2015
DOI: 10.1109/tpwrs.2014.2351374
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Generation Capacity Expansion Planning Under Hydro Uncertainty Using Stochastic Mixed Integer Programming and Scenario Reduction

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Cited by 89 publications
(44 citation statements)
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“…Further, operational decisions should be modeled during chronological sequences of timesteps within many study days. This allows direct modeling of choices that depend on the sequence of hours within a single day, such as unit commitment (slow and expensive power plant start/stop decisions), when to charge and discharge finite storage, or when to schedule time-shiftable demand within the day [8,9] --NEMS [10,11,12,13] --ReEDS [14] n/a LEAP + OseMOSYS [15,16] --Balmorel [17] ---E4 Simulation Tool [18] --US-REGEN (non-UC mode) [19] n/a US-REGEN (UC mode) [19] n/a Oemof [20,21] URBS [22,23] -PyPSA [24] Palmintier and Webster [25] -Stiphout et al [26] -O'Neill et al [27] -GenX [28] n/a PLEXOS LT Plan [29,30,31] ---Switch 1.x [32,33] ---RESOLVE [34,35] --RPM [36,37] n/a NEWS/WIS:dom [38,39] ? ?…”
Section: Motivation and Significancementioning
confidence: 99%
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“…Further, operational decisions should be modeled during chronological sequences of timesteps within many study days. This allows direct modeling of choices that depend on the sequence of hours within a single day, such as unit commitment (slow and expensive power plant start/stop decisions), when to charge and discharge finite storage, or when to schedule time-shiftable demand within the day [8,9] --NEMS [10,11,12,13] --ReEDS [14] n/a LEAP + OseMOSYS [15,16] --Balmorel [17] ---E4 Simulation Tool [18] --US-REGEN (non-UC mode) [19] n/a US-REGEN (UC mode) [19] n/a Oemof [20,21] URBS [22,23] -PyPSA [24] Palmintier and Webster [25] -Stiphout et al [26] -O'Neill et al [27] -GenX [28] n/a PLEXOS LT Plan [29,30,31] ---Switch 1.x [32,33] ---RESOLVE [34,35] --RPM [36,37] n/a NEWS/WIS:dom [38,39] ? ?…”
Section: Motivation and Significancementioning
confidence: 99%
“…Meeting both of these requirements is computationally difficult. A number of capacity planning models use multiple investment periods but don't model sequential timepoints within each day, impairing their ability to study unit commitment, storage and demand response [8,10,14,15,17,18,30,31]; others use a single planning step with hour-by-hour timeseries [20,22,24,25,26,27,28]. The PLEXOS model in long-term planning mode [31] uses hourly resolution for peak days, but only 1-2 blocks on all other days, obscuring the year-round view.…”
Section: Motivation and Significancementioning
confidence: 99%
“…In this study, it is proposed to transform not only the pre-contingency nodal power balance equality constraints but the post-contingency nodal power balance equality constraints (3). In spite of the fact that there are three global equations (N − 0, N − 1 and N − 2), only one equation is needed since active power generation for each condition is the same because these three equations are the same.…”
Section: Transforming the Equality Constraintsmentioning
confidence: 99%
“…Assuming that the electricity market is centrally operated (e.g., Chile situation), and that the generation companies do not have the ability to accomplish local market power, the GCEP optimization problem can be formulated as a cost minimization in which operational costs are modeled using a DC-network through an optimal power flow (DC-OPF) model [3].…”
Section: Introductionmentioning
confidence: 99%
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