Abstract
The purpose of this paper was to develop an analytical, easy to visualize solution to the problem of determining the optimal off-peak storage size. This has been done within the constraints stated. That is, no effort has been expended to define more efficient control systems, and changes in the efficiencies of an off-peak system with respect to system size have not been addressed. The method is certainly easy to visualize. The impacts of varying weather parameters, demand, and energy charges and capital costs are easily seen. More worthwhile work could be done in this area. Although this method can be used to determine the optimal storage size given parameters such as utility rates, whether parameters, etc., perhaps more important is the setting of appropriate utility rates in the first place. That is, this method could be used as part of a larger solution to the problem of understanding the dynamical relationships between setting utility rates, utility load curves, residential growth patterns, and storage sizing. Not considering this aspect of implementing off-peak storage systems may lead to an electric utility finding itself in the untenable position of having once offered on-peak/off-peak rate incentives, then subsequently finding its load curve leveled offmore » enough to make such rates no longer needed. If the incentives are maintained, problems such as night peaking may occur. If incentives are reduced, the economic motivation for the original system users may be eliminated. There are solutions to this problem, to be sure, but control of systems such as this can be tricky, particularly when the controller (utility rates in this case) is bandwidth limited.« less
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