2007
DOI: 10.1109/tpwrs.2007.894849
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Long-Run Marginal Cost Pricing Based on Network Spare Capacity

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Cited by 26 publications
(16 citation statements)
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References 4 publications
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“…Regarding the quantification of asset reinforcement costs, the projected long-run investment costs (LRICs) for power systems was defined and quantified in existing publications [24][25][26]. The LRIC concept assumes that due to load growth, an asset will be used to its full capacity in a certain number of years (this time frame is defined as the time horizon), thus prompting investment at a future tipping point, i.e.…”
Section: B Deriving Additional Reinforcement Cost From 3-phase Imbalmentioning
confidence: 99%
“…Regarding the quantification of asset reinforcement costs, the projected long-run investment costs (LRICs) for power systems was defined and quantified in existing publications [24][25][26]. The LRIC concept assumes that due to load growth, an asset will be used to its full capacity in a certain number of years (this time frame is defined as the time horizon), thus prompting investment at a future tipping point, i.e.…”
Section: B Deriving Additional Reinforcement Cost From 3-phase Imbalmentioning
confidence: 99%
“…Taking a similar tack, Li [20] develops the same methodology, but using analytical expressions to calculate LTMC instead of incremental cost. In [21], the same methodology is applied to calculate reactive energy tariffs, using the reinforcements required to offset voltage limit violations.…”
Section: Ltmc-based Distribution Pricingmentioning
confidence: 99%
“…The LRIC model originally proposed by UoB in conjunction with the Office of Gas and Electricity Market (Ofgem) and Western Power Distribution (WPD) [9,13] assumes that for network components affected by a nodal injection, either demand or generation, there will be a cost associated for the injection if their reinforcement horizons are accelerated or a credit if they are deferred. Fig.2 demonstrates the basic concept behind the model.…”
Section: Long-run Incremental Cost Pricing Modelmentioning
confidence: 99%