2019
DOI: 10.1016/j.enpol.2018.10.025
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The impact of planning reserve margins in long-term planning models of the electricity sector

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Cited by 27 publications
(12 citation statements)
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“…The model determines value of each service endogenously, considering factors such as the capital and operating cost of alternative resources. In all cases, the value of firm capacity is low from the present through 2030, because throughout that period the capacity of the power system in many regions exceeds the planning reserve margin constraint enforced in the model (Murphy et al, 2020; NERC (North American Electric Reliability Corporation), 2020; Reimers et al, 2019). Over time, the value of peaking capacity increases as load grows and existing generators retire.…”
Section: Results: Drivers Of Deploymentmentioning
confidence: 99%
“…The model determines value of each service endogenously, considering factors such as the capital and operating cost of alternative resources. In all cases, the value of firm capacity is low from the present through 2030, because throughout that period the capacity of the power system in many regions exceeds the planning reserve margin constraint enforced in the model (Murphy et al, 2020; NERC (North American Electric Reliability Corporation), 2020; Reimers et al, 2019). Over time, the value of peaking capacity increases as load grows and existing generators retire.…”
Section: Results: Drivers Of Deploymentmentioning
confidence: 99%
“…ReEDS also endogenously considers how the amount of regulation and flexibility operating reserves increases with greater wind and solar generation. The capacity credit and reserve requirement estimates are based on and benchmarked with previous studies Frew et al 2018;Cole and Vincent 2019;Reimers, Cole, and Frew 2019;Zhou, Cole, and Frew 2018;Cole et al 2017;Sigrin et al 2014). All (planning and operating) reserve requirements are specified separately for different regions.…”
Section: Representation Of Reliability-related Constraintsmentioning
confidence: 99%
“…They also strike a balance between the level of detail in describing the problem and the computational resources needed to run the model. We set spinning reserves to be at least 10% of load at any instant, and capacity reserves for each region to 15% of peak load in any given year (Reimers, Cole, and Frew 2019). The central region's peak load is currently higher than its available capacity reserves; accordingly, we assumed these will be met by 2025.…”
Section: Overview Of Modelmentioning
confidence: 99%