Kang Li

• Queen's University Belfast

Plug-and-play (PnP) operations of distributed generation units (DGUs) with constant power loads (CPLs) often destabilize dc microgrids (DCmGs). To address this issue, this article proposes a scalable neural network control strategy for nonlinear DCmGs with CPLs, enabling seamless PnP operations of DGUs. A radial basis function neural network is emp...

The plugging-in/-out of renewable distributed generation units (DGUs) often alters the microgrid size and coupling terms, resulting in computational burdens and voltage shocks. This paper proposes a novel scalable fuzzy voltage control scheme for nonlinear DC microgrids (DCmGs) composed of DGUs and constant power loads (CPLs) interconnected via pow...

The fraction model has been widely used to represent a range of engineering systems. To accurately identify the fraction model is however challenging, and this paper presents a regularised fast recursive algorithm (RFRA) to identify both the true fraction model structure and the associated unknown model parameters. This is achieved first by transfo...

With the advent of sustainable and clean energy transitions, lithium-ion batteries have become one of the most important energy storage sources for many applications. Battery management is of utmost importance for the safe, efficient, and long-lasting operation of lithium-ion batteries. However, the frequently changing load and operating conditions...

Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges. The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems (CPPSs). This paper presents a comprehensive rev...

The urbanization and megalopolis have deteriorated traffic concerns, energy crisis and carbon pollution, such that the electric vehicles are expected to be an essential role. In this study, a flexible-possibilist chanced constraints programming (FCCP) model is developed to plan the low-carbon energy-transportation systems at a metropolitan scale (M...

In Yangtze River traffic management, to manage ship sequencing and scheduling effectively and efficiently in restricted waterways has long been a challenging issue. This paper proposes a Sliding Window based Online ship Sequencing and Scheduling algorithm (OSS-SW) to tackle this problem. The OSS algorithm is capable of generating a more efficient s...

Manufacturing chain of lithium-ion batteries belongs to a significantly complex process with many coupled product parameters and intermediate products. To well monitor and optimize battery manufacturing process, it is vital to design a data-driven approach for effectively modelling and classifying the product properties within this complicated prod...

The state of charge (SOC) estimation of Li-ion batteries has attracted substantial interests in recent years. Kalman Filter has been widely used in real-time battery SOC estimation, however, to build a suitable dynamic battery state-space model is a key challenge, and most existing methods still use the off-line modelling approach. To capture the d...

COVID-19 has rapidly spread around the world in the past few months, researchers around the world are working around the clock to closely monitor and assess the development of this pandemic. In this paper, a time series regression model is built to assess the short-term progression of COVID-19 pandemic. The model structure and parameters are identi...

Supervisory control and data acquisition (SCADA) system has been widely used in traditional power systems for operation and control. As increasingly more ICT technologies are deployed to improve the smartness of the power grid, cyber security is becoming an important issue in the development of smart grids, for example, false data injection attack...

The ongoing COVID-19 pandemic spread to the UK in early 2020 with the first few cases being identified in late January. A rapid increase in confirmed cases started in March, and the number of infected people is however unknown, largely due to the rather limited testing scale. A number of reports published so far reveal that the COVID-19 has long in...

In a Fused Magnesia Smelting Process(FMSP), its electricity demand is defined as the average electric power consumption over a fixed period of time and often used to calculate the electricity cost. The power supply has to be switched off once the demand value exceeds one specific threshold for safety and economic reasons. However, it has been shown...

Conventional unit commitment is a mixed integer optimization problem and has long been a key issue for power system operators. The complexity of this problem has increased in recent years given the emergence of new participants such as large penetration of plug-in electric vehicles. In this paper, a new model is established for simultaneously consi...

This paper applies advanced battery modeling and multi-objective constrained nonlinear optimization techniques to derive suitable charging patterns for lithium-ion batteries. Three important yet competing charging objectives, including battery health, charging time, and energy conversion efficiency, are taken into account simultaneously. These opti...

Temperature is a crucial state to guarantee the reliability and safety of a battery during operation. The ability to estimate battery temperature, especially the internal temperature, is of paramount importance to the battery management system for monitoring and thermal control purposes. In this paper, a data-driven approach combining the RBF neura...

As a novel family member of the redox flow batteries (RFBs), the single flow zinc-nickel battery (ZNB) without ion exchange membranes has attracted a lot of interests in recent years due to the high charging and discharging efficiencies. To understand the electrical behaviour is a key for proper battery management system. Unlike the electrochemical...

The majority of embedded systems are designed for specific applications, often associated with limited hardware resources in order to meet various and sometime conflicting requirements such as cost, speed, size and performance. Advanced intelligent heuristic optimization algorithms have been widely used in solving engineering problems. However, the...

Probabilistic wind power forecasting has become an important tool for optimal economic dispatch and unit commitment of modern power systems with significant renewable energy penetrations. Ensemble forecasting based on Monte Carlo simulation is commonly used by many grid operators, but other probabilistic approaches, such as multi-step iterative win...

In this paper, a new online proportional-integral-derivative (PID) controller parameter optimisation method is proposed by incorporating the philosophy of the model predictive control (MPC) algorithm. The future system predictive output and control sequence are first written as a function of the controller parameters. Then PID controller design is...

Batteries have been widely applied in many high-power applications, such as electric vehicles (EVs) and hybrid electric vehicles, where a suitable battery management system (BMS) is vital in ensuring safe and reliable operation of batteries. This paper aims to give a brief review on several key technologies of BMS, including battery modelling, stat...

Lithium-ion (Li-ion) battery charging is a crucial issue in energy management of electric vehicles. Developing suitable charging patterns, while taking into account of various contradictory objectives and constraints is a key but challenging topic in battery management. This paper develops a model based strategy that optimizes the charging patterns...

Local variable selection by first order expansion for nonlinear nonparametric systems is investigated in the paper. By substantially modifying the algorithms developed in our earlier work (Bai et al., 2014), the previous results have been considerably strengthened under much less restrictive conditions. Firstly, the estimates generated by the modif...

As a popular type of Redox Flow Batteries (RFBs), single flow Zinc Nickel Battery (ZNB) was proposed in the last decade without requiring an expensive and complex ionic membrane in the battery. In this paper, a Radial Basis Function (RBF) neural model is proposed for modelling the behaviours of ZNBs. Both the linear and non-linear parameters in the...

A novel framework for the state-of-charge (SOC) estimation of lithium batteries is proposed in this paper based on an adaptive unscented Kalman filters (AUKF) and radial basis function (RBF) neural networks. Firstly, a compact off-line RBF network model is built using a two-stage input selection strategy and the differential evolution optimization...

The injection stretch blow moulding (ISBM) process is widely used to manufacture plastic bottles for the beverage and consumer goods industry. The majority of the production processes are open-loop systems, often suffering from high raw material and energy waste. In this paper, a heuristic based norm-optimal terminal iterative learning control (ILC...

Unit commitment is a traditional mixed-integer non-convex problem and remains a key optimisation task in power system scheduling. The high penetration of intermittent renewable generations such as wind and solar as well as mass roll-out of plug-in electric vehicles (PEVs) impose significant challenges to the traditional unit commitment problem, not...

The Organic Rankine Cycle (ORC) is a promising technique to recover low grade waste heat, and thus helps to improve the overall thermal efficiency of a process and reduce the environmental impact of large consumption of fossil fuels. A proper control strategy is a key for the safe and efficient operation of the ORC systems. In this paper, the key c...

By supplying thermal and electric energies to host facilities, microgrids with combined heat and power can enhance the resilience of urban energy systems. However, the increasing use of gas-fired distributed generations is pushing gas distribution networks to their operating limits, which may cause significant adverse impacts on microgrids. This pa...

Teaching-learning-based Optimization (TLBO) is a popular meta-heuristic optimisation method that has been used in solving a number of scientific and engineering problems. In this paper, a new variant, namely Teaching-learning-feedback-based Optimization (TLFBO) is proposed. In addition to the two phases in the canonical TLBO, an additional feedback...

Network based identification of multivariable systems plays a key role in future smart manufacturing systems in achieving the goals of industry 4.0. The incomplete information caused by network traffic congestion or cyber-attack in the networked environment will inevitably deteriorate the performance of system identification, and in the extreme cas...

Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled...

Significant penetration of renewable generations (RGs) and mass roll-out of plug-in electric vehicles (PEVs) will pay a vital role in delivering the low carbon energy future and low emissions of greenhouse gas (GHG) that are responsible for the global climate change. However, it is of considerable difficulties to precisely forecast the undispatchab...

The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2017, and of the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, held in Nanjing, China, in September 2017. The 208 r...

No single solution currently exists to achieve the utopian desire of zero fossil fuel electricity generation. Until such time, it is evident that the energy mix will contain a large variation in stochastic and intermittent sources of renewable energy such as wind power. The increasing prominence of wind power in pursuit of legally binding European...

The Organic Rankine Cycle (ORC) process is promised to significantly recycle the waste heat from medium and low temperature heat sources, achieve better performance to recover low grade waste heat than traditional waste heat recovery processes used in the industrial applications. An accurate ORC model is indispensable for the optimization and contr...

Local variable selection by first order expansion for nonlinear nonparametric systems is investigated in the paper. By substantially modifying the algorithms developed in our earlier work, the previous results have been considerably strengthened under much less restrictive conditions. Precisely, the estimates generated by the modified algorithms ar...

The accuracy of surface measurement determines the manufacturing quality of membrane mirrors. Thus, an efficient and accurate measuring method is critical in membrane mirror fabrication. This paper formulates this measurement issue as a surface reconstruction problem and employs two-stage trained Zernike polynomials as an inline measuring tool to s...

This paper proposes a simplified microturbine (MT) model which allows for dynamic heat and power output prediction. Considering the time-scale difference of various dynamic processes occuring within MTs, the electromechanical subsystem is treated as a fast quasi-linear system while the thermo-mechanical subsystem is treated as a slow process with h...

A risk assessment based adaptive ultra-short-term wind power prediction (USTWPP) method is proposed in this paper. In this method, features are first extracted from the historical data, and then each wind power time series (WPTS) is split into several subsets defined by their stationary patterns. A WPTS that does not match any of the stationary pat...

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect...

In order to enhance the problem solving skills of students majoring in wind energy and power engineering, a novel TRIZ based strategy is developed for teaching the wind turbine control module. By utilizing the TRIZ theory, the key control parameters for wind turbines are identified and comprehensively analyzed, and the contradictions among various...

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...

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,...

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 metho...

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 n...

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...

The automotive industry is continuously developing technologies and strategies for increasing the efficiency in fuel consumption and reducing the emission of pollutants. The variable valve timing (VVT) system provides such a solution for internal combustion engines. Researches in this area are mainly devoted both to improved layouts and to new oper...

Yangtze River is the world's busiest inland waterway. Ships need to be guided when passing through controlled waterways based on their trajectory predictions. Inaccurate predicted trajectories lead to non-optimal traffic signalling which may cause significant traffic jam. For the existing intelligent traffic signalling systems (ITSSs), ships are su...

Unit commitment is a key issue in power system operation and has long been an intractable problem due to its complex mix-integer nonlinear formulation. The original unit commitment problem aims to minimize the fossil fuel cost by determining the on/off status of power units and power contribution of each online unit at the same time. However, the u...

Battery charging strategy is a key issue in battery management system to ensure good battery performance and safe operation during the charging process. In this paper, a novel battery optimal charging strategy is proposed by applying the TLBO algorithm to a LiFeP04 battery for an optimal charging based on a coupled thermoelectric model. A specific...

Large scale wind power generation complicated with restrictions on the tie line plans may lead to significant wind power curtailment and deep cycling of coal units during the valley load periods. This study proposes a dispatch strategy for interconnected wind-coal intensive power systems (WCISs). Wind power curtailment and cycling of coal units are...

The European Union continues to exert a large influence on the direction of member states energy policy. The 2020 targets for renewable energy integration have had significant impact on the operation of current power systems, forcing a rapid change from fossil fuel dominated systems to those with high levels of renewable power. Additionally, the ov...

Due to the variability and stochastic nature of wind power, accurate wind power forecasting plays an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disa...

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-chan...

Throughout the European Union there is an increasing amount of wind generation being dispatched-down due to the binding of power system operating constraints from high levels of wind generation. This paper examines the impact a system non-synchronous penetration limit has on the dispatch-down of wind and quantifies the significance of interconnecto...

Gas fired generation currently plays an integral support role ensuring security of supply in power systems with high wind power penetrations due to its technical and economic attributes. However, the increase in variable wind power has affected the gas generation output profile and is pushing the boundaries of the design and operating envelope of g...

The demand for sustainable development has resulted in a rapid growth in wind power worldwide. Although various approaches have been proposed to improve the accuracy and to overcome the uncertainties associated with traditional methods, the stochastic and variable nature of wind still remains the most challenging issue in accurately forecasting win...

This study presents a novel analysis of the utilisation of grid scale energy storage to mitigate negative system operational impacts due to high penetrations of wind power. This was investigated by artificially lowering the minimum stable generation level of a gas thermal generating unit coupled to a storage device over a five hour storage charging...

Modern control methods like optimal control and model predictive control (MPC) provide a framework for simultaneous regulation of the tracking performance and limiting the control energy, thus have been widely deployed in industrial applications. Yet, due to its simplicity and robustness, the conventional P (Proportional) and PI (Proportional-Integ...

Dependency on thermal generation and continued wind power growth in Europe due to renewable energy and greenhouse gas emissions targets has resulted in an interesting set of challenges for power systems. The variability of wind power impacts dispatch and balancing by grid operators, power plant operations by generating companies and market wholesal...

Due to the variability of wind power, it is imperative to accurately and timely forecast wind generation to enhance the flexibility and reliability of the operation and control of real-time power systems. Special events such as ramps and spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Ga...

Electric vehicles provide an opportunit y to reduce fossil fuel consumptions and to decrease the emissions of green­ house gas and air pollutants from the transport sector. The adoption of a large number of plug-in electric vehicles however imposes significant impacts on the power s y stem operation due to uncertain charging and discharging pattern...

Increasing installed capacities of wind power in an effort to achieve sustainable power systems for future generations pose problems for system operators. Volatility in generation volumes due to the adoption of stochastic wind power is increasing. Storage has been shown to act as a buffer for these stochastic energy sources, facilitating the integr...

A new fast estimation algorithm is derived for identification of non-linear dynamic systems using radial basis function networks. The new algorithm is able to both select the hidden nodes and to compute weights of the output layer in the radial basis function neural networks (RBFN) simultaneously in a stepwise forward fashion.

The existence of loose particles left inside the sealed electronic devices is one of the main factors affecting the reliability of the whole system. It is important to identify the particle material for analyzing their source. The conventional material identification algorithms mainly rely on time, frequency and wavelet domain features. However, th...

Electric vehicles (EVs) offer great potential to move from fossil fuel dependency in transport once some of the technical barriers related to battery reliability and grid integration are resolved. The European Union has set a target to achieve a 10% reduction in greenhouse gas emissions by 2020 relative to 2005 levels. This target is binding in all...

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to...

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively consi...

We consider the local order estimation of nonlinear autoregressive systems with exogenous inputs (NARX), which may have different local dimensions at different points. By minimizing the kernel-based local information criterion introduced in this paper, the strongly consistent estimates for the local orders of the NARX system at points of interest a...

Economic dispatch (ED) problems often exhibit non-linear, non-convex characteristics due to the valve point effects. Further, various constraints and factors, such as prohibited operation zones, ramp rate limits and security constraints imposed by the generating units, and power loss in transmission make it even more challenging to obtain the globa...

This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The...

Polymer extrusion is fundamental to the processing of polymeric materials and melt flow temperature homogeneity is a major factor which influences product quality. Undesirable thermal conditions can cause problems such as melt degradation, dimensional instability, weaknesses in mechanical/optical/geometrical properties, and so forth. It has been re...

This paper investigates the problem of identification of a class of Hammerstein systems over a wireless network. An iterative identification method is implemented over a physical IEEE 802.11b wireless channel. Every time the identified model is used into next identification process to produce the estimated values of the plant outputs for compensati...

This paper describes the communication requirements for an intelligent electric vehicle charge station which can provide inertial support to the electricity grid. The application is described. Telecoms delivery technologies are experimentally assessed, and an open source measurement system is discussed.

Electric vehicles (EVs) are becoming more popular and have gained better customer acceptance in the past few years due to the improved performances, such as high acceleration rate and long driving distance from a single charging. Recent research also shows some promising benefits from integrating EVs with power grid. One of these is to use EV batte...

In recent years, renewable energy resources have drawn a lot of attention worldwide in developing a more sustainable society. Among various forms of renewable energies, wind power has been recognized as one of the most promising ones in many countries and regions including Northern Ireland and Ireland according to the National Renewable Energy Acti...

Mankind is facing the twin challenges of sustainable energy supply and climate change due to the greenhouse gases emissions. Reducing the energy consumption has been given a significant role in addressing these problems. Although modern control technologies have been successfully applied in many engineering systems, PID (Proportional-Integral-Deriv...

In this paper, a systematic approach adopting sparse least-squares SVMs (LS-SVMs) is proposed to automatically detect fire using vision-based systems with fast speed and good performance. Within this framework, the features are first extracted from input images using wavelet analysis. The LS-SVM is then trained on the obtained dataset with global s...

A number of neural networks can be formulated as the linear-in-the-parameters models. Training such networks can be transformed to a model selection problem where a compact model is selected from all the candidates using subset selection algorithms. Forward selection methods are popular fast subset selection approaches. However, they may only produ...

Extrusion is one of the fundamental production methods in the polymer processing industry and is used in the production of a large number of commodities in a diverse industrial sector. Being an energy intensive production method, process energy efficiency is one of the major concerns and the selection of the most energy efficient processing conditi...

Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost...

In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The prefo...