Back-to-back Converter Control of Grid-connected Wind Turbine to Mitigate Voltage Drop Caused by Faults

Power electronic converters enable wind turbines, operating at variable speed, to generate electricity more efficiently. Among variable speed operating turbine generators, permanent magnetic synchronous generator (PMSG) has got more attentions due to low cost and maintenance requirements. In addition, the converter in a wind turbine with PMSG decouples the turbine from the power grid, which favors them for grid codes. In this paper, the performance of back-to-back (B2B) converter control of a wind turbine system with PMSG is investigated on a faulty grid. The switching strategy of the grid side converter is designed to improve voltage drop caused by the fault in the grid while the maximum available active power of wind turbine system is injected to the grid and the DC link voltage in the converter is regulated. The methodology of the converter control is elaborated in details and its performance on a sample faulty grid is assessed through simulation

A proposed mathematical model for closed-loop network configuration based on product life cycle

Products may be returned over their life cycle. Industrial experiences show that there are three main return–recovery pairs. Commercial returns are repaired. End-of-use returns often are remanufactured. In addition, end-of-life returns are recycled. However, up to now, no optimization model is proposed for closed-loop configuration based on three return–recovery pairs. The repaired and remanufactured products can be sold in the same or secondary market. In this paper, we design and configure a general closed-loop supply chain network based on product life cycle. The network includes a manufacturer, collection, repair, disassembly, recycling, and disposal sites. The returned products are collected in a collection site. Commercial returns go to a repair site. End-of-use and end-of-life returns are disassembled. Then, end-of-life returns are recycled. The manufacturer uses recycled and end-of-use parts and new parts to manufacture new products. The new parts are purchased from external suppliers. A mixed-integer linear programming model is proposed to configure the network. The objective is to maximize profit by determining quantity of parts and products in the network. We also extend the model for the condition that the remanufactured products are sent to the secondary market. The mathematical models are validated through computational testing and sensitivity analysis

A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return

A closed-loop supply chain (CLSC) network consists of both forward and reverse supply chains. In this paper, a CLSC network is investigated which includes multiple plants, collection centres, demand markets, and products. To this aim, a mixed-integer linear programming model is proposed that minimizes the total cost. Besides, two test problems are examined. The model is extended to consider environmental factors by weighed sums and ε-constraint methods. In addition, we investigate the impact of demand and return uncertainties on the network configuration by stochastic programming (scenario-based). Computational results show that the model can handle demand and return uncertainties, simultaneously

A three-stage model for closed-loop supply chain configuration under uncertainty

In this paper, a general closed-loop supply chain (CLSC) network is configured which consists of multiple customers, parts, products, suppliers, remanufacturing subcontractors, and refurbishing sites. We propose a three-stage model including evaluation, network configuration, and selection and order allocation. In the first stage, suppliers, remanufacturing subcontractors, and refurbishing sites are evaluated based on a new quality function deployment (QFD) model. The proposed QFD model determines the relationship between customer requirements, part requirements, and process requirements. In addition, the fuzzy sets theory is utilised to overcome the uncertainty in the decision-making process. In the second stage, the closed-loop supply chain network is configured by a stochastic mixed-integer nonlinear programming model. It is supposed that demand is an uncertain parameter. Finally in the third stage, suppliers, remanufacturing subcontractors, and refurbishing sites are selected and order allocation is determined. To this end, a multi-objective mixed-integer linear programming model is presented. An illustrative example is conducted to show the process. The main novel innovation of the proposed model is to consider the CLSC network configuration and selection process simultaneously, under uncertain demand and in an uncertain decision-making environment

Challenges and Solutions for Intrusion Detection in Wireless Mesh Networks

The problem of intrusion detection in wireless mesh networks (WMN) is challenging, primarily because of lack of single vantage points where traffic can be analyzed and the limited resources available to participating nodes. Although the problem has received some attention from the research community, little is known about the tradeoffs among different objectives, such as high network performance, low energy consumption, and high security effectiveness. In this research, we show how accurate intrusion detection can be achieved in such resource constrained environments. The major challenges that hinder the performance of intrusion detection systems (IDS) in WMN are resources (e.g., energy, processing, and storage capabilities) accompanied by the adhoc-dynamic communication flows. In light of these challenges, we classify the proposed solutions into four classes: 1) Resourceless Traffic Aware (RL-TW) IDS, 2) Resourceless Traffic Agnostic (RLTG) IDS, 3) Resourceful Traffic Agnostic (RF-TG) IDS, and 4) Resourceful Traffic Aware (RF-TW) IDS. To achieve a desirable level of intrusion detection in WMN, we propose a research program encompassing five thrusts. First we show how traffic-awareness helps IDS solutions achieving high detection rates in resource-constrained WMN. Next, we propose two RL-TG (i.e., cooperative and non-cooperative) IDS solutions that can optimally monitor the entire WMN traffic without relying on WMN traffic information. The third (RF-TG) and fourth (RF-TW) IDS solutions propose energy-efficient monitoring mechanisms for intrusion detection in battery-powered WMN for traffic-agnostic and traffic-aware scenarios, respectively. We then investigate the Attack and Fault Tolerance of our proposed solutions and finally enumerate potential improvements and future works for our proposed solutions

Analysis of Transportation Modes by Evaluating SWOT Factors and Pairwise Comparisons: A Case Study

Cape Breton Island is one of the most beautiful islands in the World. The island itself has a unique geography and is located in Nova Scotia, Canada. This chapter introduces and summarizes the current transportation modes in Cape Breton Island. The transportation modes discussed include air, rail, water, truck, and intermodal modes. A SWOT matrix is applied to identify the strengths, weaknesses, opportunities, and threats related to the different transportation modes in Cape Breton Island. Then, the factors are evaluated and ranked based on pairwise comparisons in analytic hierarchy process (AHP) method, and the best strategies are defined. This research provides a unique and multidisciplinary overview of transportation modes in the region that is necessary for future quantitative investigations. Furthermore, it introduces the steps to analyze transportation modes of other areas and regions

Design and Optimization of Closed-Loop Supply Chain Management

Because of cost and environmental concerns, reverse supply chain (RSC) has received a lot of attention. RSC is defined as the activities of the collection and recovery of product returns in supply chain management. The integration of forward supply chain (FSC) and RSC results in a closed-loop supply chain (CLSC). In this dissertation, FSC, RSC, and CLSC are introduced. Then, the research objectives are mentioned. The objective of this dissertation is to develop effective approaches to support closed-loop supply chain configurations and analyses, especially develop methodologies to examine impacts of multi-objectives, and uncertainty on CLSC. In Chapter 2, literature of CLSC configuration is reviewed including deterministic and uncertain models. In addition, gaps in the literature are mentioned. In Chapter 3, a facility location model is examined. After problem definition, a mixed-integer linear programming model is proposed. Then, the model is developed to consider multi-objectives under uncertain demand and return. In Chapter 4, a CLSC network is examined. In this chapter, an integrated model for CLSC configuration and supplier selection is proposed and a solution approach is developed for the multi-objective model. A numerical example is used to validate the model. In Chapter 5, a three stage model for closed-loop supply chain configuration is proposed based on a general network. It is supposed that demand is an uncertain parameter. Besides, an illustrative example is applied to show the three-stage model. In addition, managerial insights are discussed in this chapter. In Chapter 6, a mixed-integer linear programming model is proposed to configure a CLSC network. The network has been designed based on product life cycle. The objective is to maximize profit by determining quantity of parts and products in the network. We also extend the model for the condition that the remanufactured products are sent to the secondary market. Finally in Chapter 7, conclusions and future works are provided

Selection of Food Items for Diet Problem Using a Multi-objective Approach under Uncertainty

It is a problem that concerns us all: what should we eat on a day-to-day basis to meet our health goals? Scientists have been utilizing mathematical programming to answer this question. Through the use of operations research techniques, it is possible to find a list of foods that, in a certain quantity, can provide all nutrient recommendations in a day. In this research, a multi-objective programming model is provided to determine the selected food items for a diet problem. Two solution approaches are developed to solve this problem including weighted-sums and ε-constraint methods. Two sources of uncertainty have been considered in the model. To handle these sources, a scenario-based approach is utilized. The application of this model is shown using a case study in Canada. Using the proposed model and the solution approaches, the best food items can be selected and purchased to minimize the total cost and maximize health