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Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics

机译:使用节点价格的多个微电网的分层调度:来自共识和复制器动力学的方法

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A hierarchical approach for the energy management of geographically close microgrids connected through a dedicated AC power network is proposed in this paper. The proposed approach consists of a two-layer energy management system (EMS) for networked microgrids. In the lower layer, each microgrid solves its own economic dispatch problem through a distributed model predictive control approach that respects capacity limits and ramp-rate constraints of distributed generation. In the upper layer, the energy trading in the network of microgrids decides how to optimally trade the energy based on the marginal cost information from the lower layer in order to improve global optimization objectives, e.g., social welfare. In order to solve the trading problem, a consensus-based algorithm and a replicator dynamics algorithm are proposed assuming that the marginal cost function of the microgrid is known and linear. It is shown that both algorithms converge to the same solution, which is equivalent to the minimization of operation costs. The consensus-based algorithm is extended in order to tackle more general marginal cost functions and trading network constraints. Moreover, the effect of ramp constraints and network limits is studied. Simulations show the effectiveness of the proposed algorithms for three interconnected microgrids with different characteristics.
机译:本文提出了通过专用交流电网连接的地理上关闭微电网的能量管理的分层方法。该方法包括用于网络微电网的双层能量管理系统(EMS)。在下层中,每个微电网通过尊重分布式发电的容量限制和斜率约束来解决自己的经济调度问题。在上层中,微电网网络中的能量交易决定了如何基于来自下层的边际成本信息来最佳地交易能量,以改善全球优化目标,例如社会福利。为了解决交易问题,提出了一种基于共识的算法和复制器动力学算法,假设显微普林的边际成本函数是已知的和线性的。结果表明,这两个算法都会收敛到相同的解决方案,这相当于最小化运营成本。扩展了基于共识的算法,以解决更通用的边际成本函数和交易网络约束。此外,研究了斜坡约束和网络限制的影响。模拟显示所提出的三种互连微电网具有不同特性的算法的有效性。

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