On Stochastic-User-Equilibrium-Based Day-to-Day Dynamics

Researchers have proposed many different concepts and models to study day-to-day dynamics. Some models explicitly model travelers’ perceiving and learning on travel costs, and some other models do not explicitly consider the travel cost perception but instead formulate the dynamics of flows as the functions of flows and measured travel costs (which are determined by flows). This paper investigates the interconnection between these two types of day-to-day models, in particular, those models whose fixed points are a stochastic user equilibrium. Specifically, a widely used day-to-day model that combines exponential-smoothing learning and logit stochastic network loading (called the logit-ESL model in this paper) is proved to be equivalent to a model based purely on flows, which is the logit-based extension of the first-in-first-out dynamic of Jin [Jin W (2007) A dynamical system model of the traffic assignment problem. Transportation Res. Part B Methodological 41(1):32–48]. Via this equivalent form, the logit-ESL model is proved to be globally stable under nonseparable and monotone travel cost functions. Moreover, the model of Cantarella and Cascetta is shown to be equivalent to a second-order dynamic incorporating purely flows and is proved to be globally stable under separable link cost functions [Cantarella GE, Cascetta E (1995) Dynamic processes and equilibrium in transportation networks: Towards a unifying theory. Transportation Sci. 29(4):305–329]. Further, other discrete choice models, such as C-logit, path-size logit, and weibit, are introduced into the logit-ESL model, leading to several new day-to-day models, which are also proved to be globally stable under different conditions.

A Reduced Electrically-Equivalent Model of the IEEE European Low Voltage Test Feeder

<div>This letter presents a reduced, electrically equivalent model of the IEEE European Low Voltage Test Feeder for use in distribution network studies. The original test feeder is made up of 906 buses, of which only 55 have loads connected. This work proposes an equivalent 116 bus network which accurately represents all of the characteristics of the original test feeder, but significantly reduces the computational effort required when applied in a range of distribution system applications. The model reduction technique applied is explained in detail, and the performance of the modified network is tested under a wide range of network loading conditions. The analysis in this letter demonstrates that the modified 116 bus network produces identical results with 80% less computation time when compared to the original 906 bus network. The full data set for the modified network is provided on IEEE Dataport. Available: https://dx.doi.org/10.21227/0d2n-j565.</div>

A Reduced Electrically-Equivalent Model of the IEEE European Low Voltage Test Feeder

<div>This letter presents a reduced, electrically equivalent model of the IEEE European Low Voltage Test Feeder for use in distribution network studies. The original test feeder is made up of 906 buses, of which only 55 have loads connected. This work proposes an equivalent 116 bus network which accurately represents all of the characteristics of the original test feeder, but significantly reduces the computational effort required when applied in a range of distribution system applications. The model reduction technique applied is explained in detail, and the performance of the modified network is tested under a wide range of network loading conditions. The analysis in this letter demonstrates that the modified 116 bus network produces identical results with 80% less computation time when compared to the original 906 bus network. The full data set for the modified network is provided on IEEE Dataport. Available: https://dx.doi.org/10.21227/0d2n-j565.</div>

Cellular Traffic Prediction Based on an Intelligent Model

The evolution of cellular technology development has led to explosive growth in cellular network traffic. Accurate time-series models to predict cellular mobile traffic have become very important for increasing the quality of service (QoS) with a network. The modelling and forecasting of cellular network loading play an important role in achieving the greatest favourable resource allocation by convenient bandwidth provisioning and simultaneously preserve the highest network utilization. The novelty of the proposed research is to develop a model that can help intelligently predict load traffic in a cellular network. In this paper, a model that combines single-exponential smoothing with long short-term memory (SES-LSTM) is proposed to predict cellular traffic. A min-max normalization model was used to scale the network loading. The single-exponential smoothing method was applied to adjust the volumes of network traffic, due to network traffic being very complex and having different forms. The output from a single-exponential model was processed by using an LSTM model to predict the network load. The intelligent system was evaluated by using real cellular network traffic that had been collected in a kaggle dataset. The results of the experiment revealed that the proposed method had superior accuracy, achieving R-square metric values of 88.21%, 92.20%, and 89.81% for three one-month time intervals, respectively. It was observed that the prediction values were very close to the observations. A comparison of the prediction results between the existing LSTM model and our proposed system is presented. The proposed system achieved superior performance for predicting cellular network traffic.

Computational Methods for Calculating Multimodal Multiclass Traffic Network Equilibrium: Simulation Benchmark on a Large-Scale Test Case

This study reviews existing computational methods to calculate simulation-based dynamic network equilibrium. We consider a trip-based multimodal approach for the dynamic network loading. Mode and path choices are carried out at the same level; therefore, travel times depend on the travel path and the mode attributes of travelers. This study develops a multiclass model with several parameters per class. Two different categories of algorithms (heuristic and metaheuristic) are considered in order to solve the discrete dynamic traffic assignment (DTA) problem. Finally, we analyze the equilibrium in a large-scale multimodal DTA test case (Lyon 6th + Villeurbanne) in order to investigate the performance of different optimization approaches to solve trip-based DTA. The results show that, in a multimodal and heterogeneous setting, the metaheuristic methods provide better solutions than the heuristic methods in terms of optimality and computation time. These improvements are even more significant than in a homogeneous setting.

Comparison of Different References When Assessing PV HC in Distribution Networks

The burgeoning photovoltaics’ (PVs) penetration in the low voltage distribution networks can cause operational bottlenecks if the PV integration exceeds the threshold known as hosting capacity (HC). There has been no common consensus on defining HC, and its numerical value varies depending on the reference used. Therefore, this article compared the HC values of three types of networks in rural, suburban, and urban regions for different HC reference definitions. The comparison was made under balanced and unbalanced PV deployment scenarios and also for two different network loading conditions. A Monte Carlo (MC) simulation approach was utilized to consider the intermittency of PV power and varying loading conditions. The stochastic analysis of the networks was implemented by carrying out a large number of simulation scenarios, which led towards the determination of the maximum amount of PV generation in each network case.

A Choice of Representative Sections for the Estimation of the Transport Network Loading

The problem of a choice of representative sections for transport network loading management is considered in the following article. To solve the problem, the use of Principal component analysis and the procedures of cluster analysis are offered. The example of the choice of representative sections at network traffic control is presented.