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Optimal Control of Combined Wind and Hydrogen System Based on Genetic Algorithm

机译：基于遗传算法的余氢系统优化控制

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摘要

To deal with increasing demand for clean and efficient energy in the residential sector, distributed energy resources including wind energy, fuel cell, etc. have been paid more and more attention. This paper presents an economical optimal energy management strategy for a grid-tied wind-fuel cell hybrid power supply system. The hybrid system meets the electrical load demand and sells the excess energy to the grid. The objective is to minimize energy cost and make full use of fuel cell system, taking into account the time-of-use electricity tariff. The optimal control problem is solved using genetic algorithm and test it with real wind condition. The power to/from the inverter, electrolyzer hydrogen power and fuel cell power are the control variables while the hydrogen in the storage tank are the state variables. The performance of the proposed control strategy is tested by simulating different operating scenarios, with or without fuel cell system feed-in or rather export to the grid. The results clearly demonstrate that the new method is able to optimize the operating costs and provide optimally schedules of the combined wind and hydrogen system accurately.
机译：为了应对居住部门的清洁和高效能量的日益增长，包括风能，燃料电池等的分布能源资源得到了越来越多的关注。本文介绍了一款经济的最佳能源管理策略，适用于网格绑住风力 - 燃料电池混合电源系统。混合系统满足电负荷需求并将多余的能量销售给电网。目的是最大限度地减少能源成本并充分利用燃料电池系统，考虑到使用时间的电费。使用遗传算法解决了最佳控制问题并用实际风力调整。来自逆变器的电源，电解槽氢功率和燃料电池功率是控制变量，而储罐中的氢气是状态变量。通过模拟不同的操作场景，使用或没有燃料电池系统进料或相当导出到电网来测试所提出的控制策略的性能。结果清楚地表明，新方法能够精确优化运营成本，并准确地提供组合风和氢气系统的最佳时间表。

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