Local Freeway Ramp Metering using Self-Adjusted Fuzzy Controller

A self-adjusted fuzzy local ramp metering strategy is proposed to keep the mainline traffic state and the on-ramp queue length at reasonable levels. The fuzzy ramp metering strategy (FRMS) takes the following variables as inputs: error between desired density and measured density, change-in-error and on-ramp queue length. On-ramp metering flow is decided by these variables. It is difficult to construct fuzzy rules for a three-dimension inputs fuzzy controller based on expert knowledge, so the proposed FRMS generates fuzzy control rules by an analytic expression with correction factors. The correction factors reflect the weights upon linguistic variables of inputs and can be regulated according to actual traffic state of mainline and on-ramp. The proposed FRMS not only simplifies the process of rules definition for a multi-dimension fuzzy controller, but also has function of self-adjusted control rules. To examine the proposed FRMS, a freeway stretch in Los Angeles is simulated with distributed models. The proposed FRMS is also compared with an existing T-S FRMS and PI-ALINEA in the simulation experiments which cover different on-ramp inflow scenarios. Simulation results show the proposed FRMS provides improved adaptation to various scenarios and superiority in striking a balance between the mainline and on-ramp performances

Workshop on Fuzzy Control Systems and Space Station Applications

The Workshop on Fuzzy Control Systems and Space Station Applications was held on 14-15 Nov. 1990. The workshop was co-sponsored by McDonnell Douglas Space Systems Company and NASA Ames Research Center. Proceedings of the workshop are presented

Increasing the capacity of distributed generation in electricity networks by intelligent generator control

The rise of environmental awareness as well as the unstable global fossil fuel market has brought about government initiatives to increase electricity generation from renewable energy sources. These resources tend to be geographically and electrically remote from load centres. Consequently many Distributed Generators (DGs) are expected to be connected to the existing Distribution Networks (DNs), which have high impedance and low X/R ratios. Intermittence and unpredictability of the various types of renewable energy sources can be of time scales of days (hydro) down to seconds (wind, wave). As the time scale becomes smaller, the output of the DG becomes more difficult to accommodate in the DN. With the DGs operating in constant power factor mode, intermittence of the output of the generator combined with the high impedance and low X/R ratios of the DN will cause voltage variations above the statutory limits for quality of supply. This is traditionally mitigated by accepting increased operation of automated network control or network reinforcement. However, due to the distributed nature of RES, automating or reinforcing the DN can be expensive and difficult solutions to implement. The Thesis proposed was that new methods of controlling DG voltage could enable the connection of increased capacities of plant to existing DNs without the need for network management or reinforcement. The work reported here discusses the implications of the increasing capacity of DG in rural distribution networks on steady-state voltage profiles. Two methods of voltage compensation are proposed. The first is a deterministic system that uses a set of rules to intelligently switch between voltage and power factor control modes. This new control algorithm is shown to be able to respond well to slow voltage variations due to load or generation changes. The second method is a fuzzy inference system that adjusts the setpoint of the power factor controller in response to the local voltage. This system can be set to respond to any steady-state voltage variations that will be experienced. Further, control of real power is developed as a supplementary means for voltage regulation in weak rural networks. The algorithms developed in the study are shown to operate with any synchronous or asynchronous generation wherein real and reactive power can be separately controlled. Extensive simulations of typical and real rural systems using synchronous generators (small hydro) and doubly-fed induction generators (wind turbines) have verified that the proposed approaches improve the voltage profile of the distribution network. This demonstrated that the original Thesis was true and that the techniques proposed allow wider operation of greater capacities of DG within the statutory voltage limits

An overview of measurement standards for power quality

Received: December 7th, 2020 ; Accepted: April 7th, 2021 ; Published: May 13th, 2021 ; Correspondence: [email protected] Quality (PQ) is a vital aspect of electrical power systems, which cannot be neglected anymore, as an ample PQ guarantees the essential compatibility between consumer equipment and the electricity network. The analysis of electrical parameters related to distributing electricity is recognized as a complex engineering problem. It remains a critical task to maintain and improve PQ in modern evolving networks as the overall system performance highly depends on it. Future smart grids will also require a further increase in PQ levels in terms of observability, affordability, data exchange, flexibility, and net metering, thus making the network much more complex as it will be featuring a large amount of variable renewable-based distributed generation. This will further require the need for the introduction of novel, efficient and intelligent monitoring, control, and communication systems with various demand manageable resources. In this paper, a review and comparisons have been made for different IEEE and IEC measurement standards that are used for PQ with a specific focus on harmonic distortion as it is one of the most important parameters in PQ and some guidelines have been suggested for future electricity networks

Investigation of Impact of Contingencies on Power Plant and Transmission Lines

Contingency analysis are widely applied to predict the effect of outages in power systems, like tripping of equipment in power plants and transmission lines. Using off line analysis to predict the effect of individual contingency is a tedious task on power system containing large number of components. Practically, only selected contingencies will lead to severe conditions in power system, like violation of voltage and active power flow limits. Simultaneously, the value of active power flow before and after severe transmission and power plant contingencies was analysed using Genetic Eigenvalue Analysis Technique. This was achieved by simulating the Simulink of Nigerian 330KV 48 bus power system using m-file programme in MATLAB environment.The result of the simulation for the power flow solution for transmission line outage contingencies shows that the voltage trajectory at bus 11 stood at 0.3934 p.u, at bus 15 is0.4986 p.u, and bus of 23 is 0.4647 p.u while for the contingencies on power plant, there voltage trajectories stood at 0.2342 p.u for bus 11, 0.3987 p.u for bus 23. The result shows that the impact on power plant is higher than that of transmission line by 40%, 20%, 14%for sampled buses 11, 15, and 23 respectively. Keywords: Power Stability- Genetic Eigenvalue, Load flow DOI: 10.7176/JETP/11-1-04 Publication date: January 31st 202

A comparative study of time-series forecasting applied to stock market price

This thesis is a comparative study on forecasting New Zealand stock market daily closing prices by treating them as a time series. The methods used here are Box and Jenkins autoregressive integrated moving average (ARIMA) model, Bayesian dynamic linear model and Fuzzy neural networks. These methods are compared by using simple trading strategies, resulting in potentially profitable forecasting especially through the fuzzy neural networks. In addition, the final part of this thesis are summary and comments on different methods that have been used by researchers to predict the stock prices

Power Management Strategy of a Fuel Cell Hybrid Electric Vehicle with Integrated Ultra-Capacitor with Driving Pattern Recognition

abstract: The greenhouse gases in the atmosphere have reached a highest level due to high number of vehicles. A Fuel Cell Hybrid Electric Vehicle (FCHEV) has zero greenhouse gas emissions compared to conventional ICE vehicles or Hybrid Electric Vehicles and hence is a better alternative. All Electric Vehicle (AEVs) have longer charging time which is unfavorable. A fully charged battery gives less range compared to a FCHEV with a full hydrogen tank. So FCHEV has an advantage of a quick fuel up and more mileage than AEVs. A Proton Electron Membrane Fuel Cell (PEMFC) is the commonly used kind of fuel cell vehicles but it possesses slow current dynamics and hence not suitable to be the sole power source in a vehicle. Therefore, improving the transient power capabilities of fuel cell to satisfy the road load demand is critical. This research studies integration of Ultra-Capacitor (UC) to FCHEV. The objective is to analyze the effect of integrating UCs on the transient response of FCHEV powertrain. UCs has higher power density which can overcome slow dynamics of fuel cell. A power management strategy utilizing peak power shaving strategy is implemented. The goal is to decrease power load on batteries and operate fuel cell stack in it’s most efficient region. Complete model to simulate the physical behavior of UC-Integrated FCHEV (UC-FCHEV) is developed using Matlab/SIMULINK. The fuel cell polarization curve is utilized to devise operating points of the fuel cell to maintain its operation at most efficient region. Results show reduction of hydrogen consumption in aggressive US06 drive cycle from 0.29 kg per drive cycle to 0.12 kg. The maximum charge/discharge battery current was reduced from 286 amperes to 110 amperes in US06 drive cycle. Results for the FUDS drive cycle show a reduction in fuel consumption from 0.18 kg to 0.05 kg in one drive cycle. This reduction in current increases the life of the battery since its protected from overcurrent. The SOC profile of the battery also shows that the battery is not discharged to its minimum threshold which increasing the health of the battery based on number of charge/discharge cycles.Dissertation/ThesisMasters Thesis Mechanical Engineering 201

An overview of decision table literature.

The present report contains an overview of the literature on decision tables since its origin. The goal is to analyze the dissemination of decision tables in different areas of knowledge, countries and languages, especially showing these that present the most interest on decision table use. In the first part a description of the scope of the overview is given. Next, the classification results by topic are explained. An abstract and some keywords are included for each reference, normally provided by the authors. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. Other examined topics are the theoretical or practical feature of each document, as well as its origin country and language. Finally, the main body of the paper consists of the ordered list of publications with abstract, classification and comments.