Modelling the Choice of Car Parks in Urban Areas and Managing the Demand for Parking.

Car parks are an essential piece of infrastructure associated with the road networks, yet commonly available traffic assignment models do not to explicitly integrate them into the modelling process. This research attempts to integrate the choice of car parks in urban areas into the travellers’ route choice and incorporates both the route and car park choice in a joint modelling framework of traffic assignment based on equilibrium approach. This paper illustrates the implementation of the model in a commonly used standard suite of traffic assignment software. The proposed method considers multiple user classes - commuter and non-commuter flows, and involves modelling the demand for short stay and long stay car parks over multiple departure periods. A special search time delay function has been developed to represent the disutility in searching for a place in a car park, which is integrated further into the function of generalised cost of travel. This technique has been successfully applied to study the choice of car parks in the case of a simple hypothetical network. Another larger numerical example illustrates the case of managing the demand between two car parks in Leeds, England

Modeling and Real-Time Scheduling of DC Platform Supply Vessel for Fuel Efficient Operation

DC marine architecture integrated with variable speed diesel generators (DGs) has garnered the attention of the researchers primarily because of its ability to deliver fuel efficient operation. This paper aims in modeling and to autonomously perform real-time load scheduling of dc platform supply vessel (PSV) with an objective to minimize specific fuel oil consumption (SFOC) for better fuel efficiency. Focus has been on the modeling of various components and control routines, which are envisaged to be an integral part of dc PSVs. Integration with photovoltaic-based energy storage system (ESS) has been considered as an option to cater for the short time load transients. In this context, this paper proposes a real-time transient simulation scheme, which comprises of optimized generation scheduling of generators and ESS using dc optimal power flow algorithm. This framework considers real dynamics of dc PSV during various marine operations with possible contingency scenarios, such as outage of generation systems, abrupt load changes, and unavailability of ESS. The proposed modeling and control routines with real-time transient simulation scheme have been validated utilizing the real-time marine simulation platform. The results indicate that the coordinated treatment of renewable based ESS with DGs operating with optimized speed yields better fuel savings. This has been observed in improved SFOC operating trajectory for critical marine missions. Furthermore, SFOC minimization at multiple suboptimal points with its treatment in the real-time marine system is also highlighted

A method to assess demand growth vulnerability of travel times on road network links

Many national governments around the world have turned their recent focus to monitoring the actual reliability of their road networks. In parallel there have been major research efforts aimed at developing modelling approaches for predicting the potential vulnerability of such networks, and in forecasting the future impact of any mitigating actions. In practice-whether monitoring the past or planning for the future-a confounding factor may arise, namely the potential for systematic growth in demand over a period of years. As this growth occurs the networks will operate in a regime closer to capacity, in which they are more sensitive to any variation in flow or capacity. Such growth will be partially an explanation for trends observed in historic data, and it will have an impact in forecasting too, where we can interpret this as implying that the networks are vulnerable to demand growth. This fact is not reflected in current vulnerability methods which focus almost exclusively on vulnerability to loss in capacity. In the paper, a simple, moment-based method is developed to separate out this effect of demand growth on the distribution of travel times on a network link, the aim being to develop a simple, tractable, analytic method for medium-term planning applications. Thus the impact of demand growth on the mean, variance and skewness in travel times may be isolated. For given critical changes in these summary measures, we are thus able to identify what (location-specific) level of demand growth would cause these critical values to be exceeded, and this level is referred to as Demand Growth Reliability Vulnerability (DGRV). Computing the DGRV index for each link of a network also allows the planner to identify the most vulnerable locations, in terms of their ability to accommodate growth in demand. Numerical examples are used to illustrate the principles and computation of the DGRV measure

Advances in distribution system reliability assessment

Traditionally, reliability of power systems has been an important measure of system performance and a key factor in system planning. Recently, the large-scale changes in the regulations governing the power industry have lead to a growing emphasis on distribution system reliability. Further, the shift towards a more technical and computerized society requires that power supply be increasingly reliable. Advanced models and methods are needed to obtain an improved understanding of the distribution system reliability. Monte Carlo simulation is one such method that can be used to find the statistical distribution of the reliability indices. This dissertation presents a computationally efficient Monte Carlo simulation algorithm for assessing the distribution reliability indices. Several state regulatory agencies have started to prescribe minimum reliability standards to be maintained by the distribution companies. The effect of these regulations has not been fully explored. In this work, a detailed analysis of the impact of various regulatory standards on a practical distribution system is presented. Storms cause a significant fraction of the distribution customer interruptions. While the impact of wind storms on distribution system reliability has been studied earlier, the effect of lightning storms on the reliability indices is not fully understood. Momentary interruptions caused by lightning storms may severely disrupt production at automated manufacturing facilities and other sensitive loads resulting in a loss of millions of dollars per incident. An analysis of lightning storm data is presented in this dissertation along with a method for calculating the impact of lightning storms on distribution system reliability. Finally, several topics for future research are discussed

Stochastic process models for dynamic traffic assignment

This research explored the idea of unifying the deterministic and stochastic process approaches together, and developing a generalised framework of dynamic traffic assignment models to include day-to-day and within day variations in traffic flow. The framework of models is also aimed at capturing individual drivers’ adaptation of route choices based on the route costs experienced through suitable driver learning models. In this thesis, the route flows within a day in a given departure period are modelled as random variables, and their evolution over a period of time (a number of days) is modelled as stochastic processes based on the laws of probability. The interactions among the route flows from various departure periods over the network links in space and time, are modelled through dynamic link loading procedures. Stochastic processes under certain mild conditions admit a unique stationary probability distribution which can be modelled by using simulation techniques. Alternatively, the moments (e.g., mean and variance) of the equilibrium (stationary) probability distribution can also be estimated. This research has advanced the idea of estimating the properties of equilibrium probability distribution by making a particular contribution in formulating the methodology for computing the Jacobians of route travel times with respect to the route inflows in a doubly dynamic assignment context using an analytical procedure, which are necessary for estimating the variance-covariance matrices of stationary route flows. In this modelling framework, there are three modules - the first one is a day-to-day route choice model defined as a discrete time stochastic process, the second is a continuous time dynamic network loading of the route flows considering the complete spatio-temporal effects of the traffic flows that use the road links at the same time, and the third is the drivers’ learning and adjusting model based on a linear filter. The main idea of estimating the properties of stationary probability distribution in this research builds on two earlier results: firstly, when the demand is sufficiently large, the equilibrium probability distribution converges approximately to a Multivariate Normal distribution and its mean coincides with the SUE flows; secondly, the variance can be estimated by an approximation procedure. The equilibrium probability distribution can also be worked out using the commonly followed Monte Carlo simulation technique, which involves simulating the route choice process as a multinomial probability distribution over a number of days, and then summarising the properties e.g., the mean and the variance of the stationary probability distribution. This procedure though simple, is time consuming and the main difficulty lies in detecting the stationarity of the process. Based on the necessary conditions, simple and practically useable tests for identifying the stationarity of a stochastic process have been introduced. These tests involve analysing autocorrelations and computing large lag standard errors in autocorrelations. The stationary variance-covariance of route flows obtained by the variance approximation model, was compared with that computed by the simulation procedure. Overall, the variance approximation model performs satisfactorily. Variance-covariance of route flows has been found sensitive primarily to the input logit choice parameter, which defines the boundaries of the validity of the variance approximation model. Variance-covariance is also affected by the memory length with the shorter memory systems essentially producing highly variant systems. Similarly, the variance-covariance of route flows is also sensitive to the memory weight, and the lower memory weight (0 < memory weight « 1) produces the same effect as that of shorter memory systems. The Jacobians of the travel times worked out in this thesis have much wider applicability, and a few possible situations have been listed here among many others. Firstly, the optimisation based user equilibrium programs can be speeded up by defining the descent direction with the help of the Jacobians. Secondly, the Jacobians may be found very useful in defining the dynamic road user pricing problems. Finally, the sensitivity analysis of user equilibrium problems requires the computation of the Jacobians

Analysis of Drinking Water Supply System Encompassing The Catchment, The Reservoir and The Treatment Facility (A Case Study of Osman Sagar Drinking Water Supply System, Hyderabad, India)

Unregulated urban growth and unscientific approach towards source protection led to the degradation and loss of fresh water lakes in Hyderabad. Osman Sagar is one of the few lakes that still retains its fresh water status. In recent times it witnessed drastic fluctuations in its inflows resulting in reduced drinking water supply. The study emphasizes the need to improve the overall water management based on the integration of scientific assessment and appropriate management strategies