Resource Planning Model: An Integrated Resource Planning and Dispatch Tool for Regional Electric Systems

Mai, Trieu; Drury, Easan; Newman, Alexandra M.; Bodington, N.; Lopez, Anthony; Perry, A.M.

doi:10.2172/1067943

Cited by 43 publications

(51 citation statements)

References 13 publications

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“…28 PVWatts: http://pvwatts.nrel.gov/ SAM: https://sam.nrel.gov/ PV-DesignPro: http://www.mauisolarsoftware.com/ PV*SOL: http://www.solardesign.co.uk/pv.php PVSyst: http://www.pvsyst.com/en/ most basic approach, EPPA applies a simple cost adder of $0.01/kWh to account for additional transmission requirements to access solar resources (Morris 2008). Both RPM and SWITCH-WECC use a flat cost per distance (e.g., dollar per megawatt-mile) of transmission required to connect solar resource to the existing grid (Mai et al 2013a;Johnston et al 2013). Several models-GCAM, NEMS, ReEDS and SEDS-use analyses based on a geographic information system (GIS) to apply additional solar resource transmission detail (Zhang et al 2010;EIA 2013;Short et al 2011;Short et al 2006).…”

Section: Assessing the Potential For Solar Powermentioning

confidence: 99%

“…US-REGEN (EPRI 2013) uses a clustering algorithm to select time blocks with similar load-wind-solar as well as extreme moments (e.g., the set of high load hours with low output from wind and solar). Certain models such as MARKAL, PLEXOS LT Plan and RPM have the benefit of allowing for user-defined temporal resolution (Loulou et al 2004;Energy Exemplar 2013;Mai et al 2013a). …”

Section: Dispatch (Value Of Energy At Time Delivered)mentioning

confidence: 99%

“…LIMES-EU uses an algorithm to select 12 characteristic days that are representative of temporal and spatial fluctuations (Haller et al 2012). RPM selects a week for each season that is most representative of "typical" seasonal electricity demand, i.e., the week with the lowest root mean square error deviation from the demand in each hour of the average week of the season (Mai et al 2013a). …”

Section: Dispatch (Value Of Energy At Time Delivered)mentioning

confidence: 99%

“…REMix (Scholz 2012) and SWITCH-WECC (Nelson et al 2012) assign a capacity value equal to the capacity factor in that hour or time block. RPM (Mai et al 2013a) uses a simplified net-load approach that estimates the capacity value as the ability of solar to reduce the peak load. Other models use exogenous estimates of capacity value.…”

Section: Resource Adequacy: Effective Load-carrying Capacitymentioning

confidence: 99%

See 3 more Smart Citations

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

Sullivan¹,

Newman²,

Margolis³

2014

Self Cite

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Section: Assessing the Potential For Solar Powermentioning

confidence: 99%

Section: Dispatch (Value Of Energy At Time Delivered)mentioning

confidence: 99%

Section: Dispatch (Value Of Energy At Time Delivered)mentioning

confidence: 99%

Section: Resource Adequacy: Effective Load-carrying Capacitymentioning

confidence: 99%

See 2 more Smart Citations

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

Sullivan¹,

Newman²,

Margolis³

2014

Self Cite

View full text Add to dashboard Cite

“…Utilities in the United States operate within synchronized electrical interconnections where new generation resources outside a utility's service territory can impact transmission line congestion and the price and accessibility of power transfers from other regions. Several recent studies have analyzed renewable resource build-out pathways and their impacts on power flow and marginal energy costs (Mai et al 2013;Milligan et al 2012;Lew et al 2010). These studies suggest that failing to account for out-of-state capacity expansion either directly or through dynamic boundary conditions can lead to sub-optimal investment within a utility's jurisdiction.…”

Section: Other Considerations For Solar In Capacity Expansion Models Andmentioning

confidence: 99%

Treatment of Solar Generation in Electric Utility Resource Planning

Sterling¹,

McLaren²,

Taylor³

et al. 2013

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Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches

Helistö

Kiviluoma

Holttinen

et al. 2019

WIREs Energy & Environment

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In the past, power system planning was based on meeting the load duration curve at minimum cost. The increasing share of variable generation (VG) makes operational constraints more important in the planning problem, and there is more and more interest in considering aspects such as sufficient ramping capability, sufficient reserve procurement, power system stability, storage behavior, and the integration of other energy sectors often through demand response assets. In VG integration studies, several methods have been applied to combine the planning and operational timescales. We present a four-level categorization for the modeling methods, in order of increasing complexity: (1a) investment model only, (1b) operational model only, (2) unidirectionally soft-linked investment and operational models, (3a) bidirectionally soft-linked investment and operational models, (3b) operational model with an investment update algorithm, and (4) co-optimization of investments and operation. The review shows that using a low temporal resolution or only few representative days will not suffice in order to determine the optimal generation portfolio. In addition, considering operational effects proves to be important in order to get a more optimal generation portfolio and more realistic estimations of system costs. However, operational details appear to be less significant than the temporal representation. Furthermore, the benefits and impacts of more advanced modeling techniques on the resulting generation capacity mix significantly depend on the system properties. Thus, the choice of the model should depend on the purpose of the study as well as on system characteristics. generation expansion planning, integration of renewable energy sources, operational constraints, power system planning, temporal representation | INTRODUCTIONPower systems can play a crucial role in decarbonizing energy systems as they can relatively easily integrate large amounts of renewable generation. However, the increasing amount of wind and solar power, as well as other forms of variable generation (VG), has a strong impact on the operation of power systems through the variability and uncertainty of wind speed (Wu et al.,

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Resource Planning Model: An Integrated Resource Planning and Dispatch Tool for Regional Electric Systems

Cited by 43 publications

References 13 publications

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

Treatment of Solar Generation in Electric Utility Resource Planning

Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches

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