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首页> 外文期刊>Energy Conversion & Management >MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H_2 system incorporating demand response
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MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H_2 system incorporating demand response

机译：MPC用于结合需求响应优化调度交流链接的混合光伏/风能/生物质/ H_2系统

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摘要

A Model Predictive Control (MPC) strategy based on the Evolutionary Algorithms (EA) is proposed for the optimal dispatch of renewable generation units and demand response in a grid-tied hybrid system. The generating system is based on the experimental setup installed in a Distributed Energy Resources Laboratory (LabDER), which includes an AC micro-grid with small scale PV/Wind/Biomass systems. Energy storage is by lead-acid batteries and an H2 system (electrolyzer, H2 cylinders and Fuel Cell). The energy demand is residential in nature, consisting of a base load plus others that can be disconnected or moved to other times of the day within a demand response program. Based on the experimental data from each of the LabDER renewable generation and storage systems, a micro-grid operating model was developed in MATLAB(C) to simulate energy flows and their interaction with the grid. The proposed optimization algorithm seeks the minimum hourly cost of the energy consumed by the demand and the maximum use of renewable resources, using the minimum computational resources. The simulation results of the experimental micro-grid are given with seasonal data and the benefits of using the algorithm are pointed out.
机译：提出了一种基于进化算法（EA）的模型预测控制（MPC）策略，用于并网混合动力系统中可再生能源发电单元的最优调度和需求响应。该发电系统基于安装在分布式能源实验室（LabDER）中的实验装置，该实验装置包括带有小型PV /风/生物质系统的AC微电网。能量存储通过铅酸电池和H2系统（电解槽，H2气瓶和燃料电池）实现。能源需求本质上是住宅，由基本负荷以及其他可以在需求响应计划中断开或移动到一天中其他时间的负荷组成。基于来自每个LabDER可再生发电和存储系统的实验数据，在MATLAB（C）中开发了微电网运行模型，以模拟能量流及其与电网的相互作用。所提出的优化算法使用最小的计算资源来寻求需求所消耗的能源的最小小时成本，以及可再生资源的最大利用。给出了实验微电网的仿真结果，并给出了季节性数据，并指出了使用该算法的好处。

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