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Incentivizing sustainable practices: Game-theoretic approach to peer-to-peer energy trading in the green transition era 激励可持续做法:绿色转型时代点对点能源交易的博弈论方法
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-07-07 DOI: 10.1016/j.segan.2024.101472
Jingxuan Dong, Jian Li

The urgent global concern regarding climate change has highlighted the necessity for transitioning to power generation with zero carbon emissions to promote a sustainable and environmentally conscious society. A crucial element in this transformation is reducing our dependence on the primary grid, which is predominantly powered by fossil fuels, natural gas, and coal. An innovative strategy for achieving this essential transition is through peer-to-peer energy trading (P2PET). However, the effectiveness of P2PET relies on successfully aligning the energy-related objectives of its participants. Identifying and effectively addressing these goals is a significant challenge. In response, this paper introduces a game-theoretic framework designed to encourage subscribers to engage in P2PET, both in islanded microgrids and interconnected grid configurations. Our methodology begins by introducing a model that captures the core energy-related objectives of both energy producers and consumers. This model is supported by a layered architectural framework tailored for peer-to-peer (P2P) marketplaces, enhancing the identification and classification of existing technologies in this domain. Following this, we delve into the formulation of an extended-form game rooted in non-cooperative game theory. We systematically evaluate the presence of strict Nash equilibria within this game-theoretic structure. To promote active engagement and trading in the peer-to-peer energy market (P2PEM), we introduce an innovative energy allocation policy. This policy is strategically devised to ensure the inclusion of every subscriber in the market, irrespective of fluctuations in supply and demand dynamics. Our proposed P2PET scheme is tested on a representative system, specifically a 14-bus IEEE network, incorporating 8 energy producers and 11 consumers as active participants in the market. By conducting an extensive series of tests, we accurately evaluate the design's performance. The results, compared to previous studies, show a significant reduction in consumer energy bills, ranging from 33 % to 7 %. This convincing result underscores the effectiveness and robustness of our proposed energy trading framework. In a world grappling with the imperative to transition to sustainable energy practices, our game-theoretic approach to incentivizing participants in P2PET emerges as a pivotal contribution. It demonstrates tangible benefits, promotes green energy production, and encourages responsible energy consumption.

全球对气候变化的迫切关注凸显了向零碳排放发电转型的必要性,以促进社会的可持续发展和环保意识。这种转型的一个关键因素是减少我们对主要由化石燃料、天然气和煤炭驱动的主电网的依赖。实现这一重要转变的创新战略是点对点能源交易(P2PET)。然而,P2PET 的有效性取决于能否成功协调参与者的能源相关目标。确定并有效实现这些目标是一项重大挑战。为此,本文引入了一个博弈论框架,旨在鼓励用户参与 P2PET,包括孤岛微电网和互联电网配置中的 P2PET。我们的方法首先引入了一个模型,该模型捕捉了能源生产者和消费者与能源相关的核心目标。该模型由专为点对点(P2P)市场定制的分层架构框架提供支持,从而加强了对该领域现有技术的识别和分类。随后,我们深入探讨了基于非合作博弈论的扩展形式博弈。我们系统地评估了这一博弈理论结构中是否存在严格的纳什均衡。为了促进点对点能源市场(P2PEM)中的积极参与和交易,我们引入了一种创新的能源分配政策。无论供需动态如何波动,该政策的战略设计都能确保将每个用户都纳入市场。我们提出的 P2PET 方案在一个具有代表性的系统上进行了测试,特别是一个 14 总线的 IEEE 网络,其中有 8 个能源生产商和 11 个消费者作为市场的积极参与者。通过进行一系列广泛的测试,我们准确评估了该设计的性能。与之前的研究相比,结果显示消费者的能源账单显著减少,减少幅度从 33% 到 7%。这一令人信服的结果凸显了我们提出的能源交易框架的有效性和稳健性。在全世界都在努力向可持续能源实践转型的当下,我们采用博弈论方法来激励 P2PET 的参与者是一项关键性的贡献。它展示了实实在在的好处,促进了绿色能源生产,鼓励了负责任的能源消费。
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引用次数: 0
Reactive power management in distribution networks in the presence of distributed generation sources based on information gap decision theory 基于信息差距决策理论的分布式发电网络无功功率管理
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-07-06 DOI: 10.1016/j.segan.2024.101470
Maryam Ramezani, Mahboobeh Etemadizadeh, Hamid Falaghi

The presence of uncertain parameters in power systems has led to many challenges for the designers and operators of these systems. One of these challenges is reactive power management in the presence of distributed renewable generation sources.

In this article, the management of reactive power in distribution networks in the electricity market and the presence of distributed renewable generation sources, including wind and solar power plants, is performed considering the uncertainties in the network load, power generation of distributed generation sources, and active and reactive power market prices. Furthermore, reactive power cost modeling of reactive power compensation equipment is carried out.

A hybrid stochastic/robust optimization method is employed to model the uncertainties in the problem. Finally, the efficiency of the method is confirmed by numerical examinations using the IEEE 33-bus distribution network and the GAMS optimization software. Simulation results indicate that in the risk-averse strategy, for a certain increase in cost, the radius of uncertainty in the active and reactive power market prices increases. Also, in this strategy, as β increases, the total cost of network operating increases by 81.72 %, while in a risk-seeking strategy, with the increase of β, the total operating cost of the network decreases by 77.78 %.

电力系统中不确定参数的存在给这些系统的设计者和操作者带来了许多挑战。本文考虑到网络负荷、分布式发电设备发电量以及有功和无功功率市场价格的不确定性,对电力市场中配电网络的无功功率管理以及分布式可再生能源(包括风能和太阳能发电厂)的存在进行了研究。此外,还对无功功率补偿设备进行了无功功率成本建模,并采用随机/稳健混合优化方法对问题中的不确定性进行建模。最后,通过使用 IEEE 33 总线配电网络和 GAMS 优化软件进行数值检验,证实了该方法的效率。仿真结果表明,在风险规避策略中,当成本增加到一定程度时,有功和无功功率市场价格的不确定性半径会增大。同时,在该策略中,随着 β 的增加,网络的总运行成本增加了 81.72%;而在风险规避策略中,随着 β 的增加,网络的总运行成本降低了 77.78%。
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引用次数: 0
Renewable energy communities and mitigation of energy poverty: Instruments for policymakers and community managers 可再生能源社区和减轻能源贫困:决策者和社区管理者的工具
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-07-04 DOI: 10.1016/j.segan.2024.101471

Energy poverty has been increasing since the early 2020s because of rising energy prices. This is attributed to geopolitical crises and the inclusion of the energy cost of CO2 pricing, which was historically an externality. Policymakers and citizens need new tools to address this issue, and energy communities are recognized as a valuable tool for mitigation. This study proposes two complementary approaches that relate to energy poverty and Renewable Energy Communities (RECs). The first aims to define and map energy poverty to support the policy in targeting measures and incentives. Using publicly available data, a new methodology is proposed for mapping energy poverty risk over a large territory with a fine granularity. The second approach taken sees REC managers at the center, who are tasked with sharing the economic benefits appropriately and equitably. A series of multi-criteria sharing mechanisms were developed and compared with the existing ones (e.g., based on Shapley value), including the energy poverty mitigation among them and the assessment of the impact of RECs on it. The results show that sharing methods can be one of the viable pathways for mitigating energy poverty through RECs without compromising the economy of non-vulnerable REC members.

由于能源价格不断上涨,能源贫困自 2020 年代初开始加剧。这归因于地缘政治危机,以及将能源成本纳入二氧化碳定价,而这在历史上是一个外部因素。政策制定者和公民需要新的工具来解决这一问题,而能源社区被认为是一种有价值的缓解工具。本研究提出了两种与能源贫困和可再生能源社区(RECs)相关的互补方法。第一种方法旨在定义能源贫困并绘制其地图,以支持政策有针对性地采取措施和激励措施。利用可公开获得的数据,提出了一种新的方法,以精细的粒度绘制大范围内的能源贫困风险图。第二种方法以区域经济共同体管理者为中心,他们的任务是适当、公平地分享经济利益。研究人员开发了一系列多标准分享机制,并与现有机制(如基于夏普利值的机制)进行了比较,包括其中的能源贫困缓解机制以及可再生能源中心对其影响的评估。结果表明,共享方法可以成为通过区域经济共同体缓解能源贫困的可行途径之一,同时不会损害非弱势区域经济共同体成员的经济。
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引用次数: 0
Dynamic scheduling of electricity demand for decentralized EV charging systems 分散式电动汽车充电系统的电力需求动态调度
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-07-03 DOI: 10.1016/j.segan.2024.101467
Kratika Yadav, Mukesh Singh

The rapid growth of electric vehicles (EVs) has brought forth new challenges to the power grid. Further, the simultaneous charging of EVs could lead to peak demand, potentially causing overloading, voltage swings, and other grid-related problems. To address these issues and lower the high energy costs faced by EV owners and grid operators, EV charging must be optimized. The study proposes an innovative strategy that utilizes decentralized charging systems to lessen the impact of EVs on the grid. A decentralized EV scheduling strategy offers scalability. Thus, making it suitable for a large EV population and it remains resilient to the dynamic arrivals of the EVs. The approach aims to balance the load on the grid and improve the effectiveness of charging operations. To achieve this, a convex optimization problem has been developed to effectively regulate the charging procedure, taking into account the distinct attributes of each EV. The mechanism operates by dividing time into several intervals. Each electric vehicle in the system autonomously adjusts its charging rate during the assigned time slots, with the goal of minimizing individual charging expenses. Moreover, the system demonstrates flexibility in deciding when to charge and discharge, allowing prioritization based on individual EV battery levels and power grid conditions. As a result, the cost analysis was conducted using the number of EVs and the average group size. A comparison of computational times between centralized and decentralized systems was undertaken to demonstrate the efficacy of the system.

电动汽车(EV)的快速增长给电网带来了新的挑战。此外,电动汽车的同时充电会导致高峰需求,可能造成过载、电压波动和其他电网相关问题。为了解决这些问题,降低电动汽车所有者和电网运营商面临的高能源成本,必须优化电动汽车充电。本研究提出了一种创新策略,利用分散式充电系统来减少电动汽车对电网的影响。分散式电动汽车调度策略具有可扩展性。因此,它适用于庞大的电动汽车群体,并对电动汽车的动态到达保持弹性。该方法旨在平衡电网负载,提高充电操作的效率。为此,我们开发了一个凸优化问题,以有效调节充电程序,同时考虑到每辆电动汽车的不同属性。该机制的运作方式是将时间划分为几个时间段。系统中的每辆电动汽车都会在分配的时间段内自主调整充电率,以实现个人充电费用最小化的目标。此外,该系统在决定何时充电和何时放电方面表现出灵活性,可根据每辆电动汽车的电池电量和电网条件确定优先次序。因此,成本分析是根据电动汽车数量和平均组规模进行的。对集中式系统和分散式系统的计算时间进行了比较,以证明该系统的有效性。
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引用次数: 0
Cooperative voltage control in distribution networks considering multiple uncertainties in communication 考虑通信中的多重不确定性的配电网中的协同电压控制
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-07-02 DOI: 10.1016/j.segan.2024.101459
Ting Yang, Yachuang Liu, Hao Li, Yanhong Chen, Haibo Pen

Delays, jitter, and packet loss in communication networks can impact the performance of cooperative voltage control systems in distribution networks. In distribution systems with a high penetration of renewable energy sources that do not respond promptly, these issues can even lead to system destabilization when voltage surges occur. Considering the interdependence of delay, jitter, and packet loss, the current direct approach of accumulating information entropy may result in the deterioration of dynamic control performance. Based on Copula entropy theory, a new multivariate communication uncertainty metric model is proposed. Using the multivariate Epanechnikov kernel function model, a method has been developed to estimate the multivariate non-independent uncertainty of a communication system. Accurate state estimation is integrated into event-triggered sliding mode control (ETSMC) of the distribution network to facilitate coordinated voltage control and enhance resilience against communication uncertainty. Design criteria for the controller and observer parameters are provided based on Lyapunov stability theory. Simulation results confirm that the proposed ETSMC offers significant improvements in control performance and system resilience to external power disturbances and multivariate communication uncertainty events.

通信网络中的延迟、抖动和数据包丢失会影响配电网络中协同电压控制系统的性能。在可再生能源渗透率较高且不能及时响应的配电系统中,当发生电压浪涌时,这些问题甚至会导致系统失稳。考虑到延迟、抖动和数据包丢失之间的相互依存关系,目前直接积累信息熵的方法可能会导致动态控制性能下降。基于 Copula 熵理论,提出了一种新的多变量通信不确定性度量模型。利用多变量 Epanechnikov 核函数模型,开发了一种估算通信系统多变量非独立不确定性的方法。精确的状态估计被集成到配电网络的事件触发滑模控制(ETSMC)中,以促进协调电压控制并增强对通信不确定性的适应能力。基于 Lyapunov 稳定性理论,提供了控制器和观测器参数的设计标准。仿真结果证实,所提出的 ETSMC 能显著改善控制性能,提高系统对外部电力干扰和多变量通信不确定性事件的适应能力。
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引用次数: 0
Real-time small-signal security assessment using graph neural networks 利用图神经网络进行实时小信号安全评估
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-07-02 DOI: 10.1016/j.segan.2024.101469
Glory Justin, Santiago Paternain

Security assessment is one of the most crucial functions of a power system operator. However, growing complexity and unpredictability make this an increasingly complex and computationally difficult task. In recent times, machine learning methods have gained attention for their ability to handle complex modeling applications. Convolutional neural networks (CNNs) in particular, are widely used in literature for their adaptability for classification problems. While CNNs generate promising results and some real-time advantages, they still require long training times and computational resources. This paper proposes a graph neural network (GNN) approach to the small-signal security assessment problem using data from Phasor Measurement Units (PMUs). Using a GNN, the process for small signal security assessment can be optimized, reducing the time needed from minutes, to less than a second, thus allowing for faster real-time application. Also, using graph properties, optimal PMU placement is determined and the proposed method is shown to perform efficiently under partial observability with limited PMU data. Case studies with simulated data from the IEEE 68-bus system and the NPCC 140-bus system are used to verify the effectiveness of the proposed method showing comparisons with the CNN.

安全评估是电力系统运营商最重要的职能之一。然而,日益增长的复杂性和不可预测性使这项任务变得越来越复杂,计算难度也越来越大。近来,机器学习方法因其处理复杂建模应用的能力而备受关注。特别是卷积神经网络(CNN),因其对分类问题的适应性而在文献中得到广泛应用。虽然卷积神经网络能产生可喜的结果并具有一些实时优势,但它们仍然需要较长的训练时间和计算资源。本文提出了一种图神经网络(GNN)方法,利用相量测量单元(PMU)的数据来解决小信号安全评估问题。利用图神经网络,可以优化小信号安全评估过程,将所需时间从几分钟缩短到一秒以内,从而实现更快的实时应用。此外,利用图的特性,还能确定 PMU 的最佳位置,并证明所提出的方法能在 PMU 数据有限的情况下,在部分可观测性条件下高效执行。利用 IEEE 68 总线系统和 NPCC 140 总线系统的模拟数据进行的案例研究验证了所提方法的有效性,并与 CNN 进行了比较。
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引用次数: 0
A microgrid control scheme for islanded operation and re-synchronization utilizing Model Predictive Control 利用模型预测控制实现孤岛运行和再同步的微电网控制方案
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-07-01 DOI: 10.1016/j.segan.2024.101464
Fernando Fachini , Tetiana Bogodorova , Luigi Vanfretti , Sjoerd Boersma

Enhancing grid resilience is proposed through the integration of distributed energy resources (DERs) with microgrids. Due to the diverse nature of DERs, there is a need to explore the optimal combined operation of these energy sources within the framework of microgrids. As such, this paper presents the design, implementation and validation of a Model Predictive Control (MPC)-based secondary control scheme to tackle two challenges: optimal islanded operation, and optimal re-synchronization of a microgrid. The MPC optimization algorithm dynamically adjusts input signals, termed manipulated variables, for each DER within the microgrid, including a gas turbine, an aggregate photovoltaic (PV) unit, and an electrical battery energy storage (BESS) unit. To attain optimal islanded operation, the secondary-level controller based on Model Predictive Control (MPC) was configured to uphold microgrid functionality promptly following the islanding event. Subsequently, it assumed the task of power balancing within the microgrid and ensuring the reliability of the overall system. For optimal re-synchronization, the MPC-based controller was set to adjust the manipulated variables to synchronize voltage and angle with the point of common coupling of the system. All stages within the microgrid operation were optimally achieved through one MPC-driven control system, where the controller can effectively guide the system to different goals by updating the MPC’s target reference. More importantly, the results show that the MPC-based control scheme is capable of controlling different DERs simultaneously, mitigating potentially harmful transient rotor torques from the re-synchronization as well as maintaining the microgrid within system performance requirements.

有人建议通过将分布式能源资源(DER)与微电网相结合来增强电网的恢复能力。由于 DER 的多样性,有必要探索这些能源在微电网框架内的优化组合运行。因此,本文介绍了基于模型预测控制 (MPC) 的二次控制方案的设计、实施和验证,以应对两个挑战:最佳孤岛运行和微电网的最佳再同步。MPC 优化算法可动态调整微电网中每个 DER(包括燃气轮机、聚合光伏 (PV) 单元和蓄电池储能 (BESS) 单元)的输入信号(称为操纵变量)。为实现最佳孤岛运行,基于模型预测控制(MPC)的二级控制器被配置为在孤岛事件发生后立即维持微电网功能。随后,它承担起微电网内的功率平衡任务,并确保整个系统的可靠性。为了实现最佳的再同步,基于 MPC 的控制器被设定为调整操纵变量,使电压和角度与系统的公共耦合点同步。通过一个 MPC 驱动的控制系统,微电网运行的所有阶段都得到了优化,控制器可以通过更新 MPC 的目标参考值有效地引导系统实现不同的目标。更重要的是,研究结果表明,基于 MPC 的控制方案能够同时控制不同的 DER,减轻重新同步带来的潜在有害瞬态转子扭矩,并将微电网维持在系统性能要求范围内。
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引用次数: 0
Meeting the charging demand of Electric Vehicles in Greece: Enabling intercity trips 满足希腊电动汽车的充电需求:支持城际旅行
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-06-29 DOI: 10.1016/j.segan.2024.101466
Themistoklis Stamadianos, Nikolaos A. Kyriakakis, Magdalene Marinaki, Yannis Marinakis

The increasing need for sustainable transportation has underscored the pivotal role of electric mobility in shaping the future of mobility. Electric Vehicles (EVs) have emerged as a promising solution, but their widespread adoption is contingent upon the availability of a reliable charging network. This challenge extends even to EV adoption pioneers like Norway and China. This study delves into the context of EV adoption in Greece, providing insights into the EV market, existing incentives, and the state of charging infrastructure. Reports indicate that Greece is at a critical juncture, with fast EV adoption but sluggish development of Charging Stations (CSs). To address this issue, a Monte Carlo simulation is employed to evaluate the feasibility of long-distance EV trips in Greece and propose an infrastructure development plan. For EVs, the study reveals a linear relationship between battery size and autonomy, with some exceptions emphasizing the importance of data acquisition and individual EV assessment. The study also provides insights into the relationship between trip length and energy consumption, indicating that longer trips exhibit greater fluctuation in energy consumption due to varying conditions, while energy usage patterns of shorter trips are more predictable. Additionally, the analysis presents average energy consumption values for each EV model in different temperature conditions, highlighting the impact of environmental factors on EV performance.

对可持续交通日益增长的需求凸显了电动交通在塑造未来交通中的关键作用。电动汽车(EV)已成为一种前景广阔的解决方案,但其广泛应用取决于是否有可靠的充电网络。即使是挪威和中国这样的电动汽车先行者也面临着这一挑战。本研究深入探讨了希腊采用电动汽车的背景,提供了有关电动汽车市场、现有激励措施和充电基础设施状况的见解。有报告显示,希腊正处于一个关键时刻,电动汽车普及速度快,但充电站(CS)发展缓慢。为解决这一问题,我们采用蒙特卡洛模拟法对希腊电动汽车长途旅行的可行性进行了评估,并提出了基础设施发展计划。对于电动汽车而言,研究揭示了电池尺寸与自主性之间的线性关系,但也有一些例外情况,强调了数据采集和电动汽车个体评估的重要性。研究还深入分析了行程长度与能源消耗之间的关系,结果表明,由于条件不同,较长行程的能源消耗波动较大,而较短行程的能源使用模式更可预测。此外,分析还提供了每种电动汽车型号在不同温度条件下的平均能耗值,突出了环境因素对电动汽车性能的影响。
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引用次数: 0
A multi-objective mixed integer linear programming approach for simultaneous optimization of cost and resilience of power distribution networks 同时优化配电网成本和恢复能力的多目标混合整数线性规划方法
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-06-29 DOI: 10.1016/j.segan.2024.101462
Vandana Kumari, Sanjib Ganguly

In recent years, customers have experienced a significant increase in weather-related power outages. The power distribution network (PDN), a subset of the power system, in particular is more susceptible to extreme events. Therefore, ensuring the resilient and cost-effective operation of PDNs following extreme weather conditions poses a significant challenge for distribution network operators. This paper presents an approach for simultaneously optimizing the cost and load restoration for resilience enhancement of power distribution networks while determining the optimal positioning and generation levels of mobile emergency generators. The proposed method, in addition, employs a distribution network reconfiguration to improve the load restoration process, by optimally determining the status of switches. The multi-objective formulation involves the minimization of load shedding to increase the resilience of the system, while the other objective is formulated to minimize the cost of load restoration. A weighted sum method is employed to address the multi-objective mixed-integer linear programming (MILP) model. A set of non-dominated solutions determined using the proposed formulation provides opportunities to the distribution system operator in choosing a resilience improvement strategy according to the availability of the operational budget. The proposed model is implemented on 33-bus distribution system to validate the efficacy of the proposed model.

近年来,与天气有关的停电事件大幅增加。配电网络(PDN)作为电力系统的一个子集,尤其更容易受到极端事件的影响。因此,在极端天气条件下确保配电网的弹性和成本效益对配电网运营商来说是一项重大挑战。本文提出了一种方法,可在确定移动应急发电机的最佳定位和发电量的同时,优化成本和负荷恢复,以增强配电网的恢复能力。此外,所提出的方法还采用了配电网络重新配置,通过优化确定开关状态来改进负荷恢复过程。多目标表述包括最大限度地减少甩负荷以提高系统的恢复能力,而另一个目标则是最大限度地减少恢复负荷的成本。多目标混合整数线性规划(MILP)模型采用了加权和法。利用所提方案确定的一组非主导解为配电系统运营商提供了根据可用运营预算选择弹性改进策略的机会。为了验证所提模型的有效性,我们在 33 个总线配电系统上实施了所提模型。
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引用次数: 0
A comprehensive and secure scheme for privacy-preserving smart meter data aggregation in the smart grid 智能电网中保护隐私的智能电表数据汇总综合安全方案
IF 4.8 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-06-29 DOI: 10.1016/j.segan.2024.101461
Ram Baksh, Samiulla Itoo, Musheer Ahmad

Smart meters play a crucial role in the functioning of the smart grid by rapidly collecting and transmitting power consumption data to electricity companies. However, the real-time nature of smart meter data poses privacy risks for customers. To address this concern, encrypted aggregation of smart meter power consumption has been widely employed to protect customer privacy. In this paper, we propose an innovative scheme designed specifically for smart grids to fulfill these requirements. Our scheme demonstrates superior performance compared to existing solutions in terms of communication cost, computation, and functionality features. The proposed authentication protocol not only enables the secure sharing of power consumption data but also satisfies various security requirements, including mutual authentication, anonymity, prevention of man-in-the-middle attacks, and more. Furthermore, our framework exhibits significantly lower computing, communication, and storage overhead compared to similar schemes in the context of smart grids. This highlights the comprehensive and secure nature of our suggested framework, surpassing other existing smart grid schemes in terms of overall effectiveness and reliability.

智能电表通过快速收集和向电力公司传输用电数据,在智能电网的运行中发挥着至关重要的作用。然而,智能电表数据的实时性给客户带来了隐私风险。为解决这一问题,智能电表用电量的加密聚合已被广泛采用,以保护客户隐私。在本文中,我们提出了一种专为智能电网设计的创新方案,以满足这些要求。与现有解决方案相比,我们的方案在通信成本、计算和功能特性方面都表现出了卓越的性能。所提出的认证协议不仅能实现电能消耗数据的安全共享,还能满足各种安全要求,包括相互认证、匿名、防止中间人攻击等。此外,与智能电网中的类似方案相比,我们的框架大大降低了计算、通信和存储开销。这凸显了我们建议的框架的全面性和安全性,在整体有效性和可靠性方面超越了其他现有的智能电网方案。
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引用次数: 0
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