2020
DOI: 10.1016/j.renene.2020.08.074
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A comparison of PV resource modeling for sizing microgrid components

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Cited by 8 publications
(5 citation statements)
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“…It was found that individual AI models had accuracies of around 10%, whereas hybrid models achieved accuracies near 5% of error in exchange for more computational resources and more extensive datasets. When considering storage also, the computational cost substantially increases for both the sizing of the components [215] and control of the energy flow [212,213], especially if the system considers more than one type of storage [216,217].…”
Section: Discussionmentioning
confidence: 99%
“…It was found that individual AI models had accuracies of around 10%, whereas hybrid models achieved accuracies near 5% of error in exchange for more computational resources and more extensive datasets. When considering storage also, the computational cost substantially increases for both the sizing of the components [215] and control of the energy flow [212,213], especially if the system considers more than one type of storage [216,217].…”
Section: Discussionmentioning
confidence: 99%
“…The ability of different renewable resources to meet Moloka'i's electrical load is evaluated using the Microgrid Component Optimization for Resilience (MCOR) tool, developed at PNNL [22]. MCOR uses a statistical model to simulate PV resources under a wide range of potential grid outage conditions, simulates microgrid operation for each of those profiles, and returns several different combinations of resources (including PV, batteries, and diesel generators) that can meet a site's electrical loads under all simulated outage conditions.…”
Section: B Microgrid Simulationmentioning
confidence: 99%
“…MCOR uses a statistical model to simulate PV resources under a wide range of potential grid outage conditions, simulates microgrid operation for each of those profiles, and returns several different combinations of resources (including PV, batteries, and diesel generators) that can meet a site's electrical loads under all simulated outage conditions. The details of the MCOR PV profile generation algorithm and microgrid operation simulation are discussed in detail in [22]. As MCOR is designed to evaluate PV resources, considering wind and wave required some modifications, which are discussed in II-C.…”
Section: B Microgrid Simulationmentioning
confidence: 99%
“…This has led to the many new approaches to assist in both power system planning and operations that would enable greater system resilience. These include the development of new metrics [9], [10]; new analytical methods for outage prediction [9], [12]; optimal placement, sizing, and design of microgrid systems [13]- [15]; evaluating the vulnerability of generation supply mix to different extreme weather conditions [16]- [18]; and the development of new methods to model the impact of natural hazards on power system infrastructure [19]. Related to hurricane threats in particular, work has been done to characterize power system fragility and simulate cascading faults caused by strong winds [20], [21].…”
Section: Introductionmentioning
confidence: 99%