|dc.description.abstract||There are several specific applications that offer potential ways in which energy storage may be able to produce revenue and/or provide savings for system operators. The most obvious is simple energy arbitrage where low-cost energy is purchase during low-price hours and released back to the grid during high-priced times. For the purposes of avoiding upgrading transmission and distribution equipment, it can be used to decrease load. For variable renewable generation, it can store the energy from peak periods of production and discharge during period of low production, providing a smoother generator output.
For this work, the economics of using a sodium-sulfur battery for energy arbitrage and capacity upgrade deferral were explored. A reduced 240-bus model of the electrical grid in the western United States (WECC) was used to run a combination market/power-flow simulation where all generators and loads participate in an energy market auction. Into this simulation, a small sodium-sulfur battery was inserted and allowed to participate.
Several parameters regarding the characteristics and usage of the energy storage device were explored: storage efficiency, location in the electrical grid, bidding algorithm, and number of years of operation. The results from the simulation allow for the calculation of revenue from energy arbitrage while more general off-line calculations were used to estimate the savings from deferring capacity upgrades in the electrical grid, examining the effects of deferral time, storage and upgrade cost, and upgrade equipment lifetime.
The results show that this dual-use of a single storage device created a positive net present value (including capital costs), indicating this application of energy storage is financially beneficial. Most of the value generated by the storage device was through the upgrade deferral savings; the energy arbitrage added very little value and often lost money. The results from the market/power-flow simulation show that there is a strong interactive effect between the network location and the bidding strategy, both significantly effecting the revenue. The greatest savings through upgrade deferral come from deferring upgrades of more expensive equipment for longer periods of time.||