Cicilio, Phylicia

Francisco, Alexis

Pike, Christopher

Wilber, Michelle

English

ScholarWorks@UA

Utility and Residential Solar Resource Assessment and Modeling for Alaska’s Railbelt Transmission SystemAlexis Francisco, Michelle Wilber, Christopher Pike, and Phylicia Cicilioafrrancisco2, mmwilber, cpike6, pcicilio@alaska.eduI. BACKGROUNDThe Alaska Railbelt Electric Grid• Electrical grid extending from Fairbanks to Homer, AK• Consumes >75% of the state’s electricityRailbelt Decarbonization Study• Explore Railbelt decarbonization pathways whiledelivering affordable and reliable electricity• Goal of 100% carbon-free energy by 2050• Solar PV technology- explore the potentialimplementation of solar PV systems as adecarbonization technologySolar Energy• Provides affordable, clean, and renewable energywhile reducing greenhouse gas (GHG) emissions• Classified as a variable renewable energy (VRE)• Production periodically fluctuates and dependenton meteorological conditionsSolar PV Value in Alaska• Increased solar reflection (albedo) off snow duringmelting season• Extended hours of sunlight in the summer• ~20 hours of daylight in the southcentral region• Net Energy Metering (NEM) program• “sell” excess energy produced from residential PVsystems back to grid for full or partial prices• Behind-the-meter (BTM PV) net energy metering (NEM)forecast for the Railbelt until 2050 developed forresidential solar• Power system modeling in PSS/e for utility and residentialPV• Hourly energy production for the year 2050 generated forresidential and utility-scale solar PV using the SystemAdvisor Model (SAM).SAM Model Settings• Performance Model: Photovoltaic PV Watts• No Financial Model• System Design - defaults except for the following• Fixed open rack • Tilt: 45 degrees• Azimuth: 180 degrees • Ground coverage ratio: 0.3• Module is bifacial • Albedo: 0.5Residential solar PV systems were modeled in PSS/e as adistributed energy resources aggregate (DER_A) modelattached to load buses. To estimate the Railbelt’sresidential PV growth from 2022 to 2050, several forecastmodels were generated and compared. Linear andexponential regression models were created from theRailbelt’s historical data from 2010 to 2021. ISO NewEngland’s (ISONE) historical and forecasted BTM PVcapacity were also used as a reference to generate aRailbelt forecast scaling values based on the ratio of peakloads in 2021. The five-year linear nameplate capacitygrowth of ISONE was estimated and divided by the peakload ratio of ISONE and the Railbelt. The plot to the rightillustrates the various forecast trendlines.2050 Railbelt Adoption Assumptions• Assumes 200,000 homes will install 5 kW residential PVII. METHODSIIIA. RESIDENTIAL SOLAR PVThis project is part of the Arctic Regional Collaboration forTechnology Innovation and Commercialization (ARCTIC) 2 Program -Innovation Network, an initiative supported by the Office of NavalResearch (ONR) Award #N00014-22-1-2049. This project is funded bythe state of Alaska FY23 economic development capital funding.AcknowledgementsSolar PV technology is an economical and environmentally critical option for decarbonization in Alaska’s Railbelt grid. Extended daylightsummer hours and albedo effects in winter and spring increase the value of solar in Alaska as well as the NEM system. Power system modelingof the utility-scale and residential solar is implemented using the power flow representation by WECC and as aggregated model DER_A. In bothPV systems sizes, the hourly outputs of the select locations and calculated nameplate capacities were simulated in a SAM Model.IV. CONCLUSIONIIIB. UTILITY SCALE SOLAR PV DEVELOPMENTSolar facility developments were selected at several locationsnear the Railbelt and assigned a calculated nameplate capacity.These nameplate capacities were simulated in the SystemAdvisor Model (SAM) to determine their hourly outputs. Thedynamic modeling guide recommended by the WesternElectricity Coordinating Council (WECC), shown below, wasimplemented in PSS/e for modeling of utility-scale PV plants.SAM PV utility-scale hourly output adjustments• Converted to MW• Scaled by 140% (x1.4) to account for DC-AC conversion• Limit generation by the nameplate capacity size oflocationExample of a SAM monthly profile for a 100 MW solar PV development in A Fairbanks, AK

Utility and Residential Solar Resource Assessment and Modeling for Alaska’s Railbelt Transmission System

https://scholarworks.alaska.edu/bitstream/11122/13197/1/CEM_Francisco_Poster.pdf

Utility and Residential Solar Resource Assessment and Modeling for Alaska’s Railbelt Transmission System

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