23 research outputs found

    ์ „๋ 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„์„

    Get PDF
    ํ•™์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

    ์ค‘์žฅ๊ธฐ SOC ํˆฌ์ž์ „๋žต์— ๊ด€ํ•œ ์—ฐ๊ตฌ(The middle and long term investment strategies of transporation social overhead capitals)

    Get PDF
    ๋…ธํŠธ : ์ด ์—ฐ๊ตฌ๋ณด๊ณ ์„œ์˜ ๋‚ด์šฉ์€ ๊ตญํ† ์—ฐ๊ตฌ์›์˜ ์ž์ฒด ์—ฐ๊ตฌ๋ฌผ๋กœ์„œ ์ •๋ถ€์˜ ์ •์ฑ…์ด๋‚˜ ๊ฒฌํ•ด์™€๋Š” ์ƒ๊ด€์—†์Šต๋‹ˆ๋‹ค

    Type I saikosaponins a and d inhibit osteoclastogenesis in bone marrow-derived macrophages and osteolytic activity of metastatic breast cancer cells

    Get PDF
    Many osteopenic disorders, including a postmenopausal osteoporosis and lytic bone metastasis in breast and prostate cancers, are linked with a hyperosteoclast activity due to increased receptor activator of nuclear factor kappa-B ligand (RANKL) expression in osteoblastic/stromal cells. Therefore, inhibition of RANKL-induced osteoclastogenesis and osteoclast-induced bone resorption is an important approach in controlling pathophysiology of these skeletal diseases. We found that, of seven type I, II, and III saikosaponins isolated from Bupleurum falcatum, saikosaponins A and D, type I saikosaponins with an allyl oxide linkage between position 13 and 28 and two carbohydrate chains that are directly attached to the hydroxyl groups in position 3, exhibited the most potent inhibition on RANKL-induced osteoclast formation at noncytotoxic concentrations. The stereochemistry of the hydroxyl group at C16 did not affect their activity. Saikosaponins A and D inhibited the formation of resorptive pits by reducing the secreted levels of matrix metalloproteinase- (MMP-) 2, MMP-9, and cathepsin K in RANKL-induced osteoclasts. Additionally, saikosaponins A and D inhibited mRNA expression of parathyroid hormone-related protein as well as cell viability and invasion in metastatic human breast cancer cells. Thus, saikosaponins A and D can serve as a beneficial agent for the prevention and treatment of osteoporosis and cancer-induced bone loss.ope

    ์ถฉ๋Œ๊ฐ๊ณผ ์ข…๋ง ๋ฐ›์Œ๊ฐ ๊ตฌ์†์กฐ๊ฑด์„ ๊ณ ๋ คํ•œ ๋ฏธ์‚ฌ์ผ ์œ ๋„๋ฒ•์น™

    No full text
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2014. 2. ๊น€ํ˜„์ง„.This paper proposes a guidance law considering constraints on impact angle and terminal angle of attack for a homing missile. In the proposed structure, the guidance law generates angle of attack command and the controller tracks the generated command. For deriving the angle of attack command, the differential game problem with terminal boundary conditions is proposed and solved. Then, the sliding mode control is applied in order to derive the actual command input from the guidance command. Because the guidance command is the angle of attack, the terminal angle of attack constraint can be easily handled and the controller needs not deal with non-minimum phase characteristics. This capability to control the terminal angle of attack is the main contribution of the paper. The performance of the proposed law is evaluated using a two-dimensional nonlinear simulation. The result demonstrates that the proposed law allows the missile to intercept the maneuvering target with the constraints on impact angle and terminal angle of attack.Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Thesis Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1 Guidance Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Missile Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3 Guidance Law and Autopilot Design . . . . . . . . . . . . . . . . . . . . . . . . 10 3.1 Derivation of the Terminal Angle of Attack Constrained Guidance Law . . 10 3.2 Angle of Attack Controller Design . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 Angle of Attack Observer Design . . . . . . . . . . . . . . . . . . . . . . . 15 3.4 Synthesis of Guidance Law, Controller and Observer . . . . . . . . . . . . 16 4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 4.1 Performance Analysis of TAACG . . . . . . . . . . . . . . . . . . . . . . . 18 4.2 Comparison with Other Guidance Laws . . . . . . . . . . . . . . . . . . . . 19 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Maste

    U-๊ณก๊ด€์—์„œ์˜ ์ด์ฐจ ์œ ๋™์ด ์˜ˆํ˜ผํ•ฉ ๋ถ„์  ํ™”์—ผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๊ด€ํ•œ ์‹คํ—˜์  ์—ฐ๊ตฌ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ธฐ๊ณ„๊ณตํ•™๊ณผ,1999.Maste

    Bisphosphonate๊ณ„์—ด์˜ ์•ฝ๋ฌผ์ธ Clodronate์™€ Pamidronate๊ฐ€ ์กฐ๊ณจ์„ธํฌ์˜ ํ™œ์„ฑ ๋ฐ ํŒŒ๊ณจ์„ธํฌ์œ ์‚ฌ์„ธํฌ ์ƒ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์น˜์˜ํ•™๊ณผ ์น˜๊ณผ์•ฝ๋ฆฌํ•™ ์ „๊ณต,1999.Maste

    ์‹œ์•ผ ์ œํ•œ์ด ์žˆ๋Š” ์œ ๋„ํƒ„์˜ ์ถฉ๋Œ๊ฐ ๋ฐ ์ถฉ๋Œ์‹œ๊ฐ„ ์ œ์–ด ์œ ๋„ ๋ฒ•์น™

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2018. 8. ๊น€ํ˜„์ง„.Homing guidance aims at guiding a missile to its intended target using information acquired from an on-board seeker. In real applications of homing guidance laws, a field-of-view restriction of the missile seeker is a significant issue because maintaining the seeker lock-on condition is an important task for acquiring the target information. Especially, when implementing advanced guidance laws to impose terminal constraints on impact angle and time, considering the field-of-view constraint is particularly essential since the curved trajectory may let the seeker's look angle exceed the confined field-of-view limit. This dissertation presents guidance laws whose contributions are classified into three parts: i) impact angle control guidance law with the field-of-view constraint, ii) impact time control guidance law with the field-of-view constraint, and iii)iii) impact angle and time control guidance law with the field-of-view constraint. First, an impact angle control guidance law that confines the missile look angle during homing in order not to exceed a seeker's field-of-view limit is proposed. A sliding surface variable whose regulation guarantees the interception of a stationary target at the desired impact angle is designed, and the guidance law is derived to make the surface variable go to the sliding mode. Using a magnitude-limited sigmoid function in the surface variable, the proposed law prohibits the look angle from exceeding the specified limit during the entire homing. This capability to confine the missile look angle is valuable when a seeker's field-of-view is restricted, since imposing the terminal impact angle constraint demands the missile to fly a curved trajectory. Furthermore, the proposed law only needs the line-of-sight angle and look angle among the target information. Thus, the proposed law can easily be implemented into a homing missile equipped with a structurally simple passive strapdown seeker. Theoretical analysis in this part indicates that the proposed law accomplishes the impact angle constraint without violating the look angle limit although it only uses the information of bearing angles. Second, a guidance law that achieves the desired impact time without violating the seeker's field-of-view limit is presented. For the development of the law, kinematic conditions for impact time control are defined, and the backstepping control-based approach is adopted for the satisfaction of the conditions. The missile look angle is utilized as a virtual control input for the backstepping structure, and its magnitude is limited by a prescribed limit by restricting the controller gain. Consequently, the impact time constraint can be achieved with satisfying the look angle limit under the proposed law. Since few papers considering the field-of-view limit under the impact time control are available in open literature, the capability to confine the seeker's look angle with achieving the desired impact time is the main contribution of this part. Finally, a guidance law for impact angle and time control with taking into account the field-of-view constraint is developed. Basically, the law in this part is formed as a look angle-limited impact angle control guidance law that has an additional guidance gain. Since the length of the trajectory under this law is calculated as a function of this gain, the terminal impact time can be controlled by adjusting the gain. As a result, the proposed guidance law in this part can intercept the stationary target at the desired impact angle and time with satisfying the field-of-view limit. The proposed law is expected to achieve the accurate performance in real applications owing to its closed-loop structure without using any numerical routine such as off-line optimization or the shooting method. To evaluate the performance of the proposed laws, numerical simulations are conducted for each part. The results demonstrate that the proposed laws accomplish the desired terminal tasks with preventing the look angle from exceeding the prescribed limit.Table of Contents Page Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Background and motivations . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Literature survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2.1 Impact angle control guidance . . . . . . . . . . . . . . . . . . . . . 3 1.2.2 Impact time control guidance . . . . . . . . . . . . . . . . . . . . . 6 1.2.3 Impact angle and time control guidance . . . . . . . . . . . . . . . 8 1.3 Research objectives and contributions . . . . . . . . . . . . . . . . . . . . . 9 1.3.1 Impact angle control guidance law with _x000C_eld-of-view constraint . . . 9 1.3.2 Impact time control guidance law with _x000C_eld-of-view constraint . . . 10 1.3.3 Impact angle and time control guidance law with _x000C_eld-of-view constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.4 Thesis organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2 Impact Angle Control Guidance with Field-of-View Constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.1 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2 Design of impact angle control guidance law . . . . . . . . . . . . . . . . . 15 2.2.1 Kinematic conditions for impact angle control guidance . . . . . . . 16 2.2.2 Derivation of guidance law . . . . . . . . . . . . . . . . . . . . . . . 18 viii 2.3 Analysis of the proposed law . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.1 Look angle analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.2 Stability analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.3.3 Convergence analysis of error variables e1 and e2 . . . . . . . . . . . 22 2.4 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.4.1 Performance analysis of the proposed law . . . . . . . . . . . . . . . 27 2.4.2 Performance comparison with other guidance laws . . . . . . . . . . 31 2.4.3 Performance analysis in a realistic scenario . . . . . . . . . . . . . . 35 3 Impact Time Control Guidance with Field-of-View Constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.1 PROBLEM FORMULATION . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.2 IMPACT TIME CONTROL GUIDANCE LAW WITH CONSTRAINED FIELD-OF-VIEW LIMITS . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.2.1 Kinematic conditions for impact time control guidance . . . . . . . 40 3.2.2 Guidance law design . . . . . . . . . . . . . . . . . . . . . . . . . . 42 3.3 ANALYSIS OF THE PROPOSED GUIDANCE LAW . . . . . . . . . . . . 46 3.3.1 Guidance command analysis . . . . . . . . . . . . . . . . . . . . . . 46 3.3.2 Stability analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.3.3 Look-angle analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.3.4 Discussion about achievable impact time . . . . . . . . . . . . . . . 55 3.4 SIMULATION RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 3.4.1 Performance analysis of the proposed law . . . . . . . . . . . . . . . 60 3.4.2 Performance comparison with other guidance laws . . . . . . . . . . 64 3.4.3 Salvo attack in a realistic engagement . . . . . . . . . . . . . . . . . 67 4 Impact Angle and Time Control Guidance with Field-of-View Constraint . . . . 71 4.1 Problem formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.2 Impact angle control guidance law with look angle constraint . . . . . . . . 74 4.2.1 Look angle shaping based on nonlinear formulation . . . . . . . . . 74 ix 4.2.2 Design of the guidance law to follow the look angle pro_x000C_le . . . . . 76 4.3 Impact angle and time control guidance law with look angle constraint . . 79 4.3.1 Calculation of time-to-go . . . . . . . . . . . . . . . . . . . . . . . . 79 4.3.2 Impact time control based on time-to-go calculation . . . . . . . . . 82 4.4 Numerical simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.4.1 Performance analysis of the proposed guidance law . . . . . . . . . 86 4.4.2 Performance comparison with other guidance laws in realistic scenarios 89 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Abstract (in Korean) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105Docto

    ํˆฌ์ž์ฃผ์ฒด๋ณ„ ๊ฑฐ๋ž˜ํŒจํ„ด์— ๊ด€ํ•œ ์—ฐ๊ตฌ : ๊ฐ€์น˜ํฌํŠธํด๋ฆฌ์˜ค์™€ ์„ฑ์žฅํฌํŠธํด๋ฆฌ์˜ค๋ฅผ ํ†ตํ•œ ์ฆ๊ฑฐ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ฒฝ์˜ํ•™๊ณผ ๊ฒฝ์˜ํ•™์ „๊ณต,2000.Maste
    corecore