An intelligent network control system for plug-in electric vehicles and the associate communication mechanism

The development of an intelligent plug-in electric vehicle (PEV) network is an important research topic in the smart grid environment. An intelligent PEV network enables a flexible control of PEV charging and discharging activities and hence PEVs can be utilized as ancillary service providers in the power system concerned. Given this background, an intelligent PEV network architecture is first developed, and followed by detailed designs of its application layers, including the charging and discharging controlling system, mobility and roaming management, as well as communication mechanisms associated. The presented architecture leverages the philosophy in mobile communication network buildup

Realizing 'four comforts' in the urban fringe : the case of White Horse Lake Eco-creative City Project, Hangzhou, China

This article examines a cultural and creative industries park project – the White Horse Lake Ecocreative City on land outside the urban centre of Hangzhou, China, which uses an imaginary rural lifestyle as its key attraction. By analysing government policies and development plans, and through interviews with initiators, managers and creative practitioners, the article first assesses the geographical position, that is, the impact of locality with regard to both hard and soft infrastructure of the project; it then examines the synergies and tensions embedded in the strategic goals, that is, to build the right city for ‘four comforts’ (siyi, 四宜) – for residence, for business, for travel and for culture. The article concludes that Chinese-style cultural conversion remains locked in a top-down ideological framework, one that rural residents and the new ‘creative class’ are expected to respect.

A new approach for power system black-start decision-making with vague set theory

Power system restoration after a large area outage involves many factors, and the procedure is usually very complicated. A decision-making support system could then be developed so as to find the optimal black-start strategy. In order to evaluate candidate black-start strategies, some indices, usually both qualitative and quantitative, are employed. However, it may not be possible to directly synthesize these indices, and different extents of interactions may exist among these indices. In the existing black-start decision-making methods, qualitative and quantitative indices cannot be well synthesized, and the interactions among different indices are not taken into account. The vague set, an extended version of the well-developed fuzzy set, could be employed to deal with decision-making problems with interacting attributes. Given this background, the vague set is first employed in this work to represent the indices for facilitating the comparisons among them. Then, a concept of the vague-valued fuzzy measure is presented, and on that basis a mathematical model for black-start decision-making developed. Compared with the existing methods, the proposed method could deal with the interactions among indices and more reasonably represent the fuzzy information. Finally, an actual power system is served for demonstrating the basic features of the developed model and method.

The ‘Russian doll’ approach : developing nested case-studies to support international comparative research in education

International comparison is complicated by the use of different terms, classification methods, policy frameworks and system structures, not to mention different languages and terminology. Multi-case studies can assist in the understanding of the influence wielded by cultural, social, economic, historical and political forces upon educational decisions, policy construction and changes over time. But case studies alone are not enough. In this paper, we argue for an ecological or scaled approach that travels through macro, meso and micro levels to build nested case-studies to allow for more comprehensive analysis of the external and internal factors that shape policy-making and education systems. Such an approach allows for deeper understanding of the relationship between globalizing trends and policy developments.

An optimal under-frequency load shedding strategy considering distributed generators and load static characteristics

The well-established under-frequency load shedding (UFLS) is deemed to be the last of effective remedial measures against a severe frequency decline of a power system. With the ever-increasing size of power systems and the extensive penetration of distributed generators (DGs) in power systems, the problem of developing an optimal UFLS strategy is facing some new challenges. Given this background, an optimal UFLS strategy for a distribution system with DGs and load static characteristics taken into consideration is developed. Based on the frequency and the rate of change of frequency, the presented strategy consists of several basic rounds and a special round. In the basic round, the frequency emergency can be alleviated by quickly shedding some loads. In the special round, the frequency security can be maintained, and the operating parameters of the distribution system can be optimized by adjusting the output powers of DGs and some loads. The modified IEEE 37-node test feeder is employed to demonstrate the essential features of the developed optimal UFLS strategy in the MATLAB/SIMULINK environment.

Analytical model for fault section estimation and state identification of unobserved protective relays in power systems [电力系统故障诊断与不可观测保护状态识别的解析模型]

In recent years, some models have been proposed for the fault section estimation and state identification of unobserved protective relays (FSE-SIUPR) under the condition of incomplete state information of protective relays. In these models, the temporal alarm information from a faulted power system is not well explored although it is very helpful in compensating the incomplete state information of protective relays, quickly achieving definite fault diagnosis results and evaluating the operating status of protective relays and circuit breakers in complicated fault scenarios. In order to solve this problem, an integrated optimization mathematical model for the FSE-SIUPR, which takes full advantage of the temporal characteristics of alarm messages, is developed in the framework of the well-established temporal constraint network. With this model, the fault evolution procedure can be explained and some states of unobserved protective relays identified. The model is then solved by means of the Tabu search (TS) and finally verified by test results of fault scenarios in a practical power system.

Transmission system expansion planning considering combined operation of wind farms and energy storage systems

An energy storage system (ESS) can provide ancillary services such as frequency regulation and reserves, as well as smooth the fluctuations of wind power outputs, and hence improve the security and economics of the power system concerned. The combined operation of a wind farm and an ESS has become a widely accepted operating mode. Hence, it appears necessary to consider this operating mode in transmission system expansion planning, and this is an issue to be systematically addressed in this work. Firstly, the relationship between the cost of the NaS based ESS and its discharging cycle life is analyzed. A strategy for the combined operation of a wind farm and an ESS is next presented, so as to have a good compromise between the operating cost of the ESS and the smoothing effect of the fluctuation of wind power outputs. Then, a transmission system expansion planning model is developed with the sum of the transmission investment costs, the investment and operating costs of ESSs and the punishment cost of lost wind energy as the objective function to be minimized. An improved particle swarm optimization algorithm is employed to solve the developed planning model. Finally, the essential features of the developed model and adopted algorithm are demonstrated by 18-bus and 46-bus test systems.

Power electronic converters for high power ultrasound transducers

Piezoelectric transducers convert electrical energy to mechanical energy and play a great role in ultrasound systems. Ultrasound power transducer performance is strongly related to the applied electrical excitation. To have a suitable excitation for maximum energy conversion, it is required to analyze the effects of input signal waveform, medium and input signal distortion on the characteristic of a high power ultrasound system (including ultrasound transducer). In this research, different input voltage signals are generated using a single-phase power inverter and a linear power amplifier to excite a high power ultrasound transducer in different medium (water and oil) in order to study the characteristic of the system. We have also considered and analyzed the effect of power converter output voltage distortions on the performance of the high power ultrasound transducer using a passive filter.

A wide area monitoring system based load restoration method

Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.

Performance comparison of four power system stabilizer

The well-known power system stabilizer (PSS) is used to generate supplementary control signals for the excitation system of a generator so as to damp low frequency oscillations in the power system concerned. Up to now, various kinds of PSS design methods have been proposed and some of them applied in actual power systems with different degrees. Given this background, the small-disturbance eigenvalue analysis and large-disturbance dynamic simulations in the time domain are carried out to evaluate the performances of four different PSS design methods, including the Conventional PSS (CPSS), Single-Neuron PSS (SNPSS), Adaptive PSS (APSS) and Multi-band PSS (MBPSS). To make the comparisons equitable, the parameters of the four kinds of PSSs are all determined by the steepest descent method. Finally, an 8-unit 24-bus power system is employed to demonstrate the performances of the four kinds of PSSs by the well-established eigenvalue analysis as well as numerous digital simulations, and some useful conclusions obtained.

The correlation between electric field emission phenomenon and Schottky contact reverse bias characteristics in nanostructured systems

Two different morphologies of nanotextured molybdenum oxide were deposited by thermal evaporation. By measuring their field emission (FE) properties, an enhancement factor was extracted. Subsequently, these films were coated with a thin layer of Pt to form Schottky contacts. The current-voltage (I-V) characteristics showed low magnitude reverse breakdown voltages, which we attributed to the localized electric field enhancement. An enhancement factor was obtained from the I-V curves. We will show that the enhancement factor extracted from the I-V curves is in good agreement with the enhancement factor extracted from the FE measurements.

Coordinated probabilistic optimal decision-making model for multi-area ATC with risk control

In the decision-making of multi-area ATC (Available Transfer Capacity) in electricity market environment, the existing resources of transmission network should be optimally dispatched and coordinately employed on the premise that the secure system operation is maintained and risk associated is controllable. The non-sequential Monte Carlo simulation is used to determine the ATC probability density distribution of specified areas under the influence of several uncertainty factors, based on which, a coordinated probabilistic optimal decision-making model with the maximal risk benefit as its objective is developed for multi-area ATC. The NSGA-II is applied to calculate the ATC of each area, which considers the risk cost caused by relevant uncertainty factors and the synchronous coordination among areas. The essential characteristics of the developed model and the employed algorithm are illustrated by the example of IEEE 118-bus test system. Simulative result shows that, the risk of multi-area ATC decision-making is influenced by the uncertainties in power system operation and the relative importance degrees of different areas.

Analysis and optimisation of the preferences of decision-makers in black-start group decision-making

As the first stage of power system restoration after a blackout, an optimal black-start scheme is very important for speeding up the whole restoration procedure. Up to now, much research work has been done on generating or selecting an optimal black-start scheme by a single round of decision-making. However, less attention has been paid for improving the final decision-making results through a multiple-round decision-making procedure. In the group decision-making environment, decision-making results evaluated by different black-start experts may differ significantly with each other. Thus, the consistency of black-start decision-making results could be deemed as an important indicator in assessing the black-start group decision-making results. Given this background, an intuitionistic fuzzy distance-based method is presented to analyse the consistency of black-start group decision-making results. Moreover, the weights of black-start indices as well as the weights of decision-making experts are modified in order to optimise the consistency of black-start group decision-making results. Finally, an actual example is served for demonstrating the proposed method.

A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles

Plug-in electric vehicles (PEVs) are increasingly popular in the global trend of energy saving and environmental protection. However, the uncoordinated charging of numerous PEVs can produce significant negative impacts on the secure and economic operation of the power system concerned. In this context, a hierarchical decomposition approach is presented to coordinate the charging/discharging behaviors of PEVs. The major objective of the upper-level model is to minimize the total cost of system operation by jointly dispatching generators and electric vehicle aggregators (EVAs). On the other hand, the lower-level model aims at strictly following the dispatching instructions from the upper-level decision-maker by designing appropriate charging/discharging strategies for each individual PEV in a specified dispatching period. Two highly efficient commercial solvers, namely AMPL/IPOPT and AMPL/CPLEX, respectively, are used to solve the developed hierarchical decomposition model. Finally, a modified IEEE 118-bus testing system including 6 EVAs is employed to demonstrate the performance of the developed model and method.

A multi-objective optimization approach for coordinating available transfer capability with risk control

In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.