基于非线性随机动态规划的孤岛纳米电网能量优化管理

Andres Salazar, A. Berzoy, J. Mohammadpour, Wenzhan Song
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引用次数: 1

摘要

纳米电网是一种小型微电网,通常服务于很少的建筑物或负载。孤岛式NG是由可再生能源和传统燃料发电机等发电机组、储能系统(ESS)和负载组成的自主系统。本文提出了一种新的孤岛式自动控制系统的最优能量管理算法。为了在每个运行周期内使发电机组的运行成本最小化,并使电池的可用性最大化,采用动态规划框架对底层优化问题进行求解。所提出的电磁算法的目标是确保最大可用太阳能的使用和最佳电池充电状态。为了实现这一目标,考虑电池充放电过程的非线性,将ESS的管理描述为一个随机最优控制问题。为了预测随机DP公式中太阳能产量的概率分布,建立了一个马尔可夫模型。仿真结果表明,与基于规则的算法相比,所提出的基于dp的方法是有效的。最后,利用硬件在环系统对所提出的电磁算法的实时性进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimum Energy Management of Islanded Nanogrids through Nonlinear Stochastic Dynamic Programming
Nanogrids (NGs) are small scale microgrids typically serving few buildings or loads. An islanded NG is an autonomous system that consists of generation units including renewable energy sources and traditional fuel generators, energy storage systems (ESS) and loads. This paper presents the design and validation of a new optimal energy management (EM) algorithm for an islanded NG. To minimize the generator's operating cost and maximize battery availability at each operating cycle, dynamic programming (DP) framework is employed to solve the underlying optimization problem. The goal of the proposed EM algorithm is to ensure both the use of maximum available solar power and optimal battery state of charge. To meet that goal, the management of the ESS is formulated as a stochastic optimal control problem, where nonlinearities in the battery charging and discharging process are considered. A Markov model is built in order to predict the probability distribution of the solar production used in the stochastic DP formulation. Simulation results are given to illustrate the efficacy of the proposed DP-based approach compared to a rule-based algorithm. Finally, a hardware-in-the-loop system is used to evaluate the real-time operation of the proposed EM algorithms.
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