Electrical power generation from randomly-oriented electrospun nanofibrous nonwoven

In this study, we have demonstrated that randomly-oriented electrospun PVDF nanofiber nonwovens can be used directly as an active layer to generate electrical power with a voltage output as high as 4 volt and current 4 micoramp scales on a small nonwoven piece. This discovery may provide a simple, efficient, cost-effective and flexible solution to self-powering of microelectronics for various purposes.

A new approach for wind and solar type DG placement in power distribution networks to enhance systems stability

This paper proposes a distributed generator (DG) placement methodology based on newly defined term reactive power loadability. The effectiveness of the proposed planning is carried out over a distribution test system representative of the Kumamoto area in Japan. Firstly, this paper provides simulation results showing the sensitivity of the location of renewable energy based DG on voltage profile and stability of the system. Then, a suitable location is identified for two principal types DG, i. e., wind and solar, separately to enhance the stability margin of the system. The analysis shows that the proposed approach can reduce the power loss of the system, which in turn, reduces the size of compensating devices.

Design of a norm-bounded LQG controller for power distribution networks with distributed generation

This paper presents a novel excitation control design to improve the voltage profile of power distribution networks with distributed generation and induction motor loads. The system is linearised by perturbation technique. Controller is designed using the linear-quadratic-Gaussian (LQG) controller synthesis method. The LQG controller is addressed with norm-bounded uncertainty. The approach considered in this paper is to find the smallest upper bound on the H∞ norm of the uncertain system and to design an optimal controller based on this bound. The design method requires the solution of a linear matrix inequality. The performance of the controller is tested on a benchmark power distribution system. Simulation results show that the proposed controller provides impressive oscillation damping compared to the conventional excitation controller.

Effects of load modeling in power distribution system with distributed wind generation

This paper presents the impact of different types of load models in distribution network with distributed wind generation. The analysis is carried out for a test distribution system representative of the Kumamoto area in Japan. Firstly, this paper provides static analysis showing the impact of static load on distribution system. Then, it investigates the effects of static as well as composite load based on the load composition of IEEE task force report [1] through an accurate time-domain analysis. The analysis shows that modeling of loads has a significant impact on the voltage dynamics of the distribution system with distributed generation.

Voltage oscillations in power distribution networks in the presence of DFIGs and induction motor loads

This paper investigates the oscillatory behavior of power distribution systems in the presence of distributed generation. The analysis is carried out over a distribution test system with two doubly fed induction type wind generators and different types of induction motor loads. The system is linearized by the perturbation method. Eigenvalues are calculated to see the modal interaction within the system. The study indicates that interactions between closely placed converter controllers and induction motor loads significantly influence the damping of the oscillatory modes of the system. The critical modes have a frequency of oscillation between the electromechanical and subsynchronous oscillations of power systems. Time-domain simulations are carried out to verify the validity of the modal analysis and to provide a physical feel for the types of oscillations that occur in distribution systems. Finally, significant parameters of the system that affect the damping and frequency of the oscillation are identified.

Agent-based reactive power management of power distribution networks with distributed energy generation

In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

Distribution of power requirements during yarn winding in ring spinning

A model of a yam package is established for a ring spinning system. The yarn layer, surface area, and mass of the yam package are formulated with respect to the diameters of the empty bobbin and full yarn package, yarn count, and yarn winding-on time. Based on the principles of dynamics and aerodynamics, models of the power requirements for overcoming the skin friction drag, increasing the kinetic energy of the yarn package (bobbin and wound yarn), and overcoming the yarn wind-on tension are developed. The skin friction coefficient on the surface of a rotating yam package is obtained from experiment. The power distribution during yam packaging is discussed based on a case study. The results indicate that overcoming the skin friction drag during yarn winding consumes the largest amount of energy. The energy required to overcome the yarn wind-on tension is also significant.

Relationship between workplace reform and workforce participation

This thesis sought to advance understanding of the politics of workplace reform, explaining the respective roles of management and employees and how they relate. The literature on workplace reform usually argues that reform is predicated on greater workforce participation in managerial decisions. More specifically, different approaches to workplace reform can be aligned to different forms of participation. Thus quality management can be associated with direct forms of participation, institutional workplace reform may depend on representative forms, and best practice may require a combination of both. This thesis uses empirical evidence to explore this alignment between the different approaches to workplace reform and forms of participation. The period chosen for empirical study is approximately 1985-1992 - an era of rapid innovation in workplace reform for Australian manufacturing. Three workplaces were chosen for intensive study from automotive component manufacturers because that industry was itself a laboratory for workplace reform and also because these firms exemplified different approaches to competitiveness and reform. Three approaches to workplace reform - quality management, institutional workplace reform, and best practice - were distinguished to capture the range of Australian practice at that time. Similarly two approaches to workplace participation were distinguished - direct and representative - to reflect the range of observable practices at that time and to represent competing philosophies. Direct participation illustrated an approach founded in managerial context of the political status quo, whilst representative forms were considered to permit a pluralist shift of power to enable employees to manage in place of management. The three case studies depict companies sharing the competitive crisis of their industry. From this stems the impetus for workplace reform. At this point the firms diverged in their choice of competitive strategies for workplace reform. The case studies reveal, at the superficial level, a match between the chosen approaches to workplace reform and forms of participation. Basically, quality management is associated with direct employee participation, institutional workplace reform with collective bargaining and representative consultative committees, and best practice with both. However when the implementation of reform and participation are examined this match becomes less significant. One firm, Auto Air, achieved highly effective outcomes in both reform and participation. Another firm, Auto Electrical, failed in both. The thesis concluded that the relationship between forms of participation and reform is less significant than the effective implementation of policy. Unitarist or pluralist approaches to power distribution count less than managerial capacity to integrate successive reform initiatives and their commitment to workforce participation hi change.

Short-term load and wind power forecasting using neural network-based prediction intervals

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Construction of neural network-based prediction intervals for short-term electrical load forecasting

Short-term load forecasting (STLF) is of great importance for control and scheduling of electrical power systems. The uncertainty of power systems increases due to the random nature of climate and the penetration of the renewable energies such as wind and solar power. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in datasets. To quantify these potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for construction of prediction intervals (PIs). A newly proposed method, called lower upper bound estimation (LUBE), is applied to develop PIs using NN models. The primary multi-objective problem is firstly transformed into a constrained single-objective problem. This new problem formulation is closer to the original problem and has fewer parameters than the cost function. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Two case studies from Singapore and New South Wales (Australia) historical load datasets are used to validate the PSO-based LUBE method. Demonstrated results show that the proposed method can construct high quality PIs for load forecasting applications.

Rationale for the use of DC microgrids: feasibility, efficiency and protection analysis

Electrical power systems are undergoing highly significant changes in their structures. The emergence of renewable energy units in the power generation sector, the use of high-voltage DC in the power transmission sector, and the prevalence of islanded or integrated microgrids in the distribution sector are the strongest evidence supporting this claim. These changes are mostly the consequences of the increasing energy demand rate, climate change, and environmental challenges, as well as the high investment and maintenance cost of the previous structures. Considering these new conditions and according to the recent development in DC/DC conversion topologies and control techniques, different studies have been conducted on how and why DC microgrids outperform AC microgrids. This study discusses the feasibility of the DC microgrid system according to recent developments in power systems. The efficiency and power loss reduction in DC distribution systems are then analyzed, some of the common strategies and devices for protection systems in such networks are reviewed, and the possible and existing challenges in developing the DC microgrids are highlighted. The mathematical calculations and theories for this evaluation are presented to determine the reliable justification for selecting the appropriate microgrid systems.

Nonlinear adaptive excitation controller design for multimachine power systems

This paper presents a nonlinear adaptive excitation control scheme to enhance the dynamic stability of multimachine power systems. The proposed controller is designed based on the adaptive backstepping technique where the mechanical power input to the generators and the damping coefficient of each generator are considered as unknown. These unknown quantities are estimated through the adaption laws. The adaption laws are obtained from the formulation of Lyapunov functions which guarantee the convergence of different physical quantities of generators such as the relative speed, terminal voltage, and electrical power output. The proposed scheme is evaluated by applying a three-phase short-circuit fault at one of the key transmission lines in an 11-bus test power system and compared with an existing backstepping controller and conventional power system stabilizer (CPSS). Simulation results show that the proposed scheme is much more effective than existing controllers.

Power quality impacts in a typical microgrid

Microgrid (MG) power system plays an important role to fulfill reliable and secure energy supply to critical loads of communities as well as for communities in remote area. Distributed Generation (DG) sources integrated in a MG provides numerous benefits, at the same time leads to power quality issues in the MG power distribution network. Power Quality (PQ) issue arises due to the integration of an intermittent nature of Renewable Energy (RE) sources with advanced Power Electronics (PE) converter technology. Also, presence of non-linear and unbalancing loads in MG seems to affect PQ of the energy supply in power distribution network. In this paper, PQ impacts like; power variation, voltage variation, Total Harmonic Distortion (THD), and Unbalance voltage level have been analysed in Low Voltage (LV) distribution network of typical MG power system model. In this study, development of MG model and PQ impact analysis through simulation has been done in PSS-Sincal software environment. Analysis results from the study can be used as a guideline for developing a real and independent MG power system with improved PQ conditions.