基于深度q网络的有限功率微电网多资源能量管理

Nabil Jalil Aklo, Mofeed Turky Rashid
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引用次数: 1

摘要

为解决农村地区电力供应不足的问题,提出了一种混合并网模式微电网。建议将柴油发电机组(DG)和可再生能源发电机组(RER)并网,并网功率有限。为保证燃料供应的可得性,采用“不付即付”的方法。本文提出了一种智能能源管理系统(EMS)来控制混合动力汽车的运行,并保证在燃料供应调度下燃料的完全分配。为了便于构建EMS,为此采用了一种免费的基于模型的强化学习(RL)算法,该算法的设计依赖于深度q网络(deep Q-network, DQN)。通过MATLAB对该算法进行了仿真,验证了所提系统的有效性;结果表明,与改进的粒子群优化算法(IPSO)相比,该算法具有较好的性能。
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Deep-Q-network-based energy management of multi-resources in limited power micro-grid
To overcome the shortage of power supply to the rural area, a hybrid connected mode micro-grid (MG) is proposed. It is suggested to include a diesel generator (DG) and renewable energy resources (RER) with a limited power of utility grid. To ensure the availability of fuel supply, the take-or-pay method is employed. In this paper, a smart energy management system (EMS) has been proposed to control the operation of hybrid MG, in addition to ensuring complete fuel disbursement under the scheduling of fuel supply. To facilitate the construction of EMS, a free model-based reinforcement learning (RL) algorithm has been employed for this purpose, in which the design of this algorithm depends on deep Q-network (DQN). The simulation of the algorithm has been achieved by MATLAB to validate the proposed system; the results showed a good performance of the technique compared with the performance achieved by improved particle swarm optimisation (IPSO) algorithm.
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来源期刊
International Journal of Powertrains
International Journal of Powertrains Engineering-Automotive Engineering
CiteScore
1.20
自引率
0.00%
发文量
25
期刊介绍: IJPT addresses novel scientific/technological results contributing to advancing powertrain technology, from components/subsystems to system integration/controls. Focus is primarily but not exclusively on ground vehicle applications. IJPT''s perspective is largely inspired by the fact that many innovations in powertrain advancement are only possible due to synergies between mechanical design, mechanisms, mechatronics, controls, networking system integration, etc. The science behind these is characterised by physical phenomena across the range of physics (multiphysics) and scale of motion (multiscale) governing the behaviour of components/subsystems.
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