Sequence- and time-dependent maintenance scheduling in twice re-entrant flow shops

Industrial and academic interest converge on scheduling flow shops with sequence- and time-dependent maintenance. We posit that anticipatory, integrated scheduling of operational and maintenance tasks leads to superior performance to purely 'wait-then-fix' handling of the maintenance tasks. Motivated by an industrial problem with (sequence...

Scenario-Based MPC for Real-Time Passenger-Centric Timetable Scheduling of Urban Rail Transit Networks

Effective timetable scheduling strategies are essential for passenger satisfaction in urban rail transit networks. Most existing passenger-centric timetable scheduling approaches generate a timetable according to deterministic passenger origin-destination (OD) demands. As passenger OD demands in urban rail transit networks generally show a...

Real-Time Train Scheduling With Uncertain Passenger Flows: A Scenario-Based Distributed Model Predictive Control Approach

Real-time train scheduling is essential for passenger satisfaction in urban rail transit networks. This paper focuses on real-time train scheduling for urban rail transit networks considering uncertain time-dependent passenger origin-destination demands. First, a macroscopic passenger flow model we proposed before is extended to include...

Robustness Analysis of Platoon Control for Mixed Types of Vehicles

Currently, with the development of driving technologies, driverless vehicles gradually are becoming more and more available. Therefore, there would be a long period of time during which self-driving vehicles and human-driven vehicles coexist. However, for a mixed platoon, it is hard to control the formation due to the existence of the manual...

A traffic responsive control framework for signalized junctions based on hybrid traffic flow representation

The paper proposes a traffic responsive control framework based on a Model Predictive Control (MPC) approach. The framework focuses on a centralized method, which can simultaneously compute the network decision variables (i.e., the green timings at each junction and the offset of the traffic light plans of the network). Furthermore, the...

Short-Term Traffic Flow Prediction Based on the Efficient Hinging Hyperplanes Neural Network

Traffic flow (TF) prediction is an important and yet a challenging task in transportation systems, since the TF involves high nonlinearities and is affected by many elements. Recently, neural networks have attracted much attention for TF prediction, but they are commonly black boxes with complex architectures and difficult to be interpreted,...

A two-step distribution system state estimator with grid constraints and mixed measurements

In this paper we consider the problem of State Estimation (SE) in large-scale, 3-phase coupled, unbalanced distribution systems. More specifically, we address the problem of including mixed real-time measurements, synchronized and unsynchronized, from phasor measurement units and smart meters, into existing SE solutions. We propose a...

Linking water and energy objectives in lowland areas through the application of model predictive control

Unlike mountainous areas, lowland areas have limited potential to generate energy from water flows. Instead, for water systems in lowland areas that continuously need to pump water out of the system, the focus should be set to saving energy in the present water management. This paper gives an introduction into possibilities to manage water...

Model-based predictive control applied to multi-carrier energy systems

The optimal operation of an integrated electricity and natural gas infrastructure is investigated. The couplings between the electricity system and the gas system are modeled by so-called energy hubs, which represent the interface between the loads on the one hand and the transmission infrastructures on the other. To increase reliability and...

Multi-area control of overlapping areas in power systems for FACTS control

As power systems generally are large interconnected systems controlled by several parties, centralized optimal power flow (OPF) control taking the entire grid into account is often not feasible. To use optimal control in power systems nevertheless, the overall system is decomposed into areas with associated subproblems, which are solved in an...