Abstract
Battery energy storage (BES) systems show promise of savings for both the utility and the customer. An algorithm combining multi-pass dynamic programming (MPDP) with a time-shift technique has been developed for two purposes: economic dispatch of BES; and finding optimal BES power and energy capacities in a power system. Due to the daily cyclic nature of the load curve, a 168-hour load curve is decomposed into seven 24-hour subsections for easy management. Each subsection is treated independently. Decomposition can save computation time and computer memory. A time-shift technique provides better starting state values and improves the finding process of the MPDP approach. The Kansas City Power and Light system is used as an example to test this algorithm. The results obtained in this research have been compared with those from EPRI's DYNASTORE with reasonable discrepancy.
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