论文标题
通过随机模型预测控制对可再生产生和不确定需求的最佳管理和不确定的需求
Optimal Management of Renewable Generation and Uncertain Demand with Reverse Fuel Cells by Stochastic Model Predictive Control
论文作者
论文摘要
本文提出了用于管理可再生能源社区的反向燃料电池的控制策略。基于两阶段的模型预测控制算法旨在定义操作过程中要遵循的最佳经济策略。可再生能源产生和用户的需求由适当定义的基于马尔可夫链的方法预测。控制算法能够考虑预测的不确定性和可逆燃料电池的非线性行为。通过配备PV的工业建筑的聚集，对拟议方法的性能进行了测试。
This paper proposes a control strategy for a Reverse Fuel Cell used to manage a Renewable Energy Community. A two-stage scenario-based Model Predictive Control algorithm is designed to define the best economic strategy to be followed during operation. Renewable energy generation and users' demand are forecasted by a suitably defined Discrete Markov Chain based method. The control algorithm is able to take into account the uncertainties of forecasts and the nonlinear behaviour of the Reversible Fuel Cell. The performance of proposed approach is tested on a Renewable Energy Community composed by an aggregation of industrial buildings equipped with PV.
