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A novel stochastic method to dispatch microgrids using Monte Carlo scenarios

机译：一种使用蒙特卡洛场景分配微电网的新型随机方法

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摘要

Stochastic operating strategies have proven to achieve cheaper resource scheduling both in large power systems and microgrids, but suffer from high computational requirements with respect to traditional deterministic approaches; therefore, using stochastic formulations in advanced infra-daily operating strategies is quite challenging, especially in isolated energy systems with limited computational assets. This paper proposes a dispatching methodology for microgrids based on a novel two-stage formulation that decomposes the stochastic problem into several deterministic subproblems, whose solutions are afterwards aggregated by the aggregator using simulations and a cost-based rule. In the first stage, every subproblem is solved, then each optimal dispatching is simulated in the second stage to evaluate the corresponding expected operating cost, which is used by the aggregator to select the final optimal scheduling. When compared to traditional methods for a rural microgrid in Uganda, the proposed approach not only achieves interesting savings in operational costs, up to 5%, but also sharply reduces the computational requirements, even more than 5-100 times with respect to traditional stochastic approaches. The paper also proposes a review and first classification of this kind of methodologies, to highlight the novelties of the approach.
机译：事实证明，随机操作策略可以在大型电力系统和微电网中实现更便宜的资源调度，但是相对于传统的确定性方法而言，其计算要求很高。因此，在先进的日常运行策略中使用随机公式非常具有挑战性，特别是在计算资源有限的孤立能源系统中。本文提出了一种基于新型两阶段公式的微电网调度方法，该方法将随机问题分解为几个确定性子问题，然后由聚合器使用模拟和基于成本的规则对这些子问题的解决方案进行聚合。在第一阶段，解决每个子问题，然后在第二阶段模拟每个最佳调度，以评估相应的预期运营成本，聚合器将其用于选择最终的最佳调度。与乌干达农村微电网的传统方法相比，该方法不仅可节省高达5％的运营成本，而且还大大降低了计算需求，是传统随机方法的5至100倍以上。本文还提出了这种方法的回顾和首次分类，以突出该方法的新颖性。

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