. Multiphase electric machine are gaining a growing interest because of fault tolerance ability, high reliable and high power density, but the complexity of control structure prohibit application for aircraft. The five-phase permanent magnet synchronous motor (PMSM) offers a good compromised between fault tolerance and complexity. This paper presents a five-phase PMSM to drive directly the propeller blade of electric aircraft. Firstly, the torque requirement on propeller blade operation is analyzed in the different flying status. Secondly, near four vectors (NFV) space vector pulse width modulation (SVPWM) is employed to realize motor speed closed loop control, aiming to eliminate the content of the third current harmonics in the stator windings. The speed and torque response for the motor control are measured by simulation, and the results on a five phase PMSM drive for aircraft application are also validated by simulation.

ABSTRACT. This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.

ABSTRACT. Unit Commitment is a mix-integer optimization problem and has long been intractable for power system operators. The binary status and power generation of online units need to be determined simultaneously, while the system constraints are required to maintain at the same time. This paper proposes two binary teaching-learning based optimization methods to solve the unit commitment problem. The new methods are employed to solve different scales of 10-100 unit commitment problems with different spinning reserves. Numerical results show that the proposed new algorithms have superb performance in multiple cases studies.

ABSTRACT. Hybrid Energy Storage Systems (HESS) has the ability of providing fast and accurate response to second-to-second changes of the grids for keeping the power system uninterrupted and stable. This paper presents an enhanced Corrective Security Constrained Optimal Power Flow (CSCOPF) model by combining the technical merits of different Energy Storage technologies. The proposed HESS can be employed to take part in not only the traditional long-term rescheduling corrective control actions, but also the short-term post-contingency fast corrective control, which takes into account the current state of charge (SOC) and the energy capacity model of the HESS. An improved Benders decomposition (BD) method is developed to solve the enhanced CSCOPF problem and the effectiveness of the proposed method is evaluated and demonstrated in the paper by standard power systems.

ABSTRACT. Doubly-fed wind generator is highly sensitive to voltage variations of the grid, which poses limitations for wind power plants during the grid integrated operation. The paper proposes a new control strategy for rotor side converter of doubly-fed induction generator (DFIG) using energy-based control method based on Port-Control Hamiltonian(PCH) theory and L_2 disturbance attenuation. The proposed ride-through approach limits the peak values of the rotor inrush current, needs a lower rotor voltage and suppresses DFIG transient response at the times of occurrence and clearing the fault. The simulation results show that the proposed scheme has a good performance.

ABSTRACT. The distributed $H_\infty$ state estimation problem over a filtering network with Markov switching topology is studied in this paper by employing event-triggered strategy. The strategy at each node is built on the output estimation error of its own and those received from its neighbours. Based on the communication uncertainty of practical networks, switching topology which subjects to a heterogeneous Markov chain is considered in filter design. By utilizing stochastic Markov stability theory, switching topology-dependent filters are designed such that the underlying error system is stochastically stable in mean square and the disturbance rejection attenuation level guarantees an $H_\infty$ performance bound. An illustrative example is presented to show the applicability of the obtained results.

ABSTRACT. This paper presents an improved result on the problem of H1 analysis for networked control systems (NCSs) under the event- triggered communication scheme. The contribution of this paper has two aspects: (1)an improved method is proposed to calculate the maximum allowable number of successive packet losses (MANSPL)- dMANSPL with less conservative condition;(2)then, a stability theorem is presented for NCSs considering both the communication delays and packet losses. Fi- nally, examples are used to demonstrate the e±cacy of the proposed method.

ABSTRACT. Distributed network-induced delays of wireless networked control systems with the multi-channel may deteriorate the performance of control systems, and noise interference of system may also lead to the control quality dropping. To solve these problems, a wireless networked control strategy based on $H_2/H_{\infty}$ filtering is proposed. Firstly, a directed graph is used to describe the communication topology of the distributed sensor nodes, and different Markov chains are employed to describe the characters of network-induced delays in each wireless channel. To improve the precision of the controlled inputs, a $H_2/H_{\infty}$ filter is then designed to reduce noise interference of the output signals of the sensors, and a closed-feedback filtering and control system model is further proposed. Moreover, for the given maximum network-induced delays in each wireless channel, the stochastic stability of the closed-feedback filtering and control system is presented and a prescribed $H_2/H_{\infty}$ performance is also achieved, and the relationships between the stochastic stability criteria, the network-induced delays, the filtering parameters and the controller gain are established. Finally, simulation results confirm the feasibility and effectiveness of the proposed method.

ABSTRACT. Abstract—This paper deals with the problem of mean square (MS) stabilization for a Markov jump linear system (MJLS) over Gaussian relay channel subject to average power constraint. Based on the theory of entropy, a necessary condition of channel capacity for MS stabiliz- ation is proposed. Then by using the Schalkwijk-Kailath encoding scheme, a sufficient con- dition of MS stabilization is derived for a scalar MJLS. Finally, a numerical example is given to show the show the effectiveness and correctness of the theoretical work.

ABSTRACT. Congestion is inevitable in the TCP/IP network. In this paper, the output control method is applied to address the congestion problem of TCP/AQM system. Firstly, a linearized closed-loop model is derived to describe the TCP/AQM system by applying small signal analysis method. Secondly, we construct a novel Lyapunov functional, then, apply Jensens inequality and reciprocally convex approach to resolve the integral items in the derivation of the results. Subsequently, we can obtain the delay-dependent stability and stabilization criteria for the systems in terms of matrix inequalities. Finally, numerical simulations are implemented to confirm the performance of the proposed approach.

ABSTRACT. This paper addresses stabilty problem for a class of networked control systems (NCSs) with network attacks. As a network attack to control systems, denial-of-service attacks are fully taken into account in the NCSs modelling Under the scenario that there exist denial-of-service attacks in the communication channel, a closed-loop system with an error function is provided for the studied NCSs, where the denialof- service attacks are well considered. Then based on the above constructed system model, one sufficient condition is derived for ensuring the uniformly ultimately boundedness of the derived system under consideration, and the upper bound of the maximum allowable number of denial-of-service attack is obtained. Moreover, the celebrated time-delay system technology method is introduced to improve the result of the upper bound of the maximum allowable number of denial-of-service attack. Finally, one numerical example is given to show the effectiveness of the proposed method.

ABSTRACT. Hoop standard granulator is one of the most important equipments in the process of feed production. The performance of its control system will directly affects the quality of feed particles and production efficiency. The conventional control strategy is to apply PID control algorithm to achieve automatic control of the feeding volume and the amount of steam, but the quality of feed particles are unable to guarantee. In this paper, the control strategy of machine vision based networked supervisory control is proposed. Firstly, the feeding volume and the amount of steam is collected and controlled by embedded technology. Secondly, a threshold segmentation algorithm based machine vision technology is used to detect the defects of feed particles. A machine vision based networked supervisory control mechanism is deployed. Through the RS-485 bus, which can adjust the control effect and ensure high quality feed particles produced. The simulation experiment was carried out on the independent software and hardware platform which verified the effectiveness of the networked supervisory control.

ABSTRACT. In this paper, two kinds of control system architectures for the microgrid are presented. The proposed architectures are based on the communication networks and the network-induced delays are depicted by the inverse Gaussian distribution function. The control strategies are designed respectively according to the corresponding architecture. In every strategy the mechanism of event-triggered is used to deal with the different disturbances such as disconnection of main grid and connection of new load. Simulations are carried out to verify the effectiveness of the proposed control approach under different operating conditions.

ABSTRACT. Integration of renewable energy into energy system, which is a reasonable approach for sustainable development, posed a challenge to design, operation and optimization of distributed energy system (DES). The emerging control concept related to DES integrated with renewable energy, namely dynamic match optimization (DMO), is reviewed in this paper. A scoping review, which includes literature research and case introduction, is presented for a preliminary overview on DMO and its two main measures: load forecasting and demand side management. The literature review part contains concept, classification, mathematical tool, research challenges, while case introduction part contains engineering cases and application challenges. The discussion on research and application progress would inform a future picture on development trend of DES.

ABSTRACT. This paper proposes a complex system optimization method to solve economic emission load dispatch. First, a real-world economic emission load dispatch is modeled as a complex system problem, and the optimization objectives include economic load dispatch, emission load dispatch and transmission network loss. Then a called BBO/complex method is introduced, which extends biogeography-based optimization to a multi-archipelago environment to suit the structure of complex systems. Finally, the proposed method is applied to the economic emission load dispatch, and the results show that it can obtain good performance for economic emission load dispatch studied in this paper, and it is a competitive algorithm for solving complex system optimization problem.

ABSTRACT. Abstract—This paper focuses on the circulating current for parallel connected dc-dc converters of dc microgrids and the impact of droop coefficient on load sharing and bus voltage is analyzed. The form of variable droop coefficient and dynamic voltage compensation method is proposed based on the analysis results to suit various situation and steady bus voltage. This method is simple and effective, and it can improve the stability of the system without complicate the system. The simulation model of three parallel converters is built, and the effectiveness of the method is verified by PSCAD/EMTDC simulation software.

ABSTRACT. As a key and popular renewable energy, wind power penetration has increased significantly into the power system worldwide in recent years. In order to solve the stochastic nature of wind power and develop better dispatch plan, wind power forecasting is imperative before integrating it into the system. To achieve better forecasting accuracy, it is necessary to investigate the significance of temporal resolution for model based multi-step forecasting. In this paper, three models, namely Gaussian process (GP), temporally local Gaussian process (TLGP) and persistence are employed for short term wind power forecasting under two temporal forecasting resolutions, e.g. hourly and quarter-hourly. The methods are applied to the data collected from a wind farm located in Texas, USA. A key finding is that the hourly forecasting is more accurate and computationally efficient than the quarter-hour resolution. Another finding is that, to achieve the best forecasting performance regardless of the resolutions, the models need to use data of the same length of time period. However, a combination consideration should be taken regarding the minimum horizon required.

ABSTRACT. Wind prediction is a key technique for seamless integration of large penetration of wind power into the power system. In this study, a nonlinear autoregressive model with exogenous inputs (NARX) is developed to predict the power consumption of a single wind turbine. The training data for the NARX models are collected from a 1.5MW wind turbine of a wind farm located at Northeast of China. The accuracy of models using different independent inputs including wind direction, speed as well as engine room position, is compared. The results show that the resultant NARX models are capable of capturing the dynamic characteristics of wind turbine power consumption, and the modelling accuracy with three inputs is better than of the model using only two inputs.

ABSTRACT. This paper presents a preliminary study of developing a novel platform for big data management, processing and analysis of modern power systems. The framework comprises a big data acquisition subsystem, a big data analysis subsystem, a decision-making assistance subsystem and an information integration subsystem. For the big data management system, a novel structure is designed according to three different data resources, including database, data files and data stream. Further, powerful open-source computation algorithms and self-developed novel intelligent methods are integrated in the big data analysis system. To be specific, our early work on statistical processing monitoring (Principal Component Analysis (PCA)), advanced modelling methods (Fast Recursive Algorithm (FRA)) and newly developed optimization method (Teaching-Learning Based Optimization (TLBO)) are integrated into a self-developed analysis module. Thus, with the novel big data acquisition structure and data processing engine, the proposed platform can provide a powerful tool for big data analytic based Smart Grid monitoring.

ABSTRACT. To cope with data collision problem in consensus synchronization algorithm caused by utilizing pseudo-periodic broadcast method, this paper presents a novel gossip averaging based clock synchronization protocol, which combines the asynchronism of rumor communication and the robustness of neighbor averaging. We design a randomized link-activated based relative skew estimation strategy, which realizes gossip averaging compensation for each node's logical clock. Further, in order to accelerate global convergence rate, those links which do not share common point are colored. Numerical simulations are studied to validate the convergence of proposed protocol under different topologies, and the results show that improved mechanism avoid the collision problem effectively.

ABSTRACT. The information fusion estimation problems are investigated for uncertain systems with cross-correlated noises and data transmission delays. Based on Kalman filtering theory,a distributed fusion estimation scheme is proposed by distributed information perception and centralized fusion. To alleviate the communication burden and computational cost with network-induced transmission delays, the measurement transformation approach with re-organized innovation sequence is proposed. Depending on the fusion criterion, the optimal weighted fusion estimators are designed via minimizing error cross-covariance theory to reduce information redundancy and maintain the higher measurement accuracy. An illustrative example is given to validate the effectiveness of the proposed method.