using gis (geographic information system) to meet...
TRANSCRIPT
USING GIS (Geographic Information System)
TO MEET RENEWABLE ENERGY
AND TO FULFILL
THE BIM (Building Information Modelling)
IDEA
By. Hokkop Situngkir
Founder of IDNextLeader Foundation
Advisor for PT. Arenas
Advisor for PT. Daya Bumi Energi
Advisor for KUN Humanity System
Former Director of PT. Waskita Karya Energi
Indonesia in the Middle of Climate Change, Corbon Emission, Waste Crisis, and Forest Fire
Gambaran ratio elektrifikasi Indonesia 2019/2020
NASA : World at Night Portrait 2016/2017
Potential Distribution of Renewable Energy in Indonesia
Gambaran Saduran Proporsi Pembangkit EBT dan Non-EBT dalam Rencana Bauran Energi 56 GW, RUPTL PT. PLN 2018 – 2025 dan Kementrian ESDM EBTKE 2019
PLTA/M40% ≃ 6.000 MW
PLTP20% ≃ 3.000 MW
PLTS15% ≃ 750 MW
PLTBm10% ≃ 500 MW
PLTB15% ≃ 750 MW
PLTTd5% ≃ 75 MW
PLTU45% ≃ 20.227 MW
PLTU MT14% ≃ 6.445 MW
PLTG/MG/GU/MGU40% ≃ 17.931 MW
PLTD1% ≃ 36 MW
EBT
NON EBT
Total Pembangkit Tenaga Listrik
terpasang di Indonesia hingga
2019: 70 GW
Rencana pemerintah hingga
2025 menambah pembangkit
23 GW dengan 67% dari Fossil
Energy dan 33% dari Renewable
Energy
Dinamika Regulasi EBT dalam PERMEN tahun 2015-2020
PERMEN ESDM No. 4 TAHUN 2020
Kondisi Perizinan Indonesia Terkait Pengembangan EBT
Akuisisi Data Artikulasi DataAnalisis Data
▪ RGB [Red-Green-Blue]
Camera
▪ NIR Camera
▪ Crowd Source
▪ Apps
▪ Dashboards
▪ Cartography
▪ Spatial Statistics
▪ Automated Object
Recognition
▪ 3D Map / Contour
DIY and DIWODo-It-Yourself & Do-It-With-Others
▪ Memori Kolektif
▪ Dari ketidakpastianmenuju Potensi Presisi4.0
▪ Crowd Source
Potensi Energi
dalam Data
DATA SPASIAL & DATA ATRIBUT- Inventarisasi data- Analisis data- Informasi demografi- Konsep Perencanaan
RENEWABLE ENERGY
SOURCES
HYDRO
WIND
GEOTHERMAL
TYDAL
SOLAR
BIOMASS/WASTE to ENERGY
High tide dataTidal height measurementsWater Surface change data
River Flow Area and Sea Water MeetingRegion Electrification Ratio Data
Social Mapping
Countur MapsWind Direction Data Collection
Windrose ModelWind Flow Estimation
Compare to Climate DataRegion Electrification Ratio Data
Social Mapping
Countur MapsGeothermal data/Surface Heat
Volcano mappingGround level data
Region Electrification Ratio DataSocial Mapping
Region Electrification Ratio DataCountur Maps
Catchment Area/River Flow AreaCompare to Rain Station Data
Flow EstimationHead
Countur MapsCatchment Area
Plant Age and TypeRain Station Data/Climate change data
Thermal Data of Living ThingsRegion Electrification Ratio Data
Social Mapping
Countur MapsRadiation Intensity Data
Climate Change DataAngle of Light Falling dataRegion Electrification Data
Social Mapping
RENEWABLE ENERGY
SOURCES
COST ESTIMATIONDEVELOPMENT OF ELECTRICAL NETWORK INTERCONNECTIONS & DEMAND GROWTH SIMULATION
GIS meets BIM
GIS meets BIM (sampling on Hydro Power Plant)
Dalam Penyusunan Pra dan Feasibility Study diperlukan pembacaan dan akuisisi data yang komprehensif :- Titik lokasi dan koordinat, peta situasi- Mapping area lokasi, dari sisi waktu tempuh, jarak tempuh, jalan masuk dan area lokasi hingga ke mapping penduduk (sosial)- Gambaran Supply and Demand dan kondisi system interkoneksi PLN- Relasi dari pembangkit hingga ke supply GI ataupun GH bisa menjawab studi Interkoneksi dan studi Kelistrikan- Catchment Area di sepanjang DAS juga adalah sebuah hal yang mutlak secara data, dan bisa dikorelasikan dengan data climate dan juga curah
hujan harian- Jenis dan kondisi Catchment dari sisi planting wood, dan area batas hutan dan lain-lain- Kontur lokasi Catchment hingga detail kontur lokasi di titik pembangkit- Debit Rencana dapat diperhitungkan dengan integrasi data- Concept Design dapat dilakukan dengan mengacu pada variable Teknik yang bisa dimasukkan ke dalam platform design dan BIM- Volume pekerjaan secara estimasi juga bisa dilakukan dengan kolaborasi platform GIS dan BIM baik sebagai plotting design bahkan sampai ke
Estimasi Cost of ConstructionKombinasi GIS dan BIM ini bisa menghemat proses pembuatan FS hingga ke Konsep Design yang mengakibatkan adanya waktu yang efektif dan relative lebih singkat untuk mempercepat proses Perizinan. Dan dengan perizinan yang bisa dilakukan dengan konsep OSS diharapkan semua pekerjaanKonsultasi ini tidak memerlukan site visit dengan jumlah yang massif dan lain-lain. Konsultasi Teknik hanya diperlukan pada saat Detail Engineering Design
Platform yang digunakan :Google MapArcGISAutoCadWBS/CPM platformPlatform HidrologiPlatform EnergiDrone – Thermal type
USING GIS (Geographic Information System)
TO MEET RENEWABLE ENERGY
AND TO FULFILL
THE BIM (Building Information Modelling)
IDEA
TERIMAKASIH!!!
Location Intelligence for
Renewable Energy ResourcesSolution Strategist - Esri Indonesia
Session HighlightsLeveraging on location intelligence to uncover the potential of renewable energy resources
• Understanding the location and potential
• Leverage site suitability information
• Measure potential supply of a renewable energy resource (solar power case)
• Analyze variables predicting the potential of renewable energy resource (geothermal case)
• Monitor production and risk analysis in the project (geothermal case)
• Support stakeholders, break down silos, and enable efficient collaboration between teams
National Target Summary (Source: Kementerian ESDM Ditjen Energi Baru Terbarukan dan Konservasi Energi - EBTKE)
Solar PV added to the
installed capacity:
170 MWh
Increase capacity for
energy transition:
Decrease in coal, oil fuel and gas
Modeling Renewable Energy Potential Using GISBenefits of Renewable Energy
• Little to No Global Warming Emissions
• Improved Public Health and Environmental Quality
• A Vast and Inexhaustible Energy Supply
• Jobs and Other Economic Benefits
• Stable Energy Prices
• A More Reliable and Resilient Energy System
Union of Concerned Scientists: http://www.ucsusa.org/clean_energy/our-energy-choices/renewable-energy
1. Analysis on a local scale
2. Fine tuning of methodology
3. Broader analysis
Why GIS for Renewable Energy?GIS Utilization for Modeling Renewable Energy
Modeling Solar Power Potential
Modeling Solar Power PotentialLeveraging on location intelligence to uncover the potential of solar power
Leverage site suitability information with data enrichment: e.g.
NASA solar radiation global dataset, Population, Purchasing
Power, POIs
Modeling Solar Power Potential
• Create solar radiation layer (output in Wh/m2)
• Identify suitable rooftops for solar panel based on variable criteria
with default tools (slope, minimum solar radiation, building
orientation, rooftop size)
• Calculate usable solar radiation per building (Zonal Statistics)
• Convert solar radiation to potential power, account for energy
conversion efficiency (15%) and installation’s performance ratio
(86%) - US EPA
Leveraging on location intelligence to uncover the potential of solar power
Correlation Matrix of Geothermal Variables
ArcGIS
Correlation Matrix of Geothermal Variables Leveraging on location intelligence to analyze geothermal potential and energy production variables
• Enrich data with variables for analysis as attributes
• Call spatial and statistics libraries in R
• Calculate smoothed geothermal potential or energy
production rate in R (e.g. with Empirical Bayesian method)
and produce spatial output
• Execute hotspot analysis based on the rate calculated in R
• Create correlation matrix in R to evaluate attribute
relationships
Optimized hotspot analysis result
Correlation matrix result