Explainable Solar Irradiation Forecasting Based on Conditional Random Forests

㫆

㫆Ị⿖

⧲

⧲►

䙂

䙂⩞㓺䔎

₆

₆⹮㦮

㍺

㍺ⳛ

Ṗ

Ṗ⓻䞲

㧒

㧒㌂⨟

㡞

㡞䁷

G

Explainable Solar Irradiation Forecasting Based on

Conditional Random Forests

Jihoon Moon, Eenjun Hwang

School of Electrical Engineering, Korea University 殚 殚 檃檃 䌲㟧ὧ ⹲㩚㦖 㧊㌆䢪䌚㏢ ⺆㿲⪲ 㧎䞲 ₆䤚 ⼖䢪㠦 ╖㦧䞮⓪ 㭒㣪 㑮┾㦒⪲ 㧎㔳♮㠊 㑮㣪㢖 䞚㣪㎇㧊  ỿ䞮Ợ 㯳Ṗ䞮ἶ 㧞┺. 㾲㩗㦮 䌲㟧ὧ ⹲㩚 㔲㓺䎲㦮 㤊㡗㦚 㥚䟊㍲⓪ 㩫ᾦ䞲 㩚⩻㑮㣪 ⹥ 䌲㟧ὧ ⹲㩚⨟ 㡞䁷 ⳾◎㧊 㣪ῂ♮Ⳇ, 㡾☚ ⹥ 㧒㌂⨟㦖 䌲㟧ὧ ⹲㩚⨟ 㡞䁷 ⳾◎㦮 䞚㑮㩗㧎 㧛⩻ ⼖㑮㧊┺. 䞮㰖Ⱒ, 䞲ῃ ₆㌗㼃㦮 ☯⍺㡞⽊⓪ 㧒㌂⨟㠦 ὖ䞲 㡞䁷Ṩ㦚 㩲Ὃ䞮㰖 㞠㞚 㩫ᾦ䞲 䌲㟧ὧ ⹲㩚⨟ 㡞䁷 ⳾◎㦚 ῂ㿫䞮⓪ ộ㦖 㠊⪋┺. 㧊⯒ 㥚䟊 㧒㌂⨟ 㡞䁷 ₆⻫㠦 ὖ䞲 Ⱔ㦖 㡆ῂ ㌂⪖Ṗ ⽊ἶ♮ἶ 㧞㰖Ⱒ, ┺㑮㦮 㡆ῂ✺㦖 㿿⿚䞲 ◆㧊䎆 ㎡㦚 㧊㣿䞮㡂 㧒㌂⨟ 㡞䁷 ⳾◎㦚 Ṳ⹲ 䞮㡖┺. 㽞₆ 䌲㟧ὧ ⹲㩚 㔲㓺䎲 㤊㡗㦚 㥚䟊㍲⓪ ⿞㿿⿚䞲 ◆㧊䎆 ㎡㦚 㧊㣿䞲 㡞䁷 ⳾◎ Ṳ⹲㧊 䞚㣪䞮⋮ 㧊㠦 ╖䞲 ㌂⪖⓪ ⿞㿿⿚䞮┺. ⽎ ⏒ⶎ㦖 㔺㩲 䌲㟧ὧ ⹲㩚 㔲㓺䎲㠦㍲ 㑮㰧♲ ⿞㿿⿚䞲 ◆㧊䎆 ㎡㦚 㧊㣿䞲 ┾₆ 㧒㌂⨟ 㡞䁷 ₆⻫㦚 㩲㞞䞲┺. Ⲓ㩖, ₆㌗㼃 ☯⍺㡞⽊㦮 ┺㟧䞲 ₆㌗ 㣪㧎 ✺㦚 㧊㣿䞮㡂 㧒㌂⨟ 㡞䁷 ⳾◎㦚 㥚䞲 㧛⩻ ⼖㑮⯒ ῂ㎇䞲┺. ┺㦢㦒⪲, 㫆Ị⿖ ⧲► 䙂⩞㓺䔎⯒ 㧊㣿䞮㡂 㧒㌂⨟ 㡞䁷 ⳾◎㦚 ῂ㎇䞮Ⳇ, ㍺ⳛ Ṗ⓻䞲 㧒㌂⨟ 㡞䁷㈦Ⱒ 㞚┞⧒ ▪㤇▪ Ⱔ㦖 ◆㧊䎆 ㎡㦚 䞯㔋䞮₆ 㥚䟊 㔲Ἒ㡊 ᾦ㹾Ỗ㯳㦚 㑮䟟䞲┺. 㔺䠮 ἆὒ, 㩲㞞䞲 ₆⻫㦖 ┺⯎ 㡞䁷 ₆⻫✺⽊┺ ⏨㦖 㡞䁷 㩫䢫☚⯒ ⽊㧒 ㈦Ⱒ 㞚┞⧒ ㍺ⳛ Ṗ⓻䞲 㡞䁷 ἆὒ⯒ 㩲㔲䞶 㑮 㧞㦢㦚 ⽊㡂㭖┺. 1. 昢昢 嵦 㾲⁒ ₆䤚 ⼖䢪 ⹥ 㠦⍞㰖 ⿖㫇 ⶎ㩲⯒ ╖゚䞮₆ 㥚䟊 㔶㨂㌳ 㠦⍞㰖(Renewable Energy)⯒ 㩗⁏ 䢲㣿䞲 㓺Ⱎ䔎 ⁎Ⰲ✲ ₆㑶㦮 ὖ㕂㧊 䄺㰖ἶ 㧞┺[1]. 㓺Ⱎ䔎 ⁎Ⰲ✲(Smart Grid)⓪ 㩫⽊䐋㔶₆㑶(ICT: Information and Communication Technologies)㦚 ₆㫊㦮 㩚⩻ⰳὒ 㩧⳿ 䞮㡂 㠦⍞㰖 䣾㥾㦚 㾲㩗䢪䞮⓪ ₆㑶㧊┺[1,2]. 㔶㨂㌳ 㠦⍞㰖⓪ 㓺Ⱎ䔎 ⁎Ⰲ✲㦮 䟋㕂 㣪㏢ 㭧 䞮⋮㧊Ⳇ, 䌲㟧ὧ(PV: Photovoltaics), 䛣⩻ ❇ὒ ṯ㦖 㻲㡆 㧦㤦㦚 䐋䟊 ⳿㩗㠦 ➆⧒ 㩚₆ ㌳㌆㧊 Ṗ⓻䞮┺[3]. 䌲㟧ὧ ⹲㩚㦖 ὋṚ 㩲㟓 㠜㧊 ㍺䂮䞶 㑮 㧞⓪ 㧻㩦㧊 㧞㠊, 㧊㢖 ὖ⩾♲ ₆㑶㧊 ザ⯊Ợ ⹲㩚䞮ἶ 㧞┺[1,3]. 䌲㟧ὧ ⹲㩚 㔲㓺䎲㦖 ┺㟧䞲 ₆㌗ 㣪㧎㦒⪲ 㧎䟊 ⹲㩚㠦 䋂Ợ 㡗䟻㦚 ⹱㦒Ⳇ, 㧒㌂⨟(Solar Irradiation)㦖 䌲㟧ὧ ⹲㩚㦮 㭧㣪䞲 㣪㧎㧊┺[4]. ⁎⩂⋮ ₆㌗㼃㦮 ☯⍺㡞⽊⓪ ₆㡾, 㔋☚ ❇ὒ ṯ㦖 ₆㌗ 㣪㧎㦮 㡞䁷 Ṩ㦖 㩲Ὃ䞮㰖Ⱒ 㧒㌂⨟㦮 㡞䁷Ṩ㦖 㩲Ὃ䞮㰖 㞠⓪┺ [5]. ➆⧒㍲, ῃ⌊ 䌲㟧ὧ ⹲㩚 㔲㓺䎲㦮 㤊㡗㦚 㥚䟊 ㍲⓪ 㩫䢫䞲 㧒㌂⨟ 㡞䁷 ⳾◎㧊 䞚㣪䞮┺. ⁎Ⰲ䞮㡂,

㧎Ὃ㰖⓻(AI: Artificial Intelligence) ₆㑶 ₆⹮㦮 㧒㌂⨟ 㡞䁷 ₆⻫㠦 ὖ䞲 Ⱔ㦖 㡆ῂṖ 㑮䟟♮㠞┺[3-5]. ┺㑮㦮 㡆ῂ✺㦖 㧒㩫 ₆Ṛ 㧊㌗㦮 㿿⿚䞲 ◆㧊䎆 ㎡㦚 ㌂㣿䞮㡂 㡞䁷 ⳾◎ ῂ㎇ ⹥ 㡞䁷 ㎇⓻ 䘟Ṗ⯒ 㑮䟟䞮㡖㦒⋮, ⿞㿿⿚䞲 ◆㧊䎆 ㎡㦚 ㌂㣿䞮㡂 㧎Ὃ 㰖⓻ ₆㑶㦚 ₆⹮㦒⪲ 㧒㌂⨟㦚 㡞䁷䞲 ㌂⪖⓪ ⹎⹎ 䞮┺. ➆⧒㍲, 㽞₆ 䌲㟧ὧ ⹲㩚 㔲㓺䎲㦮 䣾㥾㩗㧎 㤊㡗㦚 㥚䟊㍲⓪ ⿞㿿⿚䞲 ◆㧊䎆 ㎡㦚 䐋䟊 㩫ᾦ䞲 㡞䁷 ⳾◎㦚 ῂ㎇䞶 䞚㣪Ṗ 㧞┺. 㦮㌂ἆ㩫⋮ⶊ ₆⹮ 㞢ἶⰂ㯮✺㦖 㧧㦖 ◆㧊䎆 ㎡㠦㍲☚ Ⱒ㫇㓺⩂㤊 㡞䁷 ㎇⓻㧊 Ṗ⓻䞮┺[6,7]. ⽎ ⏒ⶎ㦖 ⿞㿿⿚䞲 ◆㧊䎆 ㎡㦚 㧊㣿䞮㡂 㫆Ị⿖ ⧲► 䙂⩞㓺䔎(CRF: Conditional Random Forests) ₆⹮㦮 㧒㌂⨟ 㡞䁷 ₆⻫㦚 㩲㞞䞮ἶ, 㡞䁷 ㎇⓻㦚 ┺㭧㍶䡫 䣢‖(MLR: Multiple Linear Regression) ⹥ ┺㟧䞲 㦮㌂ ἆ㩫⋮ⶊ ₆⹮㦮 㞢ἶⰂ㯮✺ὒ ゚ᾦ䞲┺. ⽎ ⏒ⶎ㦮 㭒㣪 ₆㡂☚⓪ 㞚⧮㢖 ṯ┺. y 㫆Ị⿖ ⧲► 䙂⩞㓺䔎⯒ ₆⹮㦒⪲ 㡞䁷 ⳾◎㦚 ῂ㿫䞮㡂 ┺㭧 ┾₆ 㧒㌂⨟ 㡞䁷㦚 㑮䟟䞲┺. y ῃ⌊ 䌲㟧ὧ ⹲㩚 㔲㓺䎲㦮 㩗㣿 Ṗ⓻㎇㦚 㥚䟊

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₆㌗㼃㦮 ☯⍺㡞⽊㠦 䙂䞾♲ 7 Ṗ㰖 ₆㌗ 㣪㧎㦚 ⳾⚦ ἶ⩺䞲┺. y 㡞䁷 ⳾◎㦮 ⼖㑮 㭧㣪☚(Variable Importance)㢖 㔲Ἒ㡊 ᾦ㹾Ỗ㯳㦚 㧊㣿䞮㡂 㡞䁷Ṩ㦚 ☚㿲䞮⓪ ὒ㩫㦚 ㍺ⳛ䞲┺. ⽎ ⏒ⶎ㦮 ⋮Ⲏ㰖 ⿖⿚㦖 㞚⧮㢖 ṯ┺. 2 㧻㠦㍲⓪ 㧒㌂⨟ 㡞䁷 ⳾◎㦚 㥚䞲 㧛⩻ ⼖㑮 ⹥ ⳾◎ ῂ㎇㠦 ╖䟊 㧦㎎䧞 ₆㑶䞲┺. 3 㧻㠦㍲⓪ 㡞䁷 ⳾◎㦮 㡞䁷 ㎇⓻㦚 ゚ᾦ ⹥ 䘟Ṗ䞮₆ 㥚䞲 㔺䠮 ὒ㩫㦚 ₆㑶䞮ἶ 㧊⯒ ⏒㦮䞲┺. 4 㧻㠦㍲⓪ ἆ⪶ὒ 䟻䤚 㡆ῂ ⹿䟻㦚 㩲㔲䞾㦒⪲ ⽎ ⏒ⶎ㦮 ⊳㦚 ⱐ⓪┺. 2. 沂沂斲峏 欎猧 微塾 割昷 ⿞㿿⿚䞲 ◆㧊䎆 ㎡㦚 㧊㣿䞮㡂 㡞䁷 ⳾◎㦚 ῂ㎇ 䞮₆ 㥚䟊, 㔺㩲 ╖㩚㠦 㧞⓪ 䌲㟧ὧ ⹲㩚 㔲㓺䎲㦮 㧒㌂⨟ ◆㧊䎆⯒ 㑮㰧䞮㡖┺. 㑮㰧♲ ◆㧊䎆 ₆Ṛ㦖 2018 ⎚ 6 㤪⪲ 1 ╂ 䂮㦮 ◆㧊䎆㧊Ⳇ, 㡺㩚 6 㔲⿖䎆 㩖⎗ 8 㔲₢㰖㦮 㔺䁷Ṩ㦒⪲ ῂ㎇♮㠊 㧞┺. 䚲 1 㠦 㑮㰧♲ ◆㧊䎆㦮 䐋Ἒ㩗 ⿚㍳ ἆὒ⯒ ⋮䌖⌊㠞┺. ڗ䚲ٻڌڙٻ㑮㰧♲ٻ◆㧊䎆㦮ٻ䐋Ἒ㩗ٻ⿚㍳ٻἆὒڃ┾㥚ڕٻڲڊۈڍ_ڄٻ ₆㑶ٻٻ䐋ἚἚ⻫ٻ 䐋Ἒ⨟ٻٻṨٻٻ 䘟‶ٻ ڎڎڋډڋڒٻ 䚲㭖ٻ㡺㹾ٻ ڌڍډڔڎٻ 㭧㞯Ṩٻ ڍڐڏډڐڋٻ 䚲㭖ٻ䘎㹾ٻ ڍڒڏډڎڐٻ ⻪㥚ٻ ړڋڐٻ 㾲㏢Ṩٻ ڋٻ 㾲╖Ṩٻ ړڋڐٻ 䞿ٻ ڌڏړڐڍڔډڏڋٻ ὖ䁷㑮ٻ ڏڐڋٻ ٻ 2.1. 沋崫 懆朞 割昷 㡞䁷 ⳾◎㦚 㥚䞲 㧛⩻ ⼖㑮⯒ ῂ㎇䞮₆ 㥚䟊 ₆㌗ 㼃㦮 ☯⍺㡞⽊㠦㍲ 㩲Ὃ䞮⓪ ṫ㑮䡫䌲, 㔋☚, ṫ㑮⨟, 䞮⓮㌗䌲, ₆㡾, 䛣䟻, 䛣㏣㦮 㔺䁷Ṩ㦚 ₆㌗㧦⬢Ṳ⹿ 䙂䎎㠦㍲ 㑮㰧䞮㡖┺. 㡂₆㍲, ṫ㑮䡫䌲㢖 䞮⓮㌗䌲⓪ ⻪㭒䡫 ◆㧊䎆⪲ 㧊⬾㠊㰖Ⳇ, ṫ㑮䡫䌲⓪ ゚Ṗ 㢪㦚 ➢㠦⓪ 1, ⁎⩝㰖 㞠㦒Ⳋ 0 㧎 ⳛ⳿䡫 ◆㧊䎆⪲ ῂ㎇ ♮㠊 㧞┺. 䞮⓮㌗䌲⓪ Ⱗ㦢, ῂ⯚ 㫆⁞, ῂ⯚ Ⱔ㦢, 䦦Ⱂ㦚 ṗ 1 ⿖䎆 4 ₢㰖⪲ 䚲₆䞲 㑲㍲䡫 ◆㧊䎆⪲ ῂ㎇♮㠊 㧞┺. ⋮Ⲏ㰖 㔺䁷Ṩ㧎 㔋☚, ṫ㑮⨟, ₆㡾, 䛣䟻, 䛣㏣㦖 㡆㏣䡫 ◆㧊䎆㦮 䔏㰫㦚 Ṗ㰖ἶ 㧞┺. 㔲Ṛ 㩫⽊⯒ ⹮㡗䞮₆ 㥚䟊, 6 㔲⿖䎆 20 㔲₢㰖 㽳 15 㔲Ṛ Ṛỿ㠦 ╖䟊 ⳛ⳿ 㻯☚⪲ ◆㧊䎆 ㎡㦚 ῂ㎇ 䞮㡖┺. 㧊⓪ 㞚䂾ὒ 㩖⎗㠦⓪ 㧒㌂⨟㧊 㩗ἶ 㡺䤚 㔲Ṛ╖㠦⓪ 㧒㌂⨟㧊 Ⱔ㦖 㧒㌂⨟㦮 䔏㩫 㔲Ṛ╖㦮 䔏㰫㦚 ▪㤇 䣾ὒ㩗㦒⪲ ⹮㡗䞶 㑮 㧞┺. 㧊㈦Ⱒ 㞚┞⧒, ὒỆ 㧒㌂⨟ 䕾䎊 ⹥ 㿪㎎⯒ ⹮㡗 䞮₆ 㥚䟊, 㡞䁷 㔲㩦㠦㍲ ὒỆ 2 㧒㦮 㧒㌂⨟ὒ 㔋☚, ṫ㑮⨟, 䞮⓮㌗䌲, ₆㡾, 䛣㏣, 䛣䟻㦒⪲ 㽳 14 Ṳ㦮 㧛⩻ ⼖㑮⯒ ῂ㎇䞮㡖┺. ⽎ ⏒ⶎ㠦㍲ ἶ⩺䞲 㧛⩻ ⼖㑮⓪ 㽳 36 Ṳ㧊Ⳇ 䚲 2 㠦 ₆㑶䞮㡖┺. ڗ䚲ٻڍڙٻ㡞䁷ٻ⳾◎㦮ٻ㧛⩻ٻ⼖㑮ٻῂ㎇ٻ⹥ٻ䔏㰫ٻ IV # 㧛⩻ ⼖⼖㑮 (䔏䔏㰫) IV # 㧛⩻ ⼖⼖㑮 (䔏䔏㰫) IV01 6 㔲 (ⳛ⳿䡫) IV19 2 㧒 㩚 ₆㡾 (㡆㏣䡫) IV02 7 㔲 (ⳛ⳿䡫) IV20 2 㧒 㩚 䛣䟻 (㡆㏣䡫) IV03 8 㔲 (ⳛ⳿䡫) IV21 2 㧒 㩚 䛣㏣ (㡆㏣䡫) IV04 9 㔲 (ⳛ⳿䡫) IV22 2 㧒 㩚 㧒㌂⨟ (㡆㏣䡫) IV05 10 㔲 (ⳛ⳿䡫) IV23 1 㧒 㩚 㔋☚ (㡆㏣䡫) IV06 11 㔲 (ⳛ⳿䡫) IV24 1 㧒 㩚 ṫ㑮⨟ (㡆㏣䡫) IV07 12 㔲 (ⳛ⳿䡫) IV25 1 㧒 㩚 䞮⓮㌗䌲 (㑲㍲䡫) IV08 13 㔲 (ⳛ⳿䡫) IV26 1 㧒 㩚 ₆㡾 (㡆㏣䡫) IV09 14 㔲 (ⳛ⳿䡫) IV27 1 㧒 㩚 䛣䟻 (㡆㏣䡫) IV10 15 㔲 (ⳛ⳿䡫) IV28 1 㧒 㩚 䛣㏣ (㡆㏣䡫) IV11 16 㔲 (ⳛ⳿䡫) IV29 1 㧒 㩚 㧒㌂⨟ (㡆㏣䡫) IV12 17 㔲 (ⳛ⳿䡫) IV30 ṫ㑮䡫䌲 (ⳛ⳿䡫) IV13 18 㔲 (ⳛ⳿䡫) IV31 㔋☚ (㡆㏣䡫) IV14 19 㔲 (ⳛ⳿䡫) IV32 ṫ㑮⨟ (㡆㏣䡫) IV15 20 㔲 (ⳛ⳿䡫) IV33 䞮⓮㌗䌲 (㑲㍲䡫) IV16 2 㧒 㩚 㔋☚ (㡆㏣䡫) IV34 ₆㡾 (㡆㏣䡫) IV17 2 㧒 㩚 ṫ㑮⨟ (㡆㏣䡫) IV35 䛣䟻 (㡆㏣䡫) IV18 2 㧒 㩚 䞮⓮㌗䌲 (㑲㍲䡫) IV36 䛣㏣ (㡆㏣䡫) 2.2 欎猧 微塾 割昷 ⽎ 㡆ῂ⓪ ⧲► 䙂⩞㓺䔎㢖 㥶㌂䞮㰖Ⱒ ┺⯎ 㩧⁒ ⹿㔳㦚 Ṭ⓪ 㫆Ị⿖ ⧲► 䙂⩞㓺䔎⯒ 㧊㣿䞮㡂 ┾₆ 㧒㌂⨟ 㡞䁷 ⳾◎㦚 ῂ㎇䞲┺. 㧊⩂䞲 㧊㥶⪲ 㫆Ị⿖ ⧲► 䙂⩞㓺䔎㦮 ⋮ⶊ ῂ㫆⓪ ⧲► 䙂⩞㓺䔎㦮 ⋮ⶊ ῂ㫆⽊┺ ◆㧊䎆⯒ 䘎䟻㩗㦒⪲ 䞯㔋䞮㰖 㞠㦒⸖⪲, 䘟Ṗ 㰧䞿(Test Set)㠦㍲ 㿲⩻ ⼖㑮⯒ 㡞䁷䞶 ➢, 䤞⩾ 㰧䞿(Training Set)㠦㍲ ⳾◎ 䞯㔋㦮 ὒ㩗䞿(Overfitting) ⶎ㩲 䟊ἆ㠦 ▪ 㩗䞿䞮₆ ➢ⶎ㧊┺[6]. 㧊㈦Ⱒ 㞚┞⧒ 㡞䁷Ṩ㦚 䘟‶䢪䞮⓪ ⧲► 䙂⩞㓺䔎㦮 ⋮ⶊ ῂ㫆㢖 ╂Ⰲ, 㫆Ị⿖ ⧲► 䙂⩞㓺䔎⓪ 㧛⩻ ⼖㑮㦮 Ṗ㭧䂮⯒ 䘟‶䢪䞮㡂 㡞䁷Ṩ㦚 ☚㿲䞮₆ ➢ⶎ㠦 ⼖㑮 㭧㣪☚⯒ ⋮䌖⌊㠞㦚 ➢, ▪㤇 䣾ὒ㩗㦒⪲ ⳾◎ ῂ㫆㠦 ὖ䟊 ㍺ⳛ㧊 Ṗ⓻䞮┺. ⽎ ⏒ⶎ㠦㍲⓪ 㩗㦖 ◆㧊䎆 ㎡㦚

324

┺⬾⸖⪲, Ⱔ㦖 ◆㧊䎆 ㎡㦚 㣪ῂ䞮⓪ 㕂䂋 㔶ἓⰳ (DNN: Deep Neural Network)㧊⋮ Boosting Ἒ㡊㦮 㞢ἶ Ⰲ㯮✺(㡞: XGBoost, LightGBM)㦚 ἶ⩺䞮㰖 㞠㞮┺[7]. ⡦䞲, ⽎ 㡆ῂ⓪ 㩦㹾 Ⱔ㦖 ◆㧊䎆 ㎡㦚 䞯㔋䞮₆ 㥚䟊 㔲Ἒ㡊 ᾦ㹾Ỗ㯳(TSCV: Time Series Cross-Validation)㦚 㩗㣿䞲┺. 㔲Ἒ㡊 ᾦ㹾Ỗ㯳㦖 ⁎Ⱂ 1 ὒ ṯ㧊 ṗ 㡞䁷 㔲㩦㠦㍲ 㡞䁷 ⳾◎㦮 䤞⩾ 㰧䞿㦖 㼁 㔲㩦⿖䎆 㧊㩚㦮 ὖ䁷 㔲㩦₢㰖 ῂ㎇♲┺. ⁎Ⰲ䞮㡂 ṗ 㡞䁷 㔲㩦㠦 ῂ㎇♲ 㡞䁷 ⳾◎㦖 1 㔲㩦 ⛺⿖䎆 15 㔲㩦 ⛺₢㰖 ┺㭧 㔲㩦㦮 㧒㌂⨟㦚 㡞䁷䞮Ⳇ, ṗ 㔲㩦㦮 㡞䁷 㩫䢫☚⯒ Ἒ㌆䞮ἶ 㧊⯒ 䘟‶Ṩ㦚 Ἒ㌆ 䞮㡂 㡞䁷 ⳾◎㦮 ㎇⓻㦚 䘟Ṗ䞲┺.

: Training data : Forecast time ܶ݅݉݁௡ ܶ݅݉݁௡ାଵ ܶ݅݉݁௡ାଶ ܶ݅݉݁௡ାଷ ܶ݅݉݁௡ାସ ܶ݅݉݁௡ାହ ܶ݅݉݁௡ା଺ 15 points yyy yyy yyy yyy yyy yyy yyy yyy yyy yyy yyy yyy yyy yyy ڃ⁎Ⱂٻڌڄٻ┺㭧ٻ㔲㩦ٻ㡞䁷㦚ٻ㥚䞲ٻ㔲Ἒ㡊ٻᾦ㹾Ỗ㯳ٻ ٻ 3. 柪柪竞 愕 磏儆 ⽎ٻ⏒ⶎ㠦㍲ٻ㩲㞞䞲ٻ㡞䁷ٻ⳾◎㦮ٻ㎇⓻㦚ٻ䘟Ṗ䞮₆ٻ 㥚䟊, 㩚㼊 ◆㧊䎆 ㎡㦚 㧒㧦⼚⪲ ⿚Ⰲ䞮㡖㦒Ⳇ, 6 㤪 1 㧒⿖䎆 2 㧒㦖 㧛⩻ ⼖㑮⯒ 㥚䟊 ◆㧊䎆⯒ 㧊㣿䞮Ⳇ, 3 㧒⿖䎆 23 㧒 㽳 3 㭒㦮 ₆Ṛ㦖 䤞⩾ 㰧䞿㦒⪲ 24 㧒 ⿖䎆 30 㧒 㽳 1 㭒⓪ 䘟Ṗ 㰧䞿㦒⪲ ㍶㩫䞮㡂 㔺䠮㦚 㰚䟟䞮㡖┺. 㡞䁷 ₆⻫㦒⪲ 㫆Ị⿖ ⧲► 䙂⩞㓺䔎㢖 㡞䁷 ㎇⓻㦚 ゚ᾦ䞮₆ 㥚䟊, ┺㭧㍶䡫䣢‖, 㦮㌂ἆ㩫 ⋮ⶊ(DT: Decision Tree), GBM(Gradient Boosting Machine), ⧲► 䙂⩞㓺䔎(RF: Random Forest)⪲ 㽳 4 Ṗ㰖㦮 ₆⻫ ✺㦚 㧊㣿䞮㡖┺. 㔺䠮 䢮ἓ㦖 R 3.5.1 ⻚㩚㦮 RStudio 1.1453 ⻚㩚㠦㍲ 㰚䟟䞮㡖┺. Grid Search ⯒ 䐋䟊 ṗ 㡞䁷 ₆⻫㠦 ὖ䞲 㾲㩗㦮 㽞ⰺṲ⼖㑮(Hyperparameter) Ṩ㦚 ㍶㩫䞮㡖㦒Ⳇ, 㧊⓪ 䚲 3 ὒ ṯ┺. ڗ䚲ٻڎڙٻṗٻ㡞䁷ٻ₆⻫㠦㍲ٻ㍶㩫♲ٻ㽞ⰺṲ⼖㑮㦮ٻṨٻ 㡞䁷 ₆₆⻫ 䕾䋺㰖 㽞ⰺṲ⼖㑮㦮 ṨṨ GBM gbm y distribution: gaussian y shrinkage: 0.001 y interaction.depth: 5 y bag.fraction: 0.5 y n.trees: 3000 y cv.folds: 5 RF randomForest y _y mtry: 12 ntree: 128 CRF party y _y mtry: 6 ntree: 500 㡞䁷 ⳾◎㦮 㡞䁷 㩫䢫☚⯒ 䘟Ṗ䞮₆ 㥚䟊, 㩲὇⁒ 䘟‶㩲὇㡺㹾(RMSE: Root Mean Square Error) ⹥ 䘟‶ 㩞╖㡺㹾(MAE: Mean Absolute Error)⯒ ㌂㣿䞮㡖㦒Ⳇ, 㧊⓪ 㔳 1, 2 㢖 ṯ┺. At_㢖Ft_{⓪ 㔺㩲 ὖ䁷♲ 㧒㌂⨟ὒ}

㧒㌂⨟ 㡞䁷Ṩ㦚 ⋮䌖⌊Ⳇ, n 㦖 ὖ䁷䂮㦮 㑮㧊┺.

RMSE = ುೀٻ(Ft _{࡝ A}t₎2 _{࢜ n (1)}

MAE = 1࢜ nٻശೀ̮Ft _{࡝ A}t_{̮ (2)}

䚲 4 㢖 5 ⓪ ṗ 㡞䁷 㔲㩦㠦 ὖ䞲 㡞䁷 ⳾◎✺㦮 RMSE 㢖 MAE 㦮 ἆὒ㧊┺. 䚲㠦㍲ ⿟Ợ(Red) 䚲₆♲ ộ㦖 ⌄㦖 㡞䁷 ㎇⓻㦚 ⋮䌖⌊Ⳇ 䛎⯊Ợ(Blue) 䚲₆♲ ộ㦖 㤆㑮䞲 㡞䁷 ㎇⓻㦚 ⋮䌖⌎┺. 㞚⧮㦮 䚲㠦㍲ ⋮䌖⌎ ộὒ ṯ㧊, 䡚㨂 㔲㩦ὒ 㡞䁷 㔲㩦㦮 Ṛỿ㧊 Ⲗ㠊㰞㑮⪳ 㡞䁷 ㎇⓻㧊 㩖䞮♲┺⓪ ộ㦚 䢫㧎䞶 㑮 㧞┺. ⡦䞲, 㫆Ị⿖ ⧲► 䙂⩞㓺䔎⓪ ┺⯎ 㡞䁷 ₆⻫ ⽊┺ ▪㤇 㤆㑮䞲 㡞䁷 ㎇⓻㦚 ⽊㧎┺⓪ ộ㦚 䢫㧎䞶 㑮 㧞㠞┺. ڗ䚲ٻڏڙٻṗٻ㡞䁷ٻ㔲㩦㠦㍲ٻ㡞䁷ٻ⳾◎✺㦮ٻڭڨڮڠٻ 㡞䁷ٻٻ㔲㩦ٻٻ ڨڧڭٻٻ ڟگٻٻ ڢڝڨٻٻ ڭڡٻٻ ڞڭڡٻٻ ڌٻ ڌڔڔډڐڑٻ ڌړڔډڋړٻ ڌڏڒډڑړٻ ڌڑڔډڏڋٻ ڌڎړډڒڒٻ ڍٻ ڍڍڒډڋڎٻ ڌڔڐډڔڌٻ ڌڑڋډڐڑٻ ڌڒڏډڔڍٻ ڌڐڎډڋڑٻ ڎٻ ڍڐڋډڍڍٻ ڍڋڒډڐڋٻ ڌڑړډڎڑٻ ڌڒړډڔڏٻ ڌڑڎډڋڋٻ ڏٻ ڍڑڐډڍڍٻ ڍڌڏډڋڏٻ ڌڒڎډړڒٻ ڌړڍډڍڒٻ ڌڑڐډړړٻ ڐٻ ڎڋڋډڍڏٻ ڍڍڌډڋڌٻ ڌڒڒډڒڎٻ ڌړڎډڐڍٻ ڌڑڑډڑړٻ ڑٻ ڎڋڑډڋڑٻ ڍڎڋډڎڎٻ ڌڒڔډڐڏٻ ڌړڎډڑڏٻ ڌڒڋډڋڑٻ ڒٻ ڎڌړډڒڒٻ ڍڎڍډڍڑٻ ڌړڌډڍڐٻ ڌړڎډڍڌٻ ڌڒڌډڎڐٻ ړٻ ڎڍڌډڑڔٻ ڍڍڔډڏڏٻ ڌړڍډڍڍٻ ڌړڏډڍڏٻ ڌڒڌډڑڋٻ ڔٻ ڎڍڎډڐڏٻ ڍڎڌډڎڌٻ ڌړڎډڋڍٻ ڌړڐډڌڍٻ ڌڑڔډڑڒٻ ڌڋٻ ڎڍڒډړڐٻ ڍڎڌډڌڎٻ ڌړڍډڔڌٻ ڌړڐډڑڏٻ ڌڒڌډڏڎٻ ڌڌٻ ڎڎڑډڌڎٻ ڍڍڑډړڎٻ ڌړڍډړڐٻ ڌړڑډڒڔٻ ڌڒڌډڋڐٻ ڌڍٻ ڎڎڐډڑڍٻ ڍڍڌډڏڒٻ ڌړڍډڏړٻ ڌړڑډڌڋٻ ڌڒڌډڋڌٻ ڌڎٻ ڎڎڑډړڑٻ ڍڌڑډړڋٻ ڌړڍډړڑٻ ڌړڐډڑڏٻ ڌڑڔډڎڒٻ ڌڏٻ ڎڎړډڌڔٻ ڍڌڋډڍڒٻ ڌړڍډڒڔٻ ڌړڐډڒڎٻ ڌڑڔډڌڎٻ ڌڐٻ ڎڎړډړڒٻ ڍڋڌډڍڎٻ ڌړڎډڋڎٻ ڌړڑډڌڋٻ ڌڑڔډڍڌٻ ڗ䚲ٻڐڙٻṗٻ㡞䁷ٻ㔲㩦㠦㍲ٻ㡞䁷ٻ⳾◎✺㦮ٻڨڜڠٻ 㡞䁷ٻٻ㔲㩦ٻٻ ڨڧڭٻٻ ڟگٻٻ ڢڝڨٻٻ ڭڡٻٻ ڞڭڡٻٻ ڌٻ ڌڏڋډڐڏٻ ڌڍڒډڐړٻ ڌڋڑډڍڒٻ ڌڍڐډڍڋٻ ڌڋڋډڐڍٻ ڍٻ ڌڐڏډڔڍٻ ڌڎڏډڑڒٻ ڌڌڏډڒڔٻ ڌڍڔډڌڑٻ ڌڌڋډڌڐٻ ڎٻ ڌڑڒډڋڐٻ ڌڏڌډڍڌٻ ڌڌڔډړڎٻ ڌڎڍډڌڌٻ ڌڌړډڎړٻ ڏٻ ڌڒڐډڋڔٻ ڌڏڐډڌړٻ ڌڍڎډڐړٻ ڌڎڎډڋڍٻ ڌڌڔډڔڎٻ ڐٻ ڌړړډړڋٻ ڌڏړډڔڎٻ ڌڍڐډړڎٻ ڌڎڎډڔڏٻ ڌڍڋډڐڌٻ ڑٻ ڌڔڑډڍڌٻ ڌڐڏډڍڔٻ ڌڍڑډڋڐٻ ڌڎڏډڋړٻ ڌڍڍډڐڎٻ ڒٻ ڍڋڐډڎڌٻ ڌڐڑډڍڎٻ ڌڍڑډڑڑٻ ڌڎڎډڌڋٻ ڌڍڍډڌڐٻ ړٻ ڍڋڔډڑڎٻ ڌڐڎډڏڋٻ ڌڍڑډڔڑٻ ڌڎڎډړڔٻ ڌڍڌډڒڌٻ ڔٻ ڍڌڋډڍڑٻ ڌڐڐډڎڋٻ ڌڍڒډڍړٻ ڌڎڏډڐڔٻ ڌڍڋډڍڎٻ ڌڋٻ ڍڌڍډڒڌٻ ڌڐڐډڐڒٻ ڌڍڒډڏڋٻ ڌڎڏډڒڏٻ ڌڍڍډڋڒٻ ڌڌٻ ڍڌڒډڎڐٻ ڌڐڌډڐڔٻ ڌڍڒډڌڔٻ ڌڎڐډڍڐٻ ڌڍڌډڑڌٻ ڌڍٻ ڍڌړډڌڌٻ ڌڏڑډڐڔٻ ڌڍڒډڌڐٻ ڌڎڐډڎڑٻ ڌڍڋډڏڏٻ ڌڎٻ ڍڌڔډڎڔٻ ڌڏڍډڐڑٻ ڌڍڒډڎڐٻ ڌڎڏډڒڌٻ ڌڌڔډڑڒٻ ڌڏٻ ڍڌڔډڔڐٻ ڌڎڑډړڒٻ ڌڍڑډړڏٻ ڌڎڏډڔڑٻ ڌڍڋډڎڐٻ ڌڐٻ ڍڍڋډڐڏٻ ڌڎڍډڎڏٻ ڌڍڒډڋڍٻ ڌڎڏډڔڔٻ ڌڌړډڐڏٻ ⁎Ⱂ 2 ⓪ ┾₆ 㧒㌂⨟ 㡞䁷 ⳾◎㦚 ῂ㎇䞮₆ 㥚䟊, 㫆Ị⿖ ⧲► 䙂⩞㓺䔎⯒ 㔲Ἒ㡊 ᾦ㹾Ỗ㯳㦚 㧊㣿䟊 䞯㔋 㔲䅲 ῂ㎇♲ 㡞䁷 ⳾◎㦮 ⼖㑮 㭧㣪☚⯒ 䧞䔎ⱋ ⁎⧮䝚⯒ 䐋䟊 㔲Ṛ╖⼚⪲ ⋮䌖⌎ ộ㧊┺. ⁎Ⱂ㠦㍲ ⿟Ợ(Red) 䚲₆♲ ộ㦖 ⌄㦖 ⼖㑮 㭧㣪☚⯒ ⋮䌖⌊Ⳇ, 䛎⯊Ợ(Blue) 䚲₆♲ ộ㦖 ⏨㦖 ⼖㑮 㭧㣪☚⯒ ⋮䌖⌒ ㈦Ⱒ 㞚┞⧒ 㭒㣪 ⼖㑮⧒ἶ 䕦┾䞶 㑮 㧞┺.

325

Date Hour Input Variables

IV0 1 IV0 2 IV0 3 IV0 4 IV0 5 IV0 6 IV0 7 IV0 8 IV0 9 IV1 0 IV1 1 IV1 2 IV1 3 IV1 4 IV1 5 IV1 6 IV1 7 IV1 8 IV1 9 IV2 0 IV2 1 IV22 IV2 3 IV2 4 IV2 5 IV2 6 IV2 7 IV2 8 IV2 9 IV3 0 IV3 1 IV3 2 IV3 3 IV3 4 IV3 5 IV36 24 June 2018 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 25 June 2018 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 26 June 2018 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 27 June 2018 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 28 June 2018 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 29 June 2018 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 30 June 2018 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ڃ⁎Ⱂٻڍڄٻṗٻ㡞䁷ٻ㔲㩦㠦㍲ٻ㡞䁷ٻ⳾◎㦮ٻ⼖㑮ٻ㭧㣪☚ٻ ⁎Ⱂ 2 㠦㍲ 䢫㧎䞶 㑮 㧞❅㧊, ὒỆ 2 㧒㦮 㧒㌂⨟ ὖ䁷䂮⓪ 㡞䁷 ⳾◎㠦㍲ ⰺ㤆 㭧㣪䞲 㧛⩻ ⼖㑮㧊Ⳇ, 㔺㩲 ┾₆ 㧒㌂⨟㦚 㡞䁷䞶 ➢ 㭒㣪 㣪㧎㧊⧒⓪ ộ㦚 㞢 㑮 㧞┺. ⡦䞲, 2018 ⎚ 6 㤪 27 㧒 㧊䤚⪲ ṫ㑮䡫䌲 ⹥ ṫ㑮⨟㦮 ⼖㑮 㭧㣪☚Ṗ ⏨㞚㪢┺⓪ ộ㦚 䢫㧎䞶 㑮 㧞┺. 㧊⓪ 2018 ⎚ 6 㤪 1 㧒⿖䎆 27 㧒 㡺䤚₢㰖 ゚Ṗ 㡺㰖 㞠㞚 Ṩ㧊 0 㦒⪲ 䁷㩫♮㠊 㡞䁷 ⳾◎㦚 䞯㔋䞶 ➢ 㭧㣪䞲 ⼖㑮⧒⓪ ộ㦚 䕦┾䞮㰖 ⴑ䟞㦒⋮, ゚Ṗ 㡾 㔲㩦⿖䎆⓪ ゚⪲ 㧎䟊 㧒㌂⨟㧊 㠜┺⓪ ộ㦚 㡞䁷 ⳾◎ 䞯㔋㠦 㧎㰖䞮ἶ 㧊㠦 ὖ䞲 Ṗ㭧䂮⯒ ⏨㧚 㦒⪲ ⼖㑮 㭧㣪☚Ṗ ⏨㞚㪢┺⓪ ộ㦚 䢫㧎䞮㡖┺. ⁎ 㣎㠦☚ 䞮⓮㌗䌲㢖 ₆㡾㦖 㧒㌂⨟ 㡞䁷 ⳾◎㦮 㭒㣪 ⼖㑮⧒⓪ ộ㦚 䢫㧎䞮㡖┺. 4. 冶冶 嵦 ⽎ ⏒ⶎ㦖 ⿞㿿⿚䞲 ◆㧊䎆 ㎡㠦㍲ 㩫䢫䞲 㧒㌂⨟ 㡞䁷㦚 㑮䟟䞮₆ 㥚䟊, 㫆Ị⿖ ⧲► 䙂⩞㓺䔎 ₆⹮㦮 ┺㭧 ┾₆ 㧒㌂⨟ 㡞䁷 ₆⻫㦚 㩲㞞䞮㡖┺. 䌲㟧ὧ ⹲㩚 㔲㓺䎲㠦 㩗㣿 Ṗ⓻㎇㦚 ⏨㧊₆ 㥚䟊, ₆㌗㼃㦮 ☯⍺㡞⽊㠦㍲ 㩲Ὃ䞮⓪ 㩫⽊⯒ 㧊㣿䞮㡂 㡞䁷 ⳾◎㦮 㧛⩻ ⼖㑮⯒ ῂ㎇䞮㡖┺. ┺㦢㦒⪲ 㩗㦖 ◆㧊䎆 ㎡㠦 ㍲☚ 䣾ὒ㩗㦒⪲ ⳾◎㦚 䞯㔋䞶 㑮 㧞⓪ 㫆Ị⿖ ⧲► 䙂⩞㓺䔎⯒ 㧊㣿䞮㡂 㡞䁷 ⳾◎㦚 䞯㔋䞮ἶ, ▪㤇▪ Ⱔ㦖 ◆㧊䎆㦮 䞯㔋ὒ 㾲⁒ 㧒㌂⨟ 䕾䎊 ⹥ 㿪㎎⯒ ⹮㡗䞮₆ 㥚䟊 㔲Ἒ㡊 ᾦ㹾Ỗ㯳㦚 㩗㣿䞮㡖┺. 㡞䁷 ⳾◎㦖 㩦 㡞䁷 ⹿㔳㧊 㞚┢ ┺㭧 㡞䁷 ⹿㔳㦒⪲ 1 㔲㩦 ⛺ 㔲㩦⿖䎆 15 㔲㩦 ⛺ 㔲㩦₢㰖 㽳 15 㔲㩦㦚 㡞䁷䞮㡂 㡞䁷 ⿞䢫㔺㎇㦚 ╖゚䞮⓪ ◆ ☚㤖㦚 㭚 㑮 㧞㠞┺. 㩲㞞䞲 㡞䁷 ₆⻫㦖 ┺㟧䞲 㡞䁷 ₆⻫✺ὒ ゚ᾦ䞮㡂 ▪㤇 㤆㑮䞲 㡞䁷 ㎇⓻㦚 ⽊㡖㦒Ⳇ, ⼖㑮 㭧㣪☚⯒ 䐋䟊 ὒỆ 㧒㌂⨟ὒ ₆㡾, 䞮⓮㌗䌲 ❇㧊 䟻䤚 㧒㌂⨟㦚 㡞䁷䞶 ➢ 㭒㣪 ⼖㑮⧒⓪ ộ㦚 䢫㧎䞶 㑮 㧞㠞┺. ⽎ ⏒ⶎ㠦㍲⓪ 㔺㩲 㑮㰧♲ 䌲㟧ὧ ⹲㩚 㔲㓺䎲㦮 㧒㌂⨟ ◆㧊䎆Ṗ 䞲 ╂ 䂮Ⱒ 㑮㰧♮㠊 ┺㟧䞲 䢮ἓ㦮 㧒㌂⨟ ◆㧊䎆⯒ 䐋䟊 㔺䠮㦚 㰚䟟䞮₆Ṗ 㠊⩺㤶┺. 䟻䤚, 㧒㌂⨟ ◆㧊䎆⯒ 㑮㰧䞮㡂 ┺㟧䞲 ₆Ṛ, 㰖㡃 ❇㦚 ἶ⩺䞮㡂 ⻪㣿㎇㦚 Ṗ㰞 㑮 㧞⓪ 㧒㌂⨟ 㡞䁷 ⳾◎㦚 Ṳ⹲䞶 Ἒ䣣㧊┺. 斲斲怾割 㧊 㡆ῂ⓪ 2019 ⎚☚ 㩫⿖(ὒ䞯₆㑶㩫⽊䐋㔶⿖)㦮 㨂㤦㦒⪲ 䞲ῃ㡆ῂ㨂┾-㠦⍞㰖䋊⧒㤆✲₆㑶Ṳ⹲㌂㠛 (No. 2019M3F2A1073184) ⹥ 䞲ῃ㩚⩻Ὃ㌂㦮 2018 ⎚ 㹿㑮 㠦⍞㰖 Ệ㩦╖䞯 䋊⩂㓺䎆 ㌂㠛(No. R18XA05)㦮 㰖㤦㦚 ⹱㞚 㑮䟟♲ 㡆ῂ㧚. 焾処怾竒

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