59,287 research outputs found

    CyberGuarder: a virtualization security assurance architecture for green cloud computing

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    Cloud Computing, Green Computing, Virtualization, Virtual Security Appliance, Security Isolation

    myTrustedCloud: Trusted cloud infrastructure for security-critical computation and data managment

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    Copyright @ 2012 IEEECloud Computing provides an optimal infrastructure to utilise and share both computational and data resources whilst allowing a pay-per-use model, useful to cost-effectively manage hardware investment or to maximise its utilisation. Cloud Computing also offers transitory access to scalable amounts of computational resources, something that is particularly important due to the time and financial constraints of many user communities. The growing number of communities that are adopting large public cloud resources such as Amazon Web Services [1] or Microsoft Azure [2] proves the success and hence usefulness of the Cloud Computing paradigm. Nonetheless, the typical use cases for public clouds involve non-business critical applications, particularly where issues around security of utilization of applications or deposited data within shared public services are binding requisites. In this paper, a use case is presented illustrating how the integration of Trusted Computing technologies into an available cloud infrastructure - Eucalyptus - allows the security-critical energy industry to exploit the flexibility and potential economical benefits of the Cloud Computing paradigm for their business-critical applications

    Solar powered aircraft

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    A cruciform wing structure for a solar powered aircraft is disclosed. Solar cells are mounted on horizontal wing surfaces. Wing surfaces with spanwise axis perpendicular to surfaces maintain these surfaces normal to the Sun's rays by allowing aircraft to be flown in a controlled pattern at a large bank angle. The solar airplane may be of conventional design with respect to fuselage, propeller and tail, or may be constructed around a core and driven by propeller mechanisms attached near the tips of the airfoils

    Solutions and Tools for Secure Communication in Wireless Sensor Networks

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    Secure communication is considered a vital requirement in Wireless Sensor Network (WSN) applications. Such a requirement embraces different aspects, including confidentiality, integrity and authenticity of exchanged information, proper management of security material, and effective prevention and reaction against security threats and attacks. However, WSNs are mainly composed of resource-constrained devices. That is, network nodes feature reduced capabilities, especially in terms of memory storage, computing power, transmission rate, and energy availability. As a consequence, assuring secure communication in WSNs results to be more difficult than in other kinds of network. In fact, trading effectiveness of adopted solutions with their efficiency becomes far more important. In addition, specific device classes or technologies may require to design ad hoc security solutions. Also, it is necessary to efficiently manage security material, and dynamically cope with changes of security requirements. Finally, security threats and countermeasures have to be carefully considered since from the network design phase. This Ph.D. dissertion considers secure communication in WSNs, and provides the following contributions. First, we provide a performance evaluation of IEEE 802.15.4 security services. Then, we focus on the ZigBee technology and its security services, and propose possible solutions to some deficiencies and inefficiencies. Second, we present HISS, a highly scalable and efficient key management scheme, able to contrast collusion attacks while displaying a graceful degradation of performance. Third, we present STaR, a software component for WSNs that secures multiple traffic flows at the same time. It is transparent to the application, and provides runtime reconfigurability, thus coping with dynamic changes of security requirements. Finally, we describe ASF, our attack simulation framework for WSNs. Such a tool helps network designers to quantitatively evaluate effects of security attacks, produce an attack ranking based on their severity, and thus select the most appropriate countermeasures

    Assessment of Haitiโ€™s electricity sector

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    INTRODUCTION: This report summarizes the current state of the electricity sector in Haiti, to form a knowledge base from which to subsequently evaluate options for how best to increase electricity access in Haiti. Accordingly, this report summarizes the results of an extensive review of the publicly-available information on the electricity sector in Haiti, supplemented by targeted interviews with selected individuals known to be knowledgeable about electricity in Haiti based on their recent involvement in assessing the sector or in pursuing/supporting development opportunities. [TRUNCATED

    ์ „๋ ฅ์‹œ์žฅ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ธฐ๋ฒ•์„ ํ™œ์šฉํ•œ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€๊ฐ€ ์ „๋ ฅ์‹œ์Šคํ…œ ์œ ์—ฐ์„ฑ ๋ฐ ๊ฒฝ์ œ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๊ธฐ์ˆ ๊ฒฝ์˜ยท๊ฒฝ์ œยท์ •์ฑ…์ „๊ณต, 2021. 2. ์ด์ข…์ˆ˜.์ „ ์„ธ๊ณ„์ ์œผ๋กœ ์˜จ์‹ค๊ฐ€์Šค ๊ฐ์ถ• ๋ชฉํ‘œ๋ฅผ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด์„œ ์žฌ์ƒ์—๋„ˆ์ง€ ๋น„์ค‘์„ ํ™•๋Œ€ํ•˜๋Š” ์—๋„ˆ์ง€ ์ „ํ™˜ ์ •์ฑ…์ด ์‹œํ–‰๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ์ถœ๋ ฅ ๋ณ€๋™์„ฑ๊ณผ ๋ถˆํ™•์‹ค์„ฑ ํŠน์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€๋Š” ์ „๋ ฅ์‹œ์Šคํ…œ์˜ ์œ ์—ฐ์„ฑ์— ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚ฌ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๋‚ฎ์€ ์šด์˜ ๋น„์šฉ๊ณผ ๊ตญ๊ฐ€ ์ •์ฑ…์ƒ์˜ ๋ชฉ์  ๋“ฑ์— ์˜ํ•ด ์ „๋ ฅ ์‹œ์žฅ์—์„œ ์šฐ์„  ๊ตฌ๋งค๋˜๋ฉด์„œ ์ „ํ†ต ๋ฐœ์ „์›์˜ ๊ธ‰์ „ ์šฐ์„ ์ˆœ์œ„ ๊ฒฐ์ •์—๋„ ๋งŽ์€ ์˜ํ–ฅ์„ ์ฃผ๊ฒŒ ๋œ๋‹ค. ์ด์™€ ๊ฐ™์€ ๋งฅ๋ฝ์—์„œ, ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ์˜ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€ ์ •์ฑ…์— ์˜ํ•ด ์žฌ์ƒ์—๋„ˆ์ง€ ๋ฐœ์ „ ๋น„์ค‘์ด 20%๋ฅผ ์ดˆ๊ณผ ํ•˜๋Š” 2031๋…„์„ ๋Œ€์ƒ์œผ๋กœ ์ „๋ ฅ ์‹œ์Šคํ…œ์˜ ์œ ์—ฐ์„ฑ ํ‰๊ฐ€ ๋ฐ ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€๊ฐ€ ์ „๋ ฅ ์‹œ์žฅ์— ๋ฏธ์น˜๋Š” ๊ฒฝ์ œ์  ์˜ํ–ฅ ๋ถ„์„์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด์„œ ์šฐ์„ , ํ˜ผํ•ฉ์ •์ˆ˜๊ณ„ํš๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ ํ•˜๋ฃจ ์ „ ๋ฐœ์ „๊ณ„ํš ์ˆ˜๋ฆฝ ๋ชจํ˜•์„ ๊ตฌ์ถ•ํ•˜๊ณ , ์žฌ์ƒ์—๋„ˆ์ง€ ๋ฐœ์ „ ๋น„์ค‘์ด 6.2%๋กœ ์ƒ๋Œ€์ ์œผ๋กœ ๋‚ฎ์€ 2018๋…„์„ ๊ธฐ์ค€์œผ๋กœ 2031๋…„์˜ ์ „๋ ฅ ์‹œ์žฅ ์šด์˜ ์‹ค์ ๊ณผ ๋น„๊ตํ•˜๊ธฐ ์œ„ํ•ด์„œ, ๊ตฌ์ถ•ํ•œ ๋ฐœ์ „๊ณ„ํš ์ˆ˜๋ฆฝ ๋ชจํ˜•์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ „๋ ฅ ์‹œ์žฅ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. 2031๋…„ ์ „๋ ฅ ์‹œ์Šคํ…œ์˜ ์œ ์—ฐ์„ฑ ํ‰๊ฐ€๋ฅผ ์œ„ํ•ด์„œ 5๊ฐ€์ง€ ์œ ์—ฐ์„ฑ ๊ณต๊ธ‰ ์šฉ๋Ÿ‰ ์‚ฐ์ • ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ์„ค์ •ํ•˜๊ณ  ๊ฐ ์‹œ๋‚˜๋ฆฌ์˜ค์— ๋”ฐ๋ฅธ ์œ ์—ฐ์„ฑ ๊ณต๊ธ‰๋Ÿ‰๊ณผ ์ˆœ์ˆ˜์š” ๋ณ€๋™ ํญ์ธ ์œ ์—ฐ์„ฑ ์š”๊ตฌ๋Ÿ‰์˜ ์‹œ๊ฐ„ ๋‹จ์œ„ ๋น„๊ต๋ฅผ ํ†ตํ•ด์„œ ์ด 8,760์‹œ๊ฐ„์— ๋Œ€ํ•œ ์ฆโˆ™๊ฐ๋ฐœ ์œ ์—ฐ์„ฑ ๋ถ€์กฑ ํšŸ์ˆ˜๋ฅผ ์‚ฐ์ถœํ•˜์˜€๋‹ค. ์œ ์—ฐ์„ฑ ๊ณต๊ธ‰ ์ž์›์œผ๋กœ ์šด์˜ ์˜ˆ๋น„๋ ฅ๋งŒ์„ ๊ณ ๋ คํ•  ๊ฒฝ์šฐ, ์ฆ๋ฐœ ์œ ์—ฐ์„ฑ ์ธก๋ฉด์—์„œ ์žฌ์ƒ์—๋„ˆ์ง€ ๋ณ€๋™์„ฑ์„ ์•ฝ 94%๊นŒ์ง€ ๋Œ€์‘ํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์šด์˜ ์˜ˆ๋น„๋ ฅ ํ™•๋ณด๋Ÿ‰๋ณด๋‹ค ํฐ ๋ณ€๋™ ํญ์ธ ์•ฝ 6% ๋ณ€๋™์„ฑ์— ๋Œ€ํ•ด์„œ๋Š” ์†์‘์„ฑ ์ž์›์˜ ์—ญํ• ์ด ํ•„์š”ํ•œ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋ฐ˜๋ฉด์—, ๊ฐ๋ฐœ ์œ ์—ฐ์„ฑ ์ธก๋ฉด์˜ ์œ ์—ฐ์„ฑ ๋ถ€์กฑ ํšŸ์ˆ˜๋Š” ์•ฝ 18ํšŒ ์ˆ˜์ค€์œผ๋กœ ๋งค์šฐ ๋‚ฎ์€ ๋ฐœ์ƒํ™•๋ฅ ์„ ๋ณด์˜€๋‹ค. ์žฌ์ƒ์—๋„ˆ์ง€ ๋ณ€๋™์„ฑ ๋ถ„ํฌ์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋ณด๋ฉด, ๊ณ ์ •์ ์œผ๋กœ ์šด์˜ํ•˜๋˜ ์ „ํ†ต์ ์ธ ์šด์˜ ์˜ˆ๋น„๋ ฅ ๊ธฐ์ค€๊ณผ ๋‹ค๋ฅด๊ฒŒ ์žฌ์ƒ์—๋„ˆ์ง€ ๋ณ€๋™์„ฑ ๋Œ€์‘์„ ์œ„ํ•œ ์œ ์—ฐ์„ฑ ์ž์›์€ ํ™•๋ณด ๊ธฐ์ค€์„ ํƒ„๋ ฅ์ ์œผ๋กœ ์šด์˜ํ•  ํ•„์š”๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚œ๋‹ค. ๋˜ํ•œ, ์œ ์—ฐ์„ฑ ์ธก๋ฉด์—์„œ ํšจ์œจ์  ๋Œ€์‘์„ ์œ„ํ•œ ๋ฌผ๋ฆฌ์  ํŠน์„ฑ์ธ ๋†’์€ ์ฆโ€ข๊ฐ๋ฐœ๋ฅ ๊ณผ ์งง์€ ๊ธฐ๋™ ์ค€๋น„์‹œ๊ฐ„์„ ๋ณด์œ ํ•œ ๋ฐœ์ „์›๋“ค์ด ์šด์˜ ์˜ˆ๋น„๋ ฅ์— ํฌํ•จ๋˜๊ฒŒ ํ•˜๋ ค๋ฉด ํ˜„ํ–‰ ๋ฐœ์ „์ถœ๋ ฅ ์ƒํ•œ์ œ์•ฝ ๋ฐฉ๋ฒ• ๊ฐœ์„  ๋ฐ ์˜ˆ๋น„๋ ฅ ๋ณด์กฐ ์„œ๋น„์Šค ์‹œ์žฅ์˜ ๋ถ„๋ฆฌ ์šด์˜์„ ๊ฒ€ํ† ํ•  ํ•„์š”๊ฐ€ ์žˆ๊ฒ ๋‹ค. ์ด๋•Œ ๊ณ ๋ คํ•  ์ˆ˜ ์žˆ๋Š” ์˜ˆ๋น„๋ ฅ ๋ณด์กฐ ์„œ๋น„์Šค ์‹œ์žฅ ์ตœ์†Œ ๊ทœ๋ชจ๋Š” ์•ฝ 1,620์–ต ์›์œผ๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€๋กœ ์ธํ•ด 2031๋…„์˜ ๊ณ„ํ†ตํ•œ๊ณ„๊ฐ€๊ฒฉ์ด ํ‰๊ท ์ ์œผ๋กœ 13.7์›/kWh ๋‚ฎ์•„์งˆ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ์œผ๋ฉฐ, ๋”์šฑ์ด ์žฌ์ƒ์—๋„ˆ์ง€ ๋ฐœ์ „๋Ÿ‰ ๋น„์ค‘์ด ๋†’์•„์งˆ์ˆ˜๋ก ์ „ํ†ต ๋ฐœ์ „์›์œผ๋กœ ์ถฉ์กฑ์‹œ์ผœ์•ผ ํ•˜๋Š” ์ˆœ์ˆ˜์š” ํฌ๊ธฐ๊ฐ€ ๊ฐ์†Œํ•˜๋ฉด์„œ ๊ณ„ํ†ตํ•œ๊ณ„๊ฐ€๊ฒฉ ํ•˜๋ฝ์€ ๋”์šฑ ์‹ฌํ™”ํ•  ์ˆ˜๋„ ์žˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ์‹œ์žฅ ๊ฐ€๊ฒฉ ํ•˜๋ฝ์€ ํŒ๋งค์‚ฌ์—…์ž์˜ ์ „๋ ฅ ๋„๋งค ์š”๊ธˆ์˜ ๋™๋ฐ˜ ํ•˜๋ฝ์„ ์œ ๋„ํ•  ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ด์ง€๋งŒ, ๊ธฐํ›„๋ณ€ํ™” ๋Œ€์‘์„ ์œ„ํ•œ RPS ์ œ๋„์™€ ๋ฐฐ์ถœ๊ถŒ๊ฑฐ๋ž˜์ œ๋ฅผ ๊ณ ๋ คํ•œ ์ „๋ ฅ ๊ตฌ์ž…๋น„ ๋ณ€ํ™”์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋ณด๋ฉด, ์ „๋ ฅ๋Ÿ‰ ์ •์‚ฐ๊ธˆ์„ ์ œ์™ธํ•œ ์šฉ๋Ÿ‰ ์ •์‚ฐ๊ธˆ, ๋ฐฐ์ถœ๊ถŒ๊ฑฐ๋ž˜๋น„์šฉ ๋ฐ RPS ์˜๋ฌด์ดํ–‰ ๋น„์šฉ์ด ์ƒ์Šนํ•  ๊ฒƒ์œผ๋กœ ์˜ˆ์ธก๋˜์—ˆ๋‹ค. RPS ์˜๋ฌด์ดํ–‰๋น„์œจ, ๋ฐฐ์ถœ๊ถŒ ์œ ์ƒํ• ๋‹น๋น„์œจ ๋ฐ ๋ฐฐ์ถœ๊ถŒ ๊ฐ€๊ฒฉ ์‹œ๋‚˜๋ฆฌ์˜ค์— ๋”ฐ๋ฅธ ์ „๋ ฅ ์‹œ์žฅ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ์— ์˜ํ•˜๋ฉด, ํ‰๊ท  ์ „๋ ฅ ๊ตฌ๋งค ๋‹จ๊ฐ€๋Š” 2018๋…„ 93.87์›/kWh์—์„œ 2031๋…„ 106.03์›/kWh๊นŒ์ง€ ์ตœ๋Œ€ ์•ฝ 13% ์ƒ์Šนํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ด๋Š” ํ–ฅํ›„ ์ „๋ ฅ ์†Œ๋งค ์š”๊ธˆ์˜ ์ธ์ƒ ์••๋ ฅ ์š”์ธ์œผ๋กœ ์ž‘์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์ข…ํ•ฉํ•ด๋ณด๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์ •์ฑ…์  ํ•จ์˜๋ฅผ ๋Œ์–ด๋‚ผ ์ˆ˜ ์žˆ๋‹ค. ์ฒซ์งธ, 2031๋…„ ์ „๋ ฅ ์‹œ์Šคํ…œ์˜ ์œ ์—ฐ์„ฑ์„ ์ ์ • ์ˆ˜์ค€์œผ๋กœ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์šด์˜ ์˜ˆ๋น„๋ ฅ ํ™•๋ณด ๋ฐฉ๋ฒ•์„ ๋ฐœ์ „์ถœ๋ ฅ ์ƒํ•œ ์ œ์•ฝ ๋ฐฉ์‹ ๋Œ€์‹  ์œ ์—ฐ์„ฑ ์š”๊ตฌ์‚ฌํ•ญ์„ ์ถฉ์กฑํ•˜๋Š” ์ž์›๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ๊ฒฝ์Ÿ ์ž…์ฐฐ์„ ํ†ตํ•ด ํ™•๋ณดํ•˜๋Š” ๋ฐฉ์•ˆ ๋“ฑ ์ƒˆ๋กœ์šด ์šด์˜์˜ˆ๋น„๋ ฅ ํ™•๋ณด ๋Œ€์•ˆ์ด ๊ณ ๋ ค๋˜์–ด์•ผ ํ•œ๋‹ค. ๋˜ํ•œ, ์žฌ์ƒ์—๋„ˆ์ง€ ๋ณ€๋™์„ฑ ๋Œ€์‘ ๋ชฉ์ ์œผ๋กœ ์šด์˜ ์˜ˆ๋น„๋ ฅ๊ณผ ๋ณ„๋„๋กœ ์šด์˜ํ•˜๋Š” ์†์‘์„ฑ ์ž์›์„ ์ฐจ์งˆ์—†์ด ๊ณ„ํš๋Œ€๋กœ ๋ณด๊ธ‰ํ•˜๊ณ , ๊ฐ ์œ ์—ฐ์„ฑ ๊ณต๊ธ‰ ์ž์›๋ณ„ ๋ณ€๋™์„ฑ ๋Œ€์‘ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๊ณ ๋ คํ•˜์—ฌ ์žฌ์ƒ์—๋„ˆ์ง€ ๋ฐœ์ „๋Ÿ‰ ์˜ˆ์ธก์‹œ์Šคํ…œ์„ ์ •๊ตํ™”ํ•˜์—ฌ ์†์‘์„ฑ ์ž์›์— ๋Œ€ํ•œ ํƒ„๋ ฅ์ ์ธ ์œ ์—ฐ์„ฑ ๊ณต๊ธ‰๋Ÿ‰ ํ™•๋ณด ๊ธฐ์ค€์„ ์ ์šฉํ•ด ๋‚˜๊ฐ€์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๋‘˜์งธ, ์žฌ์ƒ์—๋„ˆ์ง€ ํ™•๋Œ€์™€ ๊ด€๋ จํ•œ ์ •์ฑ…์„ ๊ฐœ์ •ํ•˜๊ฑฐ๋‚˜ ์‹ ์„คํ•˜๊ณ ์ž ํ•  ๋•Œ๋Š” ์ง์ ‘์ ์ธ ์ •์ฑ…์˜ ๊ธฐ๋Œ€ํšจ๊ณผ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ํŒ๋งค์‚ฌ์—…์ž์˜ ์ „๋ ฅ ๊ตฌ์ž…๋น„ ์ฆ๊ฐ€๋กœ ์ธํ•œ ์ „๊ธฐ ์š”๊ธˆ ์ธ์ƒ ์••๋ ฅ๊ณผ ๊ฐ™์€ ๊ฐ„์ ‘์ ์ธ ํŒŒ๊ธ‰ํšจ๊ณผ๊นŒ์ง€ ํ•จ๊ป˜ ๊ณ ๋ คํ•ด ์ฃผ์–ด์•ผ๊ฒ ๋‹ค. RPS ์˜๋ฌดํ• ๋‹น๋น„์œจ, ๋ฐฐ์ถœ๊ถŒ๊ฑฐ๋ž˜์ œ ์œ ์ƒํ• ๋‹น๋น„์œจ, ๋ฐฐ์ถœ๊ถŒ ๊ฑฐ๋ž˜ ๋น„์šฉ ๋“ฑ์˜ ๋ณ€ํ™”๋กœ ์ตœ๋Œ€ 13%๊นŒ์ง€ ์ „๋ ฅ ๋„๋งค๊ฐ€๊ฒฉ์ด ์ƒ์Šนํ•  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์…‹์งธ, ์žฌ์ƒ์—๋„ˆ์ง€ ๋ฐœ์ „๋Ÿ‰๊ณผ ์‹œ์žฅ ๊ฐ€๊ฒฉ์ด ์ ์  ์ƒ๋ฐ˜๋œ ํŒจํ„ด์œผ๋กœ ๋ณ€ํ™”ํ•  ๊ฒƒ์œผ๋กœ ์˜ˆ์ธก๋˜๊ธฐ ๋•Œ๋ฌธ์—, ๋ณ€๋™๋น„ ๋ฐ˜์˜ ์‹œ์žฅ์˜ ์ •์‚ฐ ๊ทœ์น™์ด๋‚˜ ์‹œ์žฅ ๊ฐ€๊ฒฉ ์‚ฐ์ • ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๊ฐœ์„  ๊ฒ€ํ†  ์‹œ ์ด๋Ÿฐ ํŒจํ„ด ๋ณ€ํ™”๋ฅผ ๋ฐ˜๋“œ์‹œ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ๋˜ํ•œ, ์œ ์—ฐ์„ฑ ๊ณต๊ธ‰์— ์ฐธ์—ฌํ•œ ๋ฐœ์ „์‚ฌ์—…์ž๋“ค์˜ ๋ณด์ƒ์ด ์ ์ •ํ•œ ์ˆ˜์ค€์œผ๋กœ ์„ค์ •๋˜์–ด์•ผ ์—๋„ˆ์ง€ ์‹œ์žฅ ๋Œ€๋น„ ๋ณด์กฐ ์„œ๋น„์Šค ์‹œ์žฅ ์ฐธ์—ฌ๊ฐ€ ํ™œ์„ฑํ™” ๋  ๊ฒƒ์ด๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ฏธ๋ž˜ ์ „๋ ฅ ์‹œ์žฅ์—์„œ๋Š” ์ˆ˜์š” ํ”ผํฌ์™€ ์‹œ์žฅ ๊ฐ€๊ฒฉ ํ”ผํฌ์˜ ๋ถˆ์ผ์น˜๊ฐ€ ์ ์  ์ฆ๋Œ€๋  ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ, ์ˆ˜์š” ๊ด€๋ฆฌ, ๊ฒฝ์ œ์„ฑ DR, ์ „๊ธฐ ์š”๊ธˆ ์‚ฐ์ • ๋“ฑ ์ˆ˜์š” ํŒจํ„ด์„ ๊ณ ๋ คํ•˜๋Š” ๋‹ค์–‘ํ•œ ์ •์ฑ…๋“ค์ด ํ–ฅํ›„์—๋Š” ์ˆœ์ˆ˜์š” ํŒจํ„ด๋„ ํ•จ๊ป˜ ๊ณ ๋ คํ•˜๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์žฌ๊ฒ€ํ† ๋˜์–ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค.To achieve the reduction target of greenhouse gas emissions, energy transition policy is being implemented to expand the share of renewable energy worldwide. However, the expansion of renewable energy not only causes the flexibility problem of the power system due to volatility and uncertainty of renewable energy output, but also affects the merit order of traditional power generation sources due to low operating costs of renewables or national policy objectives. These effects give rise to a huge transformation in power systems with a high share of renewable energy. In this context, this study evaluates the flexibility of the power system and analyzes the economic impact on the power market in 2031, when the share of renewable energy exceeds 20% due to Koreas energy transition policy. First, a mixed-integer linear programming approach was used to formulate the power system day-ahead unit commitment and economic dispatch model, and a power market simulation was conducted to compare the performance of the electricity market in 2031 based on 2018 figures, when the share of renewable energy is relatively low at 6.2%. To assess the flexibility of the power system in 2031, the number of periods of flexibility deficit for 8,760 hours was calculated by comparing the supply of flexibility according to the scenario of available flexibility resources with the flexibility requirement, which is the fluctuation in net load over an hour. The results show that if only the operational reserve is considered as a flexibility supply resource, about 94% of the renewable energy volatility can be dealt with in terms of upward flexibility, but the role of the quick-start generation resources is found to be important for 6% of the ramping event greater than the reserve capacity. On the other hand, the number of times flexibility deficit occurs in terms of downward flexibility is expected to be about 18, showing a very low probability of occurrence. The analysis of the distribution of renewable energy volatility reveals that, unlike the standard for operational reserve, which was traditionally fixed, the resource for responding to flexibility problem in renewable energy needs to operate the flexible securing standard. In addition, it is necessary to review the improvement of the current upper limit method of power output level and the separate operation of the reserve auxiliary service market from the energy service market to ensure that power generation sources suitable for supplying flexibility with physical characteristics for response to flexibility are included in the operational reserve. At this time, the minimum market size of the reserve auxiliary service that could be considered was estimated to be about KRW 162 billion. The expansion of renewable energy will lower the system marginal price by 13.7 KRW/kWh on average in 2031. As the share of renewable energy generation increases, the capacity of net load to be met by traditional power generation decreases, and the drop in the system marginal price may be even worse. Such a decrease in electricity market prices seems to lead to the accompanied decline in the power vendors wholesale electricity price. However, when looking at the result of power purchase cost analysis considering the renewable portfolio standard (RPS) and the emissions trading scheme (ETS) to expand renewable energy, it was predicted that the capacity settlement amount, the emission trading cost, and the RPS obligation fulfillment cost, excluding the electricity settlement amount, would increase. According to the analysis of power market simulation by RPS obligatory rate, paid allocation ratio for emissions trading, and emissions price per unit scenarios, the average power purchase cost may increase up to about 13% from 93.87 KRW/kWh in 2018 to 106.03 KRW/kWh in 2031. This suggests that it could act as a pressure factor to raise electricity rates in the future. The results of this study have the following policy implications. First, to secure the flexibility of the power system to an appropriate level in 2031, it is necessary to consider the alternative method of securing the operating reserve via competitive bidding for flexibility resources that meet the power system requirement instead of the upper limit constraint on generation output. In addition, for the purpose of responding to variability of renewable energy, quick-start generators operated separately from the operational reserve should be implemented as planned. It is also necessary to refine the system for predicting the amount of renewable energy generation in consideration of the mechanism for responding to the variability of each flexibility resource to realize the flexible regulation of flexibility supply amount. Second, if policy makers consider revising or establishing a new policy related to the expansion of renewable energy, it is necessary to examine not only the expected direct effect of the policy but also the indirect ripple effect, such as the pressure to increase electricity rates due to the hike in power purchase costs of vendors. Third, since the amount of renewable energy generation and electricity market price are expected to change in an increasingly inconsistent pattern, it is also important to reconsider the design for the settlement rules of the cost-based pool market or method of deciding the market price. Finally, in the future power market, the pattern difference between the demand peak and the market price peak may increase. Therefore, various policies that consider demand patterns, such as demand management, economical demand response, and electricity fee system, should be reviewed in the direction of considering the net load pattern in the future.Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Research Objectives 6 1.3 Research Outline 9 Chapter 2. Literature Review 12 2.1 Power System Flexibility 12 2.1.1 Sources of Flexibility 15 2.1.2 Studies on Flexibility Evaluation 19 2.2 Generation Scheduling 23 2.2.1 Unit Commitment and Economic Dispatch Model 23 2.2.2 Optimization techniques for solving UC problem with High Renewable Energy Sources Penetration 25 2.3 Research of the Energy policy in Korea 28 2.4 Limitations of previous research and Research Motivation 33 Chapter 3. Methodology 36 3.1 Methodological Framework 36 3.2 Unit Commitment and Economic Dispatch Modeling 40 3.2.1 Generation scheduling using MILP 42 3.2.2 An empirical model for day-ahead unit commitment and economic dispatch 49 3.2.3 Model Input data 58 3.2.4 Evaluation of the power system flexibility 68 3.2.5 Economic impact analysis 72 3.3 Model validation 79 3.3.1 Overview of model validation 79 3.3.2 Model validation result 82 Chapter 4. Empirical Studies 87 4.1 The study on evaluating the power system flexibility 87 4.1.1 Overview of flexibility evaluation and premises of analysis 87 4.1.2 Net load variability and calculation of flexibility requirement 91 4.1.3 Unit commitment and economic dispatch simulation and calculation of flexibility supply amount 96 4.1.4 Empirical results of evaluating the power system flexibility 103 4.2 Composition of flexibility resources and ability to respond to volatility 111 4.2.1 Incentive effect for participation in operational reserve service 112 4.2.2 Composition of operational reserve resources for flexibility supply 117 4.2.3 Volatility response mechanism of operational reserves and quickโ€“start generators 123 4.2.4 Improvement of reserve system and separation of the auxiliary service market 128 4.3 Analysis of the economic impact 132 4.3.1 Premises for economic impact analysis 132 4.3.2 Forecasting SMP and electricity settlement amount 134 4.3.3 Analysis of the impact of policies related to the expansion of renewable energy 138 4.3.4 Empirical results and discussion 143 Chapter 5. Summary and Conclusion 146 5.1 Concluding Remarks and Contribution 146 5.2 Limitations and Future Studies 148 Bibliography 151 Appendix 1: The results of power generation scheduling of pumped-storage power plants 164 Appendix 2: Power market operation performance trend (2001-2019) 166 Abstract (Korean) 168Docto

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    Industrial production plants traditionally include sensors for monitoring or documenting processes, and actuators for enabling corrective actions in cases of misconfigurations, failures, or dangerous events. With the advent of the IoT, embedded controllers link these `things' to local networks that often are of low power wireless kind, and are interconnected via gateways to some cloud from the global Internet. Inter-networked sensors and actuators in the industrial IoT form a critical subsystem while frequently operating under harsh conditions. It is currently under debate how to approach inter-networking of critical industrial components in a safe and secure manner. In this paper, we analyze the potentials of ICN for providing a secure and robust networking solution for constrained controllers in industrial safety systems. We showcase hazardous gas sensing in widespread industrial environments, such as refineries, and compare with IP-based approaches such as CoAP and MQTT. Our findings indicate that the content-centric security model, as well as enhanced DoS resistance are important arguments for deploying Information Centric Networking in a safety-critical industrial IoT. Evaluation of the crypto efforts on the RIOT operating system for content security reveal its feasibility for common deployment scenarios.Comment: To be published at IEEE WF-IoT 201
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