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Assessment of a multi-agent mixed-integer optimization algorithm for battery scheduling
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DOI：10.1145/3208903.3212058.png)
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Abstract
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In the present paper, the problem of scheduling populations of energy storage systems including asymmetric charging and discharging efficiencies is formulated as a mixed integer program. The problem is solved using both a novel distributed local mixed integer solution scheme and a global mixed integer solver. We draw upon a detailed numerical comparison of both methods via a simulation example built using real PV generation data consisting of 54 energy storage systems over a horizon of 48 time steps leading to 2640 integer variables. Our results indicate that the distributed local solution method delivers values comparable to the centralized global solver but in significantly reduced time.
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