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The most important determinant of the installed cost of a BTM BESS is the overall scale of the system. By “scale”, I refer to the joint magnitude of the energy and power capacity, abstracted away from variation in discharge duration.
Thus, my preferred specification for predicting the installed cost of BTM BESS is as follows: (5) ln ( C i) = α t s + β 1 ln ( E i) + β 2 ln ( P i) + γ 1 ln ( E i) 2 + γ 2 ln ( P i) 2 + γ 3 ln ( E i) ln ( P i) + δ 1 A C i + δ 2 D C i + δ 3 ln ( w t c) + ɛ i
Visual inspection suggests that the Cobb–Douglas model underestimates the cost (i.e., generates a prediction with a positive residual) of BTM BESS with discharge durations less than one hour and more than three. Between one and three hours, the distribution of residuals is nearly identical and centered on zero.
Furthermore, TTS includes project-level data on 68,061 BTM BESS co-installed with solar PV. The preponderance of these observations (91.4%) are in California. Because the TTS dataset does not disaggregate BESS and PV costs, the upfront cost of BTM BESS present only in the TTS dataset cannot be modeled disjointly from the upfront cost of BTM PV.
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