Improving energy sustainability in electrical vehicle energy networks and internet of things
Başlık çevirisi mevcut değil.
- Tez No: 402683
- Danışmanlar: DR. BING WANG
- Tez Türü: Doktora
- Konular: Enerji, Energy
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2015
- Dil: İngilizce
- Üniversite: The University of Connecticut
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 102
Özet
Özet yok.
Özet (Çeviri)
Energy sustainability is a pressing issue facing the modern society. The twin pillars of sustainable energy are renewable energy and energy efficiency. In this dissertation, we propose novel architectures and approaches to improve energy sustainability in two application domains: transportation and the Internet of Things. Transportation is one of the major sources of energy consumption and environmental pollution. Plug-in hybrid electric vehicles (PHEVs) present many opportunities in improving energy efficiency and reducing greenhouse gas emissions. In addition, with batteries and built-in mobility, PHEVs can form a mobile and distributed energy network, where energy can be conveniently transported from place to place. In the first part of this dissertation, we investigate how to optimally distribute renewable energy in a distributed PHEV energy network under two system architectures. The first architecture assumes that each charge station is equipped with energy storage to serve as an energy exchange point. Some PHEVs can be charged by renewable energy sources and discharge energy at a charge station. Other PHEVs passing by the charge station can withdraw energy from the charge station, and therefore indirectly use the energy from the renewable energy sources. The second architecture assumes that the charge stations do not have energy storage. Instead, they are connected using underground cables to a central energy storage (CES), which has a limited capacity and is charged by renewable energy sources. PHEVs can withdraw/deposit energy from/to the CES (and thus indirectly use renewable energy) through the charge stations. We formulate and solve the optimal renewable energy transfer problem under each of the two system architectures. The two optimization problems share the same objective function to maximize the total amount of renewable energy used by the PHEVs but are subject to di↵erent constraints derived from the system architectures. Simulation results using the data set from the Manhattan city bus system demonstrate that our approaches significantly outperform baseline schemes and provide e↵ective ways to share renewable energy in PHEV energy network and thus improve energy sustainability. We further study the energy sustainability problem in a broader application domain - Internet of Things (IoT). IoT is the network of things that enables devices to exchange data with manufacturers, operators or other devices. It is expected that there will be nearly 26 billion devices on the IoT by 2020. Energy efficiency is a critical issue in the IoT. In the second part of the dissertation, we investigate energyefficient packet transmission in the IoT. Specifically, we consider a mobile network with group-based encountering. The optimization goal is to minimize the delay for transmitting a set of packets from a source to a destination while limiting the energy consumption. The challenge lies in how to schedule packet transmission among a group of nodes that meet each other so that information carried by the di↵erent nodes can be exchanged e↵ectively. We first assume that node encountering is known beforehand, and develop a max-flow based algorithm that obtains the optimal solution. While the assumption is clearly unrealistic, the optimal solution is useful to quantify the e↵ectiveness of di↵erent heuristic algorithms. Specifically, we propose two network coding based heuristic algorithms. One algorithm uses full signaling where nodes exchange their coefficient matrix with each other while the other incurs much less signaling overhead in that nodes only exchange rank information when meeting each other. Both algorithms use a token-based technique to limit the total number of transmissions, and only incur signaling at the beginning of a group meeting. Simulation results demonstrate that both algorithms achieve delays close to the minimum latency for moderate number of tokens. They present di↵erent tradeo↵s in the number of transmissions and the signaling overhead.
Benzer Tezler
- Building energy consumption modeling and prediction using data-driven models
Bina enerji tüketimi modelleme ve tahmini için veri odakli modeller
SODABA ROGH
Yüksek Lisans
İngilizce
2024
Elektrik ve Elektronik MühendisliğiOSTİM TEKNİK ÜNİVERSİTESİElektrik ve Elektronik Mühendisliği Ana Bilim Dalı
PROF. DR. İSMAİL AVCIBAŞ
- Araç üstü katlanır bomlu vinçlerin moment kontrol sistemlerininiyileştirilmesi
Truck mounted knuckle boom Crane's moment control systemsenhancement
YASİN BİRER
Yüksek Lisans
Türkçe
2023
Elektrik ve Elektronik MühendisliğiNecmettin Erbakan ÜniversitesiElektrik-Elektronik Mühendisliği Ana Bilim Dalı
DR. ÖĞR. ÜYESİ ALİ OSMAN ÖZKAN
- Organize sanayi bölgelerinde endüstriyel simbiyozun enerji verimliliğine etkisi
Effects of industrial symbiosis on energy efficiency in organized industrial zones
ARZU MÜYESSEROĞLU
Yüksek Lisans
Türkçe
2023
Endüstri ve Endüstri Mühendisliğiİstanbul Teknik ÜniversitesiEnerji Bilim ve Teknoloji Ana Bilim Dalı
PROF. DR. SERMİN ONAYGİL
- Konut binalarındaki kurulu kapasite fazlası ve yenilenebilir enerji kaynaklarının entegrasyonu ile dinamik yük yönetiminin şarj istasyonu boyutlandırılmasına etkileri
Efects of dynamic load management on sizing of charging operations with the integration of surplus installed capacity in residential building and renewable energy
ÖZCAN AKBIYIK
Yüksek Lisans
Türkçe
2024
Enerjiİstanbul Teknik ÜniversitesiEnerji Bilim ve Teknoloji Ana Bilim Dalı
PROF. DR. ÖNDER GÜLER
- Elektrikli araçlar için yüksek doğrulukla şarj kestirimi sunan batarya yönetim sistemi tasarımı
Design of battery managemenet system providing high accuracy state of charge estimation for electric vehicles
MUSTAFA MERT SERİNBAŞ
Yüksek Lisans
Türkçe
2023
Elektrik ve Elektronik Mühendisliğiİstanbul Teknik ÜniversitesiElektrik Mühendisliği Ana Bilim Dalı
DR. ÖĞR. ÜYESİ MEHMET ONUR GÜLBAHÇE