Emdadi Kazem, Gandomkar Majid, Nikoukar Javad
Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran.
Sci Rep. 2025 May 10;15(1):16347. doi: 10.1038/s41598-025-99697-z.
In this article, the energy management of the intelligent distribution system with charging stations for battery-based electric vehicles (EVs) and plug-in hybrid EVs, hydrogen station for fuel cell-based EVs, and renewable integrated energy systems (IESs) with hydrogen storage devices in accordance with the estimation of economic, operational, security and environmental goals of distribution system operator is presented. Hydrogen storage is used to store electric energy and feed hydrogen consumers. The methodology adopted here is expressed as a multi-objective formulation to be solved. Objective functions are minimizing the cost of buying energy by distribution system from the upstream network, minimizing distribution system energy losses, minimizing environmental emissions, and maximizing voltage security in the distribution system. In this issue, AC power flow model, operation and voltage security boundaries in the network, performance model of charging station for EVs, hydrogen station model for fuel cell vehicles, and renewable IES operation model with hydrogen storage is the boundaries specific to the problem. The problem in the single-objective model uses the Pareto optimization that relies on the sum of weighted functions method. Next, the fuzzy decision-making technique extracts an optimal compromised solution between the operational, economic, security and environmental objectives of the network operator. In the present scheme, load, energy prices, renewable phenomena, electric vehicles have uncertainty. In this article, stochastic optimization based on Unscented Transform is incorporated to provide a suitable modeling of the uncertain parameters appearing in the problem. Modelling of the performance of EVs charging station and hydrogen fulling station, using hydrogen storage as electricity energy storage and feeding hydrogen loads, energy management of renewable bio-waste and tidal units in IES, considering the different objectives of network operator, and using Unscented Transform approach to model of uncertainty parameters are the innovations of this article. Findings show that the method improves the technical, environmental and economic conditions of the grid, and the integrated system with its optimal performance is able to enhance the economic, environmental, security and operation status of the distribution system up to roughly 45.8%, 38%, 32-45% and 10.6%, respectively.
本文介绍了一种智能配电系统的能量管理方法，该系统配备了用于电池电动汽车（EV）和插电式混合动力电动汽车的充电站、用于燃料电池电动汽车的加氢站以及带有储氢装置的可再生综合能源系统（IES），其依据配电系统运营商的经济、运行、安全和环境目标进行评估。储氢用于存储电能并为氢消费者供气。这里采用的方法表示为一个待求解的多目标公式。目标函数包括使配电系统从上游网络购买能源的成本最小化、使配电系统的能量损耗最小化、使环境排放最小化以及使配电系统中的电压安全性最大化。在这个问题中，交流潮流模型、网络中的运行和电压安全边界、电动汽车充电站的性能模型、燃料电池汽车加氢站模型以及带有储氢的可再生IES运行模型是该问题特有的边界条件。单目标模型中的问题采用依赖加权函数法之和的帕累托优化。接下来，模糊决策技术在网络运营商的运行、经济、安全和环境目标之间提取出一个最优折衷解决方案。在当前方案中，负荷、能源价格、可再生现象、电动汽车具有不确定性。本文纳入了基于无迹变换的随机优化，以对问题中出现的不确定参数进行合适的建模。对电动汽车充电站和加氢站的性能进行建模，利用储氢作为电能存储并为氢负荷供气，对IES中的可再生生物废弃物和潮汐机组进行能量管理，考虑网络运营商的不同目标，并使用无迹变换方法对不确定参数进行建模，这些都是本文的创新之处。研究结果表明，该方法改善了电网的技术、环境和经济状况，并且具有最优性能的集成系统能够分别将配电系统的经济、环境、安全和运行状况提高约45.8%、38%、32 - 45%和10.6%。
