data streams for control · 2017-07-12 · data streams for control dr. marc mueller-stoffels...
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Data Streams for ControlDr. Marc Mueller-StoffelsProgram Director/R&D Lead, Power Systems Integration 2017 Alaska Wind-Diesel Workshop Fairbanks 2017
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“Ifwehavedata,let’slookatdata.Ifallwehaveareopinions,let’sgowithmine.”
–JimBarksdale,formerNetscapeCEO
Digi
tizat
ion
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hJp://www.mckinsey.com/industries/electric-power-and-natural-gas/our-insights/the-digital-uOlity-new-opportuniOes-and-challenges
Increased complexity
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Controls Automation is critical
• More objectives:• Cheapest • Most reliable • Least diesel utilization • Equitable demand management • Maintenance schedules • …
• More resources• Renewable generation • Energy storage • Demand management • …
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Controlled Elements20 40 60 80 100
Poss
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Com
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Test harness• 5-wire Distribution model
• 3p and 1p distributed resources (loads and generation)
• Phase imbalance impacts
• Objectives• Training environment for
optimization algorithms • Flexible experimental setup to
extract information • Driver for hardware-in-the-loop
emulation
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Ciric,etal.,2003
Phase balancing
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• Phase imbalance causes energy loss • Need to know
phase imbalance to fix• Control
distributed resources (loads, PV, etc.) to balance grid
Information from sparse data• Nonlinear Time-Series Analysis Methods• Powerful toolkits • Determine system state from
limited data • Proven in other areas to
provide state estimates/trending
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Mormann,etal.,ClinicalNeurophysiology,116(3),2005.
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0 200 400 600 800 1000 1200 14000
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Time [min]
Pow
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W]
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Customer Example: Demand Charges• Large customer
• 14 (!) individual services • 4 with demand charges
• Data: monthly utility bills• Energy use • Peak use
• Without more data:• Assess impact of combining all
demand meters • Potential annual savings: $20k
• Needed: time-series energy use data• Understand potential for load
leveling • Max. potential annual savings:
$130k
• Direct cost of not having data• ~ $100k/year
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Summary• Digitalization
• Convergence of data streams • New data streams • New use of existing data streams
• Microgrid applications• Better management of DER • Increases in technical and economic
efficiency • Novel approaches to sparse data problem?
Engineers like to solve problems. If there are no problems handily available, they will create their own problems.
- Scott Adams
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Thank you!Dr. Marc Mueller-StoffelsDirector, Power Systems Integration ProgramAlaska Center for Energy and PowerInstitute of Northern EngineeringUniversity of Alaska [email protected](907) 687 0259http://acep.uaf.edu
Partners:USDepartmentofEnergyUSDepartmentoftheInteriorUSDenaliCommissionUSEconomicDevelopmentAdministraOonUSOfficeofNavalResearchStateofAlaskaAlaskaEnergyAuthorityAlaskaPowerandTelephoneCordovaElectricCooperaOveCityofCordovaNomeJointUOlitySystemsKokhanokVillageCouncilCityofGalenaPowerandWaterCorporaOon,Darwin,AustraliaNaOonalRenewableEnergyLaboratorySandiaNaOonalLaboratoryLawrenceBerkleyNaOonalLaboratoryPacificNorthwestNaOonalLaboratoryTechnicalUniversityDarmstadt,GermanyABBShellHuntleyandAssociatesHatchAssociatesConsultantsOceanaEnergyLLC