8 research outputs found

    LoRa ๋„คํŠธ์›Œํฌ์—์„œ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ์œ„ํ•œ ๋…ธ๋“œ ๊ธฐ๋ฐ˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2020. 8. ๊น€์ข…๊ถŒ.Recently, as Internet of Things (IoT) systems have increased and Wireless Sensor Network (WSN) has been expanding, studies related to them are increasing. Among them, the interest in long range communication technologies has increased. In this regard, Low Power Wide Area (LPWA) network technologies such as Long Range (LoRa), Weightless, and Sigfox have emerged. Also, various studies related to LoRa and LoRaWAN, which are available in Industrial Scientific and Medical (ISM) bands, are being conducted. In LoRa networks, the nodes are connected to the gateway by one hop to form a start topology. LoRa nodes use the transmission parameters such as Spreading Factor (SF), Transmission Power (TP), Bandwidth (BW), Coding Rate (CR), and Carrier Frequency (CF) to transmit frames. In this process, the frame losses and the collisions between frames may occur because of the channel condition and transmission timing. To alleviate this problem, LoRaWAN utilizes the ADR mechanism to select appropriate transmission parameters considering the channel condition on the node side. In addition, there is the ADR mechanism for allocating the transmission parameters on the server side. The ADR mechanisms maintain the connection between the server and the nodes, and set appropriate transmission parameters. However, these existing ADR mechanisms have some limitations. First, the server side ADR mechanism increases the overhead of the server in proportion to the transmitted frames. Second, it is difficult to quickly and efficiently respond to dynamic channel. Third, the transmission parameters selected by these ADR mechanisms may not be the optimal transmission parameters for energy efficiency. These problems cause large energy consumption of the battery-powered nodes and decrease performance when the channel condition changes dynamically. In this paper, we propose a Node-based ADR Mechanism (NbADR), which is the ADR mechanism for Class A nodes in confirmed mode to minimize the server load and maximize energy efficiency. The proposed mechanism responds quickly to the channel condition based on the downlink pattern and selects the transmission parameters for efficient energy consumption by utilizing Efficiency of Energy (EoE) metric. We analyze the efficiency of the transmission parameters selected through EoE, and conduct extensive experiments. In conclusion, NbADR is more effective in terms of energy efficiency than the existing ADR mechanisms. Additionally, NbADR guarantees throughput of LoRa networks even in dynamically changing channel environments and improves fairness between the nodes.์ตœ๊ทผ IoT ์‹œ์Šคํ…œ์ด ์ฆ๊ฐ€ํ•˜๊ณ  ๋ฌด์„  ์„ผ์„œ ๋„คํŠธ์›Œํฌ๊ฐ€ ๋„“์–ด์ง€๋ฉด์„œ ์ด์™€ ๊ด€๋ จ๋œ ์—ฐ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ ์ค‘์—์„œ๋„ ์žฅ๊ฑฐ๋ฆฌ ํ†ต์‹  ๊ธฐ์ˆ ์— ๋Œ€ํ•œ ๊ด€์‹ฌ์ด ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์ด์™€ ๊ด€๋ จํ•˜์—ฌ LoRa, Weightless, Sigfox์™€ ๊ฐ™์€ LPWA๋„คํŠธ์›Œํฌ ๊ธฐ์ˆ ๋“ค์ด ๋“ฑ์žฅํ•˜๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ, ISM ๋ฐด๋“œ์—์„œ ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ LoRa์™€ LoRaWAN ๊ด€๋ จ ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. LoRa ๋„คํŠธ์›Œํฌ์—์„œ ๋…ธ๋“œ๋“ค์€ ์Šคํƒ€ ํ† ํด๋กœ์ง€๋ฅผ ๊ตฌ์„ฑํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ฒŒ์ดํŠธ์›จ์ด์™€ 1ํ™‰์œผ๋กœ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ๋‹ค. LoRa ๋…ธ๋“œ๋“ค์€ ํ”„๋ ˆ์ž„์„ ์ „์†กํ•˜๊ธฐ ์œ„ํ•˜์—ฌ SF, TP, BW, CR, CF์™€ ๊ฐ™์€ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ๋‹ค. ์ด ๊ณผ์ •์—์„œ ์ฑ„๋„ ์ƒํƒœ์™€ ์ „์†ก ํƒ€์ด๋ฐ์œผ๋กœ ์ธํ•œ ํ”„๋ ˆ์ž„ ์†์‹ค๊ณผ ํ”„๋ ˆ์ž„ ๊ฐ„ ์ถฉ๋Œ์ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ์™„ํ™”ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ LoRaWAN์—์„œ๋Š” ๋…ธ๋“œ ์ธก์—์„œ ๋„คํŠธ์›Œํฌ ์ƒํ™ฉ์„ ๊ณ ๋ คํ•˜์—ฌ ์ ์ ˆํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ ํƒํ•˜๊ธฐ ์œ„ํ•œ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์‚ฌ์šฉํ•œ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€ ์„œ๋ฒ„ ์ธก์—์„œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ํ• ๋‹นํ•˜๋Š” ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ์กด์žฌํ•œ๋‹ค. ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค์€ ์„œ๋ฒ„์™€ ๋…ธ๋“œ์˜ ์—ฐ๊ฒฐ์„ ์œ ์ง€ํ•˜๊ณ  ์ ์ ˆํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ค์ •ํ•œ๋‹ค. ํ•˜์ง€๋งŒ ๊ธฐ์กด์˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค์€ ์ผ๋ถ€ ํ•œ๊ณ„์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ, ์„œ๋ฒ„ ์ธก ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ์ „์†กํ•˜๋Š” ํ”„๋ ˆ์ž„์— ๋น„๋ก€ํ•˜์—ฌ ์„œ๋ฒ„์˜ ๋ถ€ํ•˜๋ฅผ ์ฆ๊ฐ€์‹œํ‚จ๋‹ค. ๋‘ ๋ฒˆ์งธ, ๋™์ ์ธ ์ฑ„๋„์—์„œ ๋น ๋ฅด๊ณ  ํšจ์œจ์ ์œผ๋กœ ๋Œ€์ฒ˜ํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ์„ธ ๋ฒˆ์งธ, ์ด๋Ÿฌํ•œ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค์—์„œ ์„ ํƒ๋œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋“ค์ด ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ์œ„ํ•œ ์ตœ์ ์˜ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๊ฐ€ ์•„๋‹ ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์ ๋“ค์€ ๋ฐฐํ„ฐ๋ฆฌ๋กœ ๋™์ž‘ํ•˜๋Š” ๋…ธ๋“œ๋“ค์˜ ํฐ ์—๋„ˆ์ง€ ์†Œ๋ชจ๋ฅผ ์•ผ๊ธฐํ•˜๊ณ  LoRa ๋„คํŠธ์›Œํฌ์˜ ์ฑ„๋„์ด ๋™์ ์œผ๋กœ ๋ณ€๊ฒฝ๋˜๋Š” ํ™˜๊ฒฝ์—์„œ ์„ฑ๋Šฅ์„ ๊ฐ์†Œ์‹œํ‚จ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์šฐ๋ฆฌ๋Š” ์„œ๋ฒ„์˜ ๋ถ€ํ•˜๋ฅผ ์ตœ์†Œํ™”ํ•˜๋ฉฐ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ๋…ธ๋“œ ๊ธฐ๋ฐ˜์˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜์ธ NbADR์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ๋…ธ๋“œ ์ธก์—์„œ ์ „์†ก ๋ฐ›์€ ๋‹ค์šด๋งํฌ ํŒจํ„ด์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฑ„๋„ ์ƒํ™ฉ์— ๋น ๋ฅด๊ฒŒ ๋Œ€์‘ํ•˜๊ณ , Efficiency of Energy (EoE) ๋ฉ”ํŠธ๋ฆญ์„ ํ™œ์šฉํ•˜์—ฌ ํšจ์œจ์ ์ธ ์—๋„ˆ์ง€ ์†Œ๋ชจ๋ฅผ ์œ„ํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ ํƒํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” EoE ๊ธฐ๋ฐ˜์œผ๋กœ ์„ ํƒํ•œ ์ „์†ก ํŒŒ๋ผ๋ฏธํ„ฐ์˜ ํšจ์œจ์„ฑ์„ ๋ถ„์„ํ•˜๊ณ , ๊ด‘๋ฒ”์œ„ํ•œ ์‹คํ—˜์„ ์ง„ํ–‰ํ•œ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, NbADR์€ ๊ธฐ์กด์˜ ADR ๋ฉ”์ปค๋‹ˆ์ฆ˜๋“ค๊ณผ ๋น„๊ตํ•˜์—ฌ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ ์ธก๋ฉด์—์„œ ํšจ๊ณผ์ ์ด๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ, NbADR์€ ๊ธ‰๊ฒฉํ•˜๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š” ์ฑ„๋„ ํ™˜๊ฒฝ์—์„œLoRa ๋„คํŠธ์›Œํฌ์˜ ์ฒ˜๋ฆฌ๋Ÿ‰์„ ๋ณด์žฅํ•˜๊ณ  ๋…ธ๋“œ ๊ฐ„ ๊ณตํ‰์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค.Chapter 1 Introduction 1 Chapter 2 Related Work 4 Chapter 3 Preliminaries 7 3.1 LoRa/LoRaWAN 7 3.2 Transmission Parameters 8 3.3 ADR Mechanism 9 Chapter 4 Channel Modeling 10 4.1 Loss 10 4.2 Collision 12 Chapter 5 Node-based ADR Mechanism 14 5.1 Approach for Energy Efficiency 15 5.2 Node-based ADR Mechanism (NbADR) 17 Chapter 6 Evaluation 21 6.1 Simulation Settings 22 6.2 Simulation Results 23 Chapter 7 Conclusion 33 Bibliography 35Maste

    ๊ฐ•์›๋Œ€ํ•™๊ต ์‹ ์ถ•์บ ํผ์Šค(๋„๊ณ„์บ ํผ์Šค) ์†Œ๊ฐœ

    Get PDF

    ์šฉ์•ก๊ณต์ •์ด ๊ฐ€๋Šฅํ•œ ๋ฆฌํŠฌ ๋ฐ ์†Œ๋“ ๊ณ ์ฒด์ „ํ•ด์งˆ์„ ์ด์šฉํ•œ ์ „๊ณ ์ฒด์ „์ง€

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€, 2017. 2. ์˜ค์Šน๋ชจ.Bulk-type all-solid-state lithium batteries using sulfide solid electrolytes are considered a very promising solution for tackling the safety challenges associated with conventional lithium-ion batteries. However, further development of solid electrolytes is imperative in order to improve their ionic contacts with active materials, conductivity, scalability of synthesis protocols, and air-stability. A solution-based synthesis process can provide a breakthrough in the architecture and fabrication of composite structures. This study show that a new, highly conductive (4.1ร—10-4 S cm-1 at 30oC), highly ductile, and dry-air-stable glass 0.4LiI-0.6Li4SnS4 is prepared at 200oC using a scalable method that employs a homogeneous methanol solution. Comprehensive diagnostic analyses reveal that lowering the crystallinity and incorporating large and highly polarizable iodide ions into Li4SnS4 improve the ductility and conductivity. Importantly, the solution process enables the wetting of any exposed surface of the active materials with highly conductive solidified electrolytes (0.4LiI-0.6Li4SnS4), resulting in considerable improvements in electrochemical performances of these electrodes over conventional mixture electrodes. Even though sodium-ion batteries (NIBs), which is another important class of battery type, have been developed extensively due to the advantage of low cost, development of all-solid-state Na batteries (ASNBs) has remained challenging because of relatively low ionic conductivity of Na-ion conductor. Na3SbS4 show high conductivity of 1.1ร—10-3 S cm-1 which is one of the most promising result so far. Furthermore it remain its structure after dissolving to water or methanol with moderate ionic conductivities. Consequently, sodium-ion conductive coating layers were casted to active material successfully. The results hold great promise for practical all-solid-state technology as well as provide insights into discovering broad classes of solution-processable superionic conductors.1. INTRODUCTION 1 2. BACKGROUND 8 2.1. Basic Principles of Electrochemical Cells 8 2.2. Overview of Bulk-type Inorganic All-solid-state Batteries 11 2.2.1. Conductivity of IonicConductor 11 2.2.2. Electrochemical stability of Solid Electrolytes 13 2.2.3. Electrode Materials for ASSLBs 16 3. EXPERIMENTAL 22 3.1. Material Preparation 22 3.2. Material Characterization 23 3.3. Electrochemical Characterization 26 4. RESULTS AND DISCUSSION 29 4.1. LiI-Li4SnS4: Lithium Ionic Conductor 29 4.1.1. Properties of LiI-Li4SnS4 29 4.1.2. All-solid-state Lithium Batteries using LiI-Li4SnS4 Superionic Conductor 51 4.2. Na3SbS4: Sodium Ionic Conductor 73 4.2.1. Properties of Na3SbS4 73 4.2.2. All-Solid-state Sodium Batteries using Na3SbS4 Superionic Conductor 87 5. CONCLUSION 102 REFERENCES 104 ๊ตญ๋ฌธ ์ดˆ๋ก 110Docto

    A Study on the improvement scheme of the operating of O-2 anchorage at the Busan north port

    Get PDF
    According to the reclaiming work due to construction of No.2 Lotte world, the alternative pier is under construction in Dongsam-dong Yeongdo-gu to accomodate small boats. As a result of that, 0-2 Anchorage used to bunkering or waiting for berth should be reduced, it is expected that the risk of passage and congestion around the anchorage could be increased because of the traffic of small boat using the alternative pier. This study analyze traffic circumstance and weather condition of anchorage near the Busan inner fairway, and suggest improvement scheme of 0-2 anchorage and procurement of alternative anchorage in order to resolve the problem caused by reduction of 0-2 anchorage. There are couple of ways to resolve congestion & to reduce the risk of traffic at designated area and to adjust the area of new anchorage based on the survey and analysis of weather, traffic situation, and etc. This study suggest to enlarge the 0-2 anchorage 250m toward to inner breakwater, where is used for 0-1 anchorage for quarantine. And the anchorage can be divided into 0-1 & 0-2 to accomodate different size of ships.์ œ 1 ์žฅ ์„œ๋ก  = 1 1.1 ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  = 1 1.2 ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• ๋ฐ ๋ฒ”์œ„ = 3 ์ œ 2 ์žฅ ๋ถ€์‚ฐ๋ถํ•ญ ์ž์—ฐํ™˜๊ฒฝ ๋ถ„์„ = 6 2.1 ๊ธฐ์ƒ๊ฐœ์š” = 6 2.2 ๊ธฐ์ƒ ๋ฐ ํ•ด์ƒ ์ž๋ฃŒ ๋ถ„์„ = 8 2.2.1 ๋ฐ”๋žŒ = 8 2.2.2 ์กฐ์„ = 12 2.2.3 ์กฐ๋ฅ˜ = 15 2.2.4 ํŒŒ๋ž‘ = 18 ์ œ 3 ์žฅ ๋ถ€์‚ฐ ๋ถํ•ญ ์‹œ์„คํ˜„ํ™ฉ ๋ฐ ์‹คํƒœ๋ถ„์„ = 23 3.1 ์‹œ์„คํ˜„ํ™ฉ = 23 3.1.1 ์ˆ˜์—ญ์‹œ์„ค = 23 3.1.2 ์™ธ๊ณฝ์‹œ์„ค = 25 3.1.3 ์ ‘์•ˆ์‹œ์„ค = 26 3.2 ์ด์šฉ ์‹คํƒœ ๋ถ„์„ = 31 3.2.1 ์„ ๋ฐ• ์ž…์ถœํ•ญ ์‹ค์  = 31 3.2.2 ์„ ๋ฐ• ์„ ์ข…๋ณ„ ์‹ค์  = 32 3.2.3 ์—ฐ๋„๋ณ„ ํ™”๋ฌผ์ฒ˜๋ฆฌ ์‹ค์  = 33 3.2.4 ํ’ˆ๋ชฉ๋ณ„ ํ™”๋ฌผ์ฒ˜๋ฆฌ์œจ = 35 3.3 ๋ถ€์‚ฐ ๋ถํ•ญ ์ •๋ฐ•์ง€ ์‚ฌ์šฉํ˜„ํ™ฉ ๋ฐ ํ•ญ์ ๋ถ„์„ = 36 3.3.1 ์ •๋ฐ•์ง€ ์‚ฌ์šฉ ํ˜„ํ•ญ = 36 3.3.2 ํ†ตํ•ญ ์„ ๋ฐ•์˜ ํ•ญ์  ๋ถ„์„ = 39 3.3.3 ํ•ด์—ญ๋ณ„ ์ด์šฉ ํ˜„ํ™ฉ ์กฐ์‚ฌ = 46 3.4 ๋Œ€์ฒด๋ถ€๋‘ ์‹ ์„ค ๊ณ„ํš ๋ฐ ์ ‘์ด์•ˆ ์˜ํ–ฅ ๋ถ„์„ = 47 3.4.1 ๋Œ€์ฒด๋ถ€๋‘ ์‹ ์„ค ๊ณ„ํš = 47 3.4.2 ์ ‘์ด์•ˆ ์˜ํ–ฅ ๋ถ„์„ = 49 ์ œ 4 ์žฅ ์„ค๋ฌธ์กฐ์‚ฌ ๋ฐ ๋ถ„์„ = 57 4.1 ์‚ฌ์šฉ์ž ์„ค๋ฌธ ์กฐ์‚ฌ ๊ฐœ์š” = 57 4.1.1 ์„ค๋ฌธ์กฐ์‚ฌ ๋ฐฐ๊ฒฝ ๋ฐ ๊ตฌ์„ฑ = 57 4.1.2 ์„ค๋ฌธ์ง€ ๋‚ด์šฉ = 58 4.2 ์„ค๋ฌธ ๊ฒฐ๊ณผ ๋ถ„์„ = 58 4.2.1 ์˜ˆ๋ถ€์„  ๋Œ€์ƒ ์„ค๋ฌธ ์กฐ์‚ฌ ๊ฒฐ๊ณผ ๋ถ„์„ = 58 4.2.2 ๋ถ€์‚ฐํ•ญ ๋„์„ ์‚ฌ ๋Œ€์ƒ ์„ค๋ฌธ ์กฐ์‚ฌ ๊ฒฐ๊ณผ ๋ถ„์„ = 80 4.2.3 ๋ถ€์‚ฐํ•ญ VTS์„ผํ„ฐ ๊ด€์ œ์‚ฌ ๋Œ€์ƒ ์„ค๋ฌธ ์กฐ์‚ฌ ๊ฒฐ๊ณผ ๋ถ„์„ = 83 ์ œ 5 ์žฅ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์— ์˜ํ•œ O-2 ์ •๋ฐ•์ง€ ํ†ตํ•ญ ์•ˆ์ „์„ฑ ๊ฒ€์ฆ = 89 5.1 ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์‹ค์‹œ ์กฐ๊ฑด ๋ฐ ์‹œ๋‚˜๋ฆฌ์˜ค = 89 5.1.1 ๋ฐ”๋žŒ ๋ฐ ์กฐ๋ฅ˜ = 89 5.1.2 ๋Œ€์ƒ ํ•ด์—ญ ๋ฐ ํ†ตํ•ญ ํ•ญ๋กœ = 90 5.2 ์„ ๋ฐ•์กฐ์ข… ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์ˆ˜ํ–‰ = 91 5.3 ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ ๋ถ„์„ = 106 ์ œ 6 ์žฅ O-2 ์ •๋ฐ•์ง€ ์ถ•์†Œ ๋ฒ”์œ„ ๋ฐ ์šด์˜ ๊ฐœ์„  ๋ฐฉ์•ˆ = 108 6.1 O-2 ์ •๋ฐ•์ง€ ์ถ•์†Œ ๋ฒ”์œ„ = 108 6.1.1 ์ •๋ฐ•์ง€ ์ถ•์†Œ ๋ฐฉ์•ˆ = 108 6.1.2 ์ •๋ฐ•์ง€ ์ถ•์†Œ ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ๊ด€๋ จ ๊ธฐ๊ด€ ์˜๊ฒฌ ์ˆ˜๋ ด ๊ฒฐ๊ณผ = 114 6.1.3 O-2 ์ •๋ฐ•์ง€ ์ถ•์†Œ ๋ฒ”์œ„ ๊ฒฐ์ • = 114 6.2 O-2 ์ •๋ฐ•์ง€ ์šด์˜ ๊ฐœ์„  ๋ฐฉ์•ˆ = 116 6.2.1 ์˜์—ญ์  ์ธก๋ฉด์—์„œ์˜ ๊ฐœ์„  ๋ฐฉ์•ˆ = 116 6.2.2 ํ•ด์ƒ๊ตํ†ต ๊ด€์ œ์  ์ธก๋ฉด์—์„œ์˜ ๊ฐœ์„  ๋ฐฉ์•ˆ = 120 ์ œ 7 ์žฅ ๊ฒฐ๋ก  = 124 ์ฐธ๊ณ  ๋ฌธํ—Œ = 128 ๋ถ€๋ก = 12

    Programmed Serial Stereochemical Relay and Application in the Synthesis of Morphinans Desymmetrization-Based Asymmetric Total Synthesis of Oxycodone

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ํ™”ํ•™๋ถ€, 2018. 2. David Yu-Kai Chen.๋ชจ๋ฅดํ•€์€ ์‹๋ฌผ๋กœ๋ถ€ํ„ฐ ์œ ๋ž˜๋œ ์•Œ์นผ๋กœ์ด๋“œ ์ฒœ์—ฐ๋ฌผ๋กœ์„œ ๋ณต์žกํ•œ ๊ตฌ์กฐ๋กœ ์ธํ•ด ์œ ๊ธฐํ•ฉ์„ฑ ํ™”ํ•™์ž๋“ค๋กœ๋ถ€ํ„ฐ ๋งŽ์€ ์ฃผ๋ชฉ์„ ๋ฐ›์•„์™”๋‹ค. ์ฒซ ์žฅ์—์„œ๋Š” ์ค‘๊ฐ„์ฒด 50 ์˜ ํ•ฉ์„ฑ์„ ์œ„ํ•ด ๋ถ„์ž์˜ ๋น„๋Œ€์นญํ™” ๊ณผ์ •๊ณผ ๋ถ„์ž ๋‚ด์˜ ์Šคํ…Œ๋ ˆ์˜ค ์„ผํ„ฐ ์ด์ „์„ ์ ์šฉํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด oxidatative dearomatization, ๋””์—˜์ฆˆ-์•Œ๋” ๋ฐ˜์‘์ด ์ด๋ฃจ์–ด ์กŒ์œผ๋ฉฐ, ๋ชจ๋ฅดํ•€์˜ key quaternary center ์™€ phenanthrene์˜ ํ•ต์‹ฌ๊ตฌ์กฐ๋ฅผ ํ˜•์„ฑํ•˜๊ฒŒ ๋œ๋‹ค. ๋‘ ๋ฒˆ์งธ ์žฅ์—์„œ๋Š” (์ค‘๊ฐ„์ฒด 50)๋ฅผ ์‚ฌ์šฉํ•ด ๋ชจ๋ฅดํ•€์˜ ์œ ๋„์ฒด์ธ ๋””ํ•˜์ด๋“œ๋กœ์ฝ”๋””๋…ผ๊ณผ ๋””ํ•˜์ด๋“œ๋กœ์ฝ”๋”˜์„ ํ•ฉ์„ฑ ํ•˜์˜€๋‹ค. ์ด ๊ณผ์ •์—์„œ Beckmann ์žฌ๋ฐฐ์—ด ๋ฐ˜์‘๊ณผ ํ˜ธํ”„๋งŒ ์ œ๊ฑฐ๋ฐ˜์‘์„ ์‚ฌ์šฉํ•˜์—ฌ ์•Œ์นผ๋กœ์ด๋“œ ๋ถ„์ž์˜ ํŠน์ง• ์ค‘์˜ ํ•˜๋‚˜์ธ ์งˆ์†Œ ์›์ž๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ์‚ฝ์ž…ํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ , ์•ŒํŒŒ ํ‚คํ†  ์˜ฅ์‹œ๋ฐ์ด์…˜ SN2 ๋ฐ˜์‘์„ ํ†ตํ•œ ํ…ŒํŠธ๋ผํžˆ๋“œ๋กœํ‘ธ๋ž€๋ง ํ•ฉ์„ฑ, ๊ทธ๋ฆฌ๊ณ  reductive birch-type detosylation์„ ์ด์šฉํ•œ ํ”ผํŽ˜๋ฆฌ๋”˜๋ง ํ•ฉ์„ฑ์ด ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์„ธ ๋ฒˆ์งธ ์žฅ์€, ์•ž์„œ ์„œ์ˆ  ๋˜์—ˆ๋˜ ํ•ฉ์„ฑ๊ณผ ๋น„๊ตํ•˜์—ฌ ๋” ๋†’์€ ํšจ์œจ์„ฑ์„ ๊ฐ€์ง„ ๋ฐฉ์‹์ด ๋„์ž…๋˜์—ˆ๋‹ค. ์ด ๊ณผ์ •์—์„œ ์ƒˆ๋กœ์šด ๋ชจ๋ฅดํ•€ ์œ ๋„์ฒด ์˜ฅ์‹œ์ฝ”๋ˆ์„ ํ•ฉ์„ฑ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ด‘๋ฐ˜์‘์„ ์‚ฌ์šฉํ•œ 5๊ฐํ˜• ๊ณ ๋ฆฌ์˜ ํ•ฉ์„ฑ๊ณผ Rovis๊ฐ€ ๋ฐœํ‘œํ–ˆ๋˜ asymmetric ๋น„๋Œ€์นญ์„ฑ์„ ๋ฐฉ์‹์„ ์ ์šฉํ•˜์—ฌ ๊ด‘ํ•™ํ™œ์„ฑ์ด ์žˆ๋Š” ํŠธ๋ฆฌ์˜ฅ์„ธ์ธ ์„ ํ•ฉ์„ฑ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.Chp 1 Molecular Desymmetrization and Rationally Designed Serial Stereochemical Induction 1 ABSTRACT 2 INTRODUCTION 3 RESULTS AND DISCUSSION 7 1.1 Synthetic investigations in a desymmetrization based approach to biaryl system 27 7 1.2 Point-to-axial stereoinduction 8 1.3 Axial-to-point stereoinduction 9 1.3.1 Temperature-dependent configurational stability study 9 1.3.2 Oxidative dearomatization of biaryl phenols 36a/36a, 36b/36b, 36d/36d and 35c/35c 10 1.4 Point-to-point stereochemical induction 16 CONCLUSION 17 EXPERIMENTAL 19 REFERENCES 66 SPECTRA 68 Chp 2 Synthetic Application of a Quaternary Center Containing Tetracyclic Intermediate in the Total Synthesis of Dihydrocodeinone and Dihydrocodeine 146 ABSTRACT 147 INTRODUCTION 148 RESULTS AND DISCUSSION 153 CONCLUSION 162 EXPERIMENTAL 164 REFERENCES 186 SPECTRA 189 Chp 3 Second Generation Synthesis Key Intermediates En-Route to the Total Synthesis of Dihydrocodeine and Dihydrocodeinone And Asymmetric Total Synthesis of Oxycodone 221 ABSTRACT 222 INTRODUCTION 223 RESULTS AND DISCUSSION 226 3.1 Sencond-Generation Synthesis of Tricyclic Intermediate 111a 226 3.2 Sencond-Generation Synthesis of Tricyclic Intermediate 124 230 3.3 Asymmetric Total Synthesis of Oxycodone 232 CONCLUSION 239 EXPERIMENTAL 242 REFERENCES 275 SPECTRA 278 LIST OF ABBREVIATIONS 327 ABSTRACT (KOREAN) 329 ACKNOWLEDGEMENT 330Maste

    ๊ธˆ์œต์ •์ฑ… ์‹œ๋ฎฌ๋ ˆ์ด์…˜์˜ ํšจ๊ณผ์ ์ธ ์ˆ˜์—…๋ฐฉ๋ฒ• ํƒ์ƒ‰ : ํ˜‘๋™ํ•™์Šต๊ณผ ๊ฐœ๋ณ„ํ•™์Šต์˜ ๋น„๊ต๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฌํšŒ๊ต์œก๊ณผ ์ผ๋ฐ˜์‚ฌํšŒ์ „๊ณต,1997.Maste

    Optimization of Consumer's ESS and Improvement of TOU Pricing for Demand Management

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณตํ•™์ „๋ฌธ๋Œ€ํ•™์› ์‘์šฉ๊ณตํ•™๊ณผ, 2019. 2. ์œค์šฉํƒœ.๊ตญ๋‚ด์™ธ ์ „๋ ฅํŒ๋งค ์‚ฌ์—…์ž๋“ค์ด ์ ์šฉํ•˜๊ณ  ์žˆ๋Š” ๊ณ„์‹œ๋ณ„์š”๊ธˆ์ œ (Time of Use, TOU)๋Š” ์‚ฌ์šฉ๋Ÿ‰์— ๋”ฐ๋ผ ๊ณ„์ ˆ๋ณ„ยท์‹œ๊ฐ„๋Œ€๋ณ„ ๊ฐ๊ฐ ๋‘ยท์„ธ๋‹จ๊ณ„์˜ ๋‹จ๊ฐ€๋ฅผ ์ ์šฉํ•˜๋Š” ์š”๊ธˆ์ œ์ด๋‹ค. ์ด๋Š” ์‚ฌ์šฉ๋Ÿ‰์ด ๋งŽ ์€ ์‹œ๊ฐ„๋Œ€์—๋Š” ๋น„์‹ผ ์š”๊ธˆ์„, ์‚ฌ์šฉ๋Ÿ‰์ด ์ ์€ ์‹œ๊ฐ„๋Œ€์—๋Š” ์ €๋ ด ํ•œ ์ „๋ ฅ์š”๊ธˆ์„ ์†Œ๋น„์ž์—๊ฒŒ ๋ถ€๊ณผํ•จ์œผ๋กœ์„œ, ์ตœ์ข… ์†Œ๋น„์ž์˜ ๋ถ€ํ•˜ ํŒจํ„ด์ด ํŒ๋งค์‚ฌ์—…์ž๊ฐ€ ์˜๋„ํ•œ ๋ฐฉํ–ฅ์œผ๋กœ ๋ณ€ํ™”ํ•˜๋„๋ก ์œ ๋„ํ•˜๊ธฐ ์œ„ํ•จ์ด๋‹ค. ํŒ๋งค์‚ฌ์—…์ž์˜ ์ด๋Ÿฌํ•œ ๋ถ€ํ•˜ํŒจํ„ด ์œ ๋„ํ™œ๋™์„ ์ˆ˜์š”๊ด€๋ฆฌ (Demand Management, DM)๋ผ๊ณ  ํ•œ๋‹ค. ์†Œ๋น„์ž์˜ ์ตœ์ข… ๋ชฉ์ ์€ ํ•„์š”ํ•œ ์ „๋ ฅ์„ ์ถฉ๋ถ„ํžˆ ์‚ฌ์šฉํ•˜๋ฉด์„œ ์ „ ๋ ฅ์š”๊ธˆ์„ ์ตœ์†Œํ™” ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ํŒ๋งค์‚ฌ์—…์ž๊ฐ€ TOU ์š”๊ธˆ์ œ๋ฅผ ์‹œํ–‰ํ•˜๋ฉด ์†Œ๋น„์ž๋Š” ๋ถ€ํ•˜์‹œ๊ฐ„๋Œ€์ด๋™(Load Shift), ์ตœ๋Œ€์ˆ˜์š”๊ฐ์†Œ (Peak Shaving) ๋“ฑ์˜ ์ˆ˜์š”๋ฐ˜์‘(Demand Response, DR)์„ ๋ณด ์ธ๋‹ค. ์ด์— ๋Œ€ํ•ด ์ „๋ ฅ์š”๊ธˆ์ด ์ €๋ ดํ•œ ์‹œ๊ฐ„๋Œ€์— ์ „๊ธฐ์—๋„ˆ์ง€๋ฅผ ์ €์žฅํ–ˆ๋‹ค๊ฐ€ ํ•„์š”ํ•œ ์‹œ๊ธฐ์— ๋ฐฉ์ „ํ•˜์—ฌ ์ „๊ธฐ์—๋„ˆ์ง€๋ฅผ ๊ณต๊ธ‰ํ•ด์ฃผ ๋Š” ์—๋„ˆ์ง€์ €์žฅ์žฅ์น˜(Energy Storage System, ESS)์˜ ํ™œ์šฉ์€ ์†Œ๋น„์ž์—๊ฒŒ ์ข‹์€ ๋Œ€์‘์ „๋žต์ด ๋  ์ˆ˜ ์žˆ๋‹ค. ์†Œ๋น„์ž๊ฐ€ ESS๋ฅผ ํ™œ์šฉํ•˜๋ฉด ์†Œ๋น„์ž๋Š” ์ „๋ ฅ์š”๊ธˆ์„ ์ ˆ๊ฐํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ํŒ๋งค์‚ฌ์—…์ž๋Š” ์ง€์†์ ์ธ ์ˆ˜์š”๊ด€๋ฆฌ์˜ ํšจ๊ณผ๋ฅผ ๊ฑฐ๋‘˜ ์ˆ˜ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ESS์˜ ๋†’์€ ํˆฌ์ž๋น„๋Š” ์†Œ๋น„์ž๊ฐ€ ๋ณดํŽธ์ ์œผ๋กœ ESS๋ฅผ ํ™œ์šฉํ•  ์ˆ˜ ์—†๊ฒŒ ํ•˜๋Š” ๊ฑธ๋ฆผ๋Œ์ด ๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ TOU ์š”๊ธˆ์ œ๋ฅผ ์ ์šฉ๋ฐ›๋Š” ์†Œ๋น„์ž์˜ ESS ํ™œ์šฉ์ด, ํŒ๋งค์‚ฌ์—…์ž๊ฐ€ ์˜๋„ํ•œ ์ˆ˜์š”๊ด€๋ฆฌ์˜ ํšจ๊ณผ์„ฑ๊ณผ ์†Œ๋น„์ž์˜ ๊ฒฝ์ œ์„ฑ์„ ํ™•๋ณดํ•˜๋ ค๋ฉด ESS ์šฉ๋Ÿ‰์‚ฐ์ •๊ณผ ์šด์˜๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ์ƒ์„ธํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์†Œ๋น„์ž์˜ ESS ํˆฌ์ž๋น„์™€ ์ „๋ ฅ์š”๊ธˆ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ๋“ค์„ ๋ถ„์„ํ•˜์—ฌ, MINLP(Mixed Integer Nonlinear Programming) ๋ชจ๋ธ๋กœ ๋ชฉ์ ํ•จ์ˆ˜๋ฅผ ์ˆ˜๋ฆฝํ•˜์—ฌ ์ตœ์ ํ™”ํ•˜์˜€๋‹ค. ์ด ํ•จ์ˆ˜๋Š” ๊ฐœ๋ณ„ ์†Œ๋น„์ž์˜ ๋ถ€ํ•˜ํŒจํ„ด์— ๋งž๋Š” ESS์˜ ์ตœ์ ์šฉ๋Ÿ‰์„ ์‚ฐ์ถœํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ฐ ์‹œ๊ฐ„๋ณ„ ์ถฉ๋ฐฉ์ „ ์Šค์ผ€์ค„์„ ์‚ฐ์ถœํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด ์‚ฐ์‹๋“ค์„ GAMS ํ”„๋กœ๊ทธ๋žจ์œผ๋กœ ๊ตฌํ˜„ํ•œ ๋’ค ์†Œ๋น„์ž์˜ ์‹ค์žฌ ์ˆ˜์š”๋ฐ์ดํ„ฐ๋ฅผ ์ ์šฉํ•˜์—ฌ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ, ํ•œ๊ตญ์—์„œ ํ˜„์žฌ ์ ์šฉ์ค‘์ธ TOU ์š”๊ธˆ๋‹จ๊ฐ€๋Š” ์†Œ๋น„์ž๊ฐ€ ESS๋ฅผ ํ™œ์šฉํ•  ์ถฉ๋ถ„ํ•œ ํŽธ์ต์„ ์ฃผ์ง€ ๋ชปํ–ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ด ํ•œ๊ณ„์ ์„ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด TOU ์š”๊ธˆ๋‹จ๊ฐ€๋ฅผ ๊ฐœ ์„ ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•˜์˜€๊ณ , ๊ฐœ์„ ํ•œ TOU ๋‹จ๊ฐ€๋ฅผ ์ ์šฉํ•˜์—ฌ ๋‹ค ์–‘ํ•œ ๋ถ€ํ•˜ํŒจํ„ด ์†Œ๋น„์ž์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ๊ฐœ์„ ๋œ TOU ์š”๊ธˆ์ œ๋„๋Š” ์†Œ๋น„์ž์—๊ฒŒ ESS๋ฅผ ํ™œ์šฉํ•  ์ถฉ๋ถ„ํ•œ ์œ ์ธ์„ ์ œ๊ณตํ•˜๋ฉฐ, ํŒ๋งค์‚ฌ์—…์ž์—๊ฒŒ ์ง€์†์ ์ธ ์ˆ˜์š”๊ด€๋ฆฌ์˜ ํšจ๊ณผ ๋ฅผ ์ค„ ์ˆ˜ ์žˆ์Œ์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค.Time of use(TOU) pricing, which is applied by domestic and overseas electric power sales companies(utilities), is a tariff that applies two or three step rates for each season and hour according to usage. This is to induce the end-use consumers to change the load pattern in the direction intended by imposing an expensive charge at a high usage time and an inexpensive electric charge at a low usage time. These load pattern inducing activities of utilities are called Demand Management(DM). The ultimate goal of the consumer is to minimize the electricity bill while fully utilizing the required power. When the TOU pricing is implemented by power companies, the consumer reacts by Demand Response(DR) like load shift and peak shaving. The use of an Energy Storage System(ESS), which stores electric energy at a time when the electricity rate is low and discharges it at a necessary time, can be a good strategy. When the consumer uses the ESS, a consumer can reduce electricity bills and electric utilities can gain a sustainable demand management effect. However, the high investment cost of ESS is a stumbling block for consumers to universally utilize ESS. Therefore, the detailed study is required for the ESS utilization of demand-side under TOU pricing to secure the economical benefit of consumer and demand management effect of utility. In this paper, the factors influencing the ESS investment cost and the electricity price of the consumer are analyzed, and the objective function and constraints with MINLP (Mixed Integer Nonlinear Programming) model are optimized. These functions calculate not only the optimum capacity of the ESS to fit on the load patterns of individual consumers, but also each hourly charging or discharging schedule for each day, each season. After these equations are implemented in GAMS program, simulations were performed by applying actual demand data of consumers. However, as a result of simulations, the current unit price of TOU pricing applied in Korea cannot provide enough benefits for consumers to utilize an ESS. Therefore, to overcome this limitation, this paper proposes a method to improve the unit price of TOU, and simulates for various load pattern consumers by applying the improved TOU unit price. As a result, the improved TOU pricing has proven that the ESS utilization of demand-side is beneficial to the consumer and provides sustainable demand management effect to power companies.์ œ 1 ์žฅ ์„œ๋ก  ์ œ 2 ์žฅ ๋ชจ๋ธ์˜ ์ˆ˜์‹ํ™” ์ œ 1 ์ ˆ ๋ชจ๋ธ ๊ฐœ์š” ๋ฐ ๋ชฉ์  ํ•จ์ˆ˜ ์ œ 2 ์ ˆ ์ œ์•ฝ์กฐ๊ฑด ์ œ 3 ์žฅ ์‚ฌ๋ก€ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์ œ 1 ์ ˆ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ธฐ์ดˆ ๋ฐ์ดํ„ฐ ์ œ 2 ์ ˆ ํ˜„์žฌ TOU ๊ธฐ๋ฐ˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์ œ 4 ์žฅ TOU ๊ฐœ์„  ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์ œ 1 ์ ˆ ํšจ๊ณผ์ ์ธ ์ˆ˜์š”๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ TOU ๊ฐœ์„  ์ œ 2 ์ ˆ ๊ฐœ์„  TOU๋ฅผ ํ™œ์šฉํ•œ ๋ถ€ํ•˜ํŒจํ„ด๋ณ„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์ œ 5 ์žฅ ๊ฒฐ๋ก  ์ฐธ๊ณ ๋ฌธํ—Œ AbstractMaste

    ๊ฐ•์›๋Œ€ํ•™๊ต ํ†ตํ•ฉ์˜ ์„ฑ๊ณผ์™€ ๊ณผ์ œ

    No full text
    corecore