Joint supply, demand, and energy storage management towards microgrid cost minimization

Sun Sun, Min Dong, B. Liang
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引用次数: 33

Abstract

The problem of real-time power balancing in a grid-connected microgrid is studied. We consider a microgrid powered by a conventional generator (CG) and multiple renewable generators (RGs) each co-located with one distributed storage (DS) unit. An aggregator operates the microgrid and aims to minimize the long-term system cost, including all RGs' cost, the CG's cost, and the cost for exploiting external energy markets. We jointly manage the supply side, demand side, and DS units, taking into account the randomness of the system, and incorporating the ramping constraint of the CG. A real-time algorithm is proposed, which does not require any statistics of the system. We analytically characterize the gap between the system cost under our algorithm and the minimum cost, demonstrating that our algorithm is asymptotically optimal as the DS energy capacity increases and the CG ramping constraint loosens. In simulation, we compare the proposed algorithm with a greedy algorithm as well as a lower bound on the optimum. Simulation shows that our algorithm outperforms the greedy one and its performance can be close to the optimum even with small DS units.
面向微电网成本最小化的联合供需和储能管理
研究了并网微电网的实时功率平衡问题。我们考虑一个由传统发电机(CG)和多个可再生发电机(RGs)供电的微电网,每个发电机都与一个分布式存储(DS)单元共存。聚合商运营微电网,目标是最小化长期系统成本,包括所有RGs的成本,CG的成本,以及开发外部能源市场的成本。我们共同管理供给侧、需求侧和DS单元,考虑到系统的随机性,并结合CG的爬坡约束。提出了一种不需要任何系统统计的实时算法。我们分析表征了算法下的系统成本与最小成本之间的差距,证明了随着DS能量容量的增加和CG斜坡约束的放松,我们的算法是渐近最优的。在仿真中,我们将该算法与贪心算法以及最优下界进行了比较。仿真结果表明,该算法优于贪婪算法,即使在较小的DS单元下,其性能也接近最优。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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