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Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic-based model predictive control approach 住宅紧急采暖蓄热优化调度方法:基于仿射算法的模型预测控制方法
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-10-17 DOI: 10.1049/esi2.12082
Jiarui Zhang, Yunfei Mu, Zeqing Wu, Zhe Liu, Yi Gao, Hongjie Jia, Hairun Li

Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic-based model predictive control approach (AA-MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH-based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA-MPC approach that takes the thermal energy for emergency building heating as a time-varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic-based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.

住宅供暖面临着停电时供热中断的挑战。蓄热式电采暖(REH)作为一种很有前途的采暖电气化形式,具有在停电时将建筑室内温度保持在理想范围内的灵活性,同时在正常运行状态下降低运行成本。然而,为了上述两种目的,在TES中有限的热能的分配和调度受到许多不确定因素的影响,例如室外温度、辐射、停电时间等。在TES中过高估计停电所需热能可以提高供热可靠性,但也会在一定程度上增加REH运行成本,反之亦然。针对这一问题,提出了一种基于仿射算法的REH优化调度方法(AA-MPC),以平衡REH在停电时的供热可靠性和运行经济性。建立了基于reh的住宅建筑能源系统模型,描述了建筑热负荷与室外温度和辐照的关系。然后,在最小舒适温度阈值的约束下,利用居民在停电时的最小热需求来确定热水箱(HWT)提供的应急建筑采暖所需的热能。在此基础上,提出了将建筑应急采暖热能作为HWT的时变约束的AA-MPC方法,以确定上述不确定性下考虑住宅应急采暖的REH最优调度。数值研究表明,该方法可以在不确定停电情况下保持至少2 h的最小热需求。同时可以减少不确定因素对运行成本的影响,在一定程度上减少应急供热带来的经济问题。与基于区间算法的模型预测控制方法相比,该方法在低、中、高预测误差水平下的运行成本区间分别缩短了57.3%、0.3%和32.5%。
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引用次数: 2
Power system coherency recognition and islanding: Practical limits and future perspectives 电力系统一致性识别和孤岛:实际限制和未来展望
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-09-06 DOI: 10.1049/esi2.12081
Harold R. Chamorro, Edgar O. Gomez-Diaz, Mario R. A. Paternina, Manuel A. Andrade, Emilio Barocio, Jose L. Rueda, Francisco Gonzalez-Longatt, Vijay K. Sood

Electrical power systems are continuously upgrading into networks with a higher degree of automation capable of identifying and reacting to different events that may trigger undesirable situations. In power systems with decreasing inertia and damping levels, poorly damped oscillations with sustained or growing amplitudes following a disturbance may eventually lead to instability and provoke a major event such as a blackout. Additionally, with the increasing and considerable share of renewable power generation, unprecedented operational challenges shall be considered when proposing protection schemes against unstable electro-mechanical (e.g. ringdown) oscillations. In an emergency situation, islanding operations enable splitting a power network into separate smaller networks to prevent a total blackout. Due to such changes, identifying the underlying types of oscillatory coherency and the islanding protocols are necessary for a continuously updating process to be incorporated into the existing power system monitoring and control tasks. This paper examines the existing evaluation methods and the islanding protocols as well as proposes an updated operational guideline based on the latest data-analytic technologies.

电力系统不断升级为自动化程度更高的网络,能够识别和应对可能引发不良情况的不同事件。在惯性和阻尼水平不断降低的电力系统中,在扰动之后持续或不断增长的振幅阻尼不良的振荡可能最终导致不稳定并引发诸如停电之类的重大事件。此外,随着可再生能源发电的不断增加和相当大的份额,在提出针对不稳定机电(如衰铃)振荡的保护方案时,必须考虑前所未有的操作挑战。在紧急情况下,孤岛操作可以将电网分割成独立的小网络,以防止全面停电。由于这些变化,确定振荡相干的潜在类型和孤岛协议对于将持续更新过程纳入现有电力系统监测和控制任务是必要的。本文分析了现有的评估方法和孤岛协议,并基于最新的数据分析技术提出了一个更新的操作指南。
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引用次数: 7
Synthetic thermal convolutional-memory network for the lithium-ion battery behaviour diagnosis against noise interruptions 用于噪声干扰下锂离子电池行为诊断的合成热卷积记忆网络
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-08-24 DOI: 10.1049/esi2.12080
Marui Li, Chaoyu Dong, Rui Wang, Xiaodan Yu, Qian Xiao, Hongjie Jia

In order to meet the two global challenges of energy shortage and environmental pollution, various countries have begun to advocate the application of new energy equipment such as electric vehicles. This has also promoted the development of energy storage equipment and energy storage systems. With their high performance, lithium-ion batteries are used in a wide range of electrical equipment. But the safety of lithium-ion batteries depends on effective behaviour diagnosis. In order to better realise behaviour diagnosis, this paper combined the long and short-term memory network (LSTM) with the temporal convolution network (TCN) for the first time and established a synthetic thermal convolutional-memory network (STCMN) for lithium-ion battery behaviour diagnosis against noise interruptions. In addition, a TCN-LSTM alliance network structure is designed. The TCN-LSTM alliance network is an effective architecture applied not only to the temperature prediction of Li-ion batteries but also to the thermal diagnosis part. And these two parts finally constitute the thermal convolutional-memory network. The experimental results show the network designed in this paper was able to improve Li-ion battery behaviour detection.

为了应对能源短缺和环境污染这两大全球性挑战,各国都开始倡导电动汽车等新能源设备的应用。这也促进了储能设备和储能系统的发展。锂离子电池的高性能被广泛应用于各种电气设备中。但锂离子电池的安全性取决于有效的行为诊断。为了更好地实现锂离子电池的行为诊断,本文首次将长短期记忆网络(LSTM)与时间卷积网络(TCN)相结合,建立了用于噪声干扰下锂离子电池行为诊断的合成热卷积记忆网络(STCMN)。此外,设计了TCN-LSTM联盟网络结构。TCN-LSTM联盟网络是一种既可用于锂离子电池温度预测又可用于热诊断的有效架构。这两部分最终构成了热卷积记忆网络。实验结果表明,本文所设计的网络能够改善锂离子电池的行为检测。
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引用次数: 3
A feedback-integrated framework for resilient and distributed scheduling of electric vehicles under uncertain charging characteristics 不确定充电特性下电动汽车弹性分布式调度的反馈集成框架
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-08-23 DOI: 10.1049/esi2.12079
Bakul Kandpal, Ashu Verma

Emerging innovation in smart charging for plug-in electric vehicles (EVs) has the potential to achieve significant economic benefits. In several works, smart charging encourages the use of EVs as a flexible resource by modifying their power consumption through a demand response (DR) program. However, it is promptly assumed that EVs are always responsive and accept the smart charging signals with no fault. In practice, due to uncertainties such as random EV mobility, volatile battery charging characteristics or charging component failures, some EVs would be unable to accept the assigned charging signals dispatched from a central server. Therefore, this article proposes a feedback loop to predict EV charging behaviours and thereby adaptively tune the time-based control signals dispatched to individual EVs. Moreover, a parallel-operating distributed DR algorithm is proposed which aims optimal EV scheduling under charging uncertainties while reducing the need of private information sharing. The proposed distributed algorithm allows increased EV user privacy, fast convergence properties and optimal operation under communication disruptions and delays. The effectiveness of the proposed methods are also numerically exhibited for varying penetration of EVs within a low-voltage (LV) distribution test network.

插电式电动汽车(ev)智能充电的新兴创新有可能实现显著的经济效益。在一些工作中,智能充电鼓励使用电动汽车作为一种灵活的资源,通过需求响应(DR)计划调整其功耗。然而,我们立即假设电动汽车始终响应,并无故障地接受智能充电信号。在实际应用中,由于电动汽车随机移动、电池充电特性不稳定或充电组件故障等不确定性,一些电动汽车将无法接受从中央服务器发送的指定充电信号。因此,本文提出了一个反馈回路来预测电动汽车充电行为,从而自适应地调整分配给单个电动汽车的基于时间的控制信号。在此基础上,提出了一种并行运行的分布式DR算法,该算法的目标是在充电不确定的情况下优化电动汽车调度,同时减少对私有信息共享的需求。所提出的分布式算法提高了EV用户的隐私性,收敛速度快,在通信中断和延迟下也能实现最优运行。在低压配电测试网络中,对于不同的电动汽车渗透情况,所提出方法的有效性也得到了数值验证。
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引用次数: 1
Multi-functional control strategy for power quality improvement of three-phase grid using solar PV fed unified power quality conditioner 太阳能光伏馈电统一电能质量调节器改善三相电网电能质量的多功能控制策略
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-08-23 DOI: 10.1049/esi2.12077
Chandrakala Devi Sanjenbam, Priyank Shah, Bhim Singh

This article presents a generalised integrator with a band-pass filter frequency locked loop (GI-BPF-FLL) control algorithm for the solar photovoltaic (SPV)-integrated unified power quality conditioner (SPVUPQC) system. This control algorithm extracts fundamental components (FC) of the distorted and deformed input signals, and it has the competence of eliminating DC-offset. The key objective is to decrease the number of sensors used in the control algorithm of the SPVUPQC system while enabling the power quality enhancement features in the distribution grid. The effectiveness of the presented GI-BPF-FLL control algorithm and its performance comparison with the conventional control algorithm are discussed in both the time domain as well as frequency domain analysis. The SPVUPQC system consisting of a distribution static compensator (DSTATCOM) and a dynamic voltage restorer (DVR), to compensate simultaneously both the voltage distortions, sag/swell etc. as well as current harmonics, reactive power and load currents unbalances etc. The model of the SPVUPQC system is developed in the MATLAB/Simulink environment, and its results are presented to demonstrate its capabilities. The system's validation is also done on the hardware prototype, and it performs effectively for the voltage and current power quality enhancement simultaneously. The load side voltages magnitudes, grid side voltages and the grid currents total harmonic distortions are found within the boundaries specified in the IEEE standard 1159 and the IEEE standard 519.

针对太阳能光伏(SPV)集成统一电能质量调节器(SPVUPQC)系统,提出了一种带通滤波器锁频环(GI-BPF-FLL)控制算法的广义积分器。该控制算法从失真和变形的输入信号中提取基本分量(FC),并具有消除直流偏置的能力。关键目标是减少SPVUPQC系统控制算法中使用的传感器数量,同时使配电网的电能质量增强功能成为可能。在时域和频域分析中讨论了所提出的GI-BPF-FLL控制算法的有效性,并与传统控制算法进行了性能比较。SPVUPQC系统由一个分布式静态补偿器(DSTATCOM)和一个动态电压恢复器(DVR)组成,可以同时补偿电压畸变、凹陷/膨胀等以及电流谐波、无功功率和负载电流不平衡等。在MATLAB/Simulink环境下建立了SPVUPQC系统的模型,并给出了仿真结果。在硬件样机上对系统进行了验证,有效地提高了电压和电流的电能质量。负载侧电压幅值、电网侧电压和电网电流总谐波畸变均在IEEE标准1159和IEEE标准519规定的范围内。
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引用次数: 3
Day-ahead unit commitment for hydro-thermal coordination with high participation of wind power 在风电高度参与的情况下,水电热协调的日前机组承诺
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-08-16 DOI: 10.1049/esi2.12078
Jorge Zuluaga, Carlos E. Murillo-Sanchez, Ricardo Moreno-Chuquen, Harold R. Chamorro, Vijay K. Sood

The variability and uncertainty of renewable resources impose new challenges in the operational planning related to the unit commitment of generation units. The development of day-ahead multi-period optimal power flow, under integration of wind power, requires modelling of multiple scenarios in order to ensure an optimal power flow minimising the generation cost. A progressive hedging approach has been proposed and developed to solve efficiently the unit commitment problem as a two-stage stochastic programming problem to update each stage in parallel. The performance of progressive hedging is compared with a standard mixed-integer linear programming problem. The results indicate that the computation time is 50 times faster than standard mixed-integer linear programming. The test case system is based on a reduced version of the interconnected Colombian system. The comparative results indicate an important reduction in computational time.

可再生能源的可变性和不确定性给发电机组的机组承诺相关的运行规划带来了新的挑战。风电一体化下的日前多时段最优潮流的发展需要对多个场景进行建模,以保证发电成本最小的最优潮流。提出并发展了一种渐进式套期保值方法,将机组承诺问题作为一个两阶段随机规划问题有效地求解,以并行更新每一阶段。将渐进式套期保值的性能与标准的混合整数线性规划问题进行了比较。结果表明,该方法的计算速度是标准混合整数线性规划的50倍。测试用例系统基于相互连接的哥伦比亚系统的简化版本。对比结果表明,计算时间大大减少。
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引用次数: 0
Performance assessment and validation of inverter control current controllers in reduced sensor maximum power point tracking based photovoltaic-grid tied system 基于简化传感器最大功率点跟踪的光伏并网系统逆变器控制电流控制器的性能评估与验证
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-07-04 DOI: 10.1049/esi2.12076
Moushumi Patowary, Hassan Haes Alhelou, Gayadhar Panda

A relative assessment on conventional and adaptive current controllers used in reduced sensor-maximum power point tracking (MPPT) based photovoltaic (PV)-grid tied inverter systems for the improvement of system power quality is suggested. The steady-state and transients errors produced in the conventional PI and proportional resonant controllers, which are used to generate the references, can be fixed by using an intelligent ADALINE-LMS adaptive controller; moreover, it helps in reducing the %THD (total harmonic distortion) level measured at different power zones. Also, to track the maximum PV power, which is further integrated to DC-bus, a reduced sensor-based technology is added into the circuit that sidesteps the problem of tracking local MPP instead of global MPP and the drawbacks of using current sensors. The use of a reduced sensor-based MPPT controller confirms extraction of maximum PV power and it guarantees a constant DC-link voltage under all the possible test conditions. The overall control architectures and system performances, which are tested under different system dynamics, are validated through MATLAB/Simulink as well as experimental findings obtained using the dSPACE RTI 1202 interfacing kit. These experimental results confirm that the adaptive control technique used in reduced sensor-MPPT based PV-grid tied inverter systems performs unbeatably with balanced load and grid voltages, less harmonics, quick response time etc. under the operation of linear, non-linear and transient loads, whereas, conventional controllers are best only for the linear loads.

建议对传统电流控制器和自适应电流控制器在基于简化传感器-最大功率点跟踪(MPPT)的光伏并网逆变器系统中的应用进行相对评价,以改善系统电能质量。采用智能ADALINE-LMS自适应控制器,可以消除传统PI控制器和比例谐振控制器产生的稳态和瞬态误差;此外,它有助于降低在不同功率区测量的%THD(总谐波失真)水平。此外,为了跟踪最大PV功率,将其进一步集成到直流总线中,电路中加入了一种基于传感器的简化技术,避免了跟踪局部MPP而不是全局MPP的问题以及使用电流传感器的缺点。使用基于简化传感器的MPPT控制器确认提取最大PV功率,并保证在所有可能的测试条件下保持恒定的直流链路电压。通过MATLAB/Simulink和dSPACE RTI 1202接口套件验证了不同系统动态下的总体控制体系结构和系统性能。实验结果表明,在线性、非线性和瞬态负载下,基于减小传感器- mppt的自适应控制技术具有负载和电网电压均衡、谐波少、响应时间快等优点,而传统控制器仅适用于线性负载。
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引用次数: 0
An online dispatch approach for distributed integrated multi-energy system considering non-ideal communication conditions 考虑非理想通信条件的分布式综合多能系统在线调度方法
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-06-21 DOI: 10.1049/esi2.12075
Jiaqi Ju, Qi Wang, Ming Ni, Yunlong Hu, Xiao Li

The distributed integrated multi-energy system (DIMS) has many advantages in terms of the utilisation of renewable energy sources and clean energy. Operation strategies for the DIMS based on a real-time profile have been extensively studied. In a DIMS online optimisation problem, besides fluctuations in the renewable energy output and load, inconsistent time scales of the transport dynamics of different energy flows and non-ideal communication (involving communication uncertainty and latency) result in suboptimal operation in dispatch scheduling. An online multi-time-scale optimal operation strategy is proposed for the DIMS to respond to the above challenges, using a hybrid algorithm comprising a model predictive control method and distributed collaborative consensus algorithm (CCA). The approach is based on a hierarchy, comprising rolling optimisation and adjustment. A rolling optimisation is established to schedule operations according to the latest forecast and status information. The rolling dispatch is then adjusted according to the ultrashort-term adjustment using the CCA. Meanwhile, the effect of the information transmission environment on real-time scheduling is considered, and the robust CCA is improved for the implementation of strategies under non-ideal communication conditions. Case studies and results are presented and discussed to show the effectiveness of the proposed approach with the better matching between demand and supply.

分布式综合多能源系统(DIMS)在利用可再生能源和清洁能源方面具有许多优势。基于实时剖面的防空导弹作战策略已经得到了广泛的研究。在DIMS在线优化问题中,除了可再生能源输出和负荷的波动外,不同能量流传输动态的时间尺度不一致以及通信不理想(涉及通信不确定性和延迟)导致调度调度的次优运行。采用模型预测控制与分布式协同共识算法(CCA)相结合的混合算法,提出了一种针对上述挑战的分布式多时间尺度在线优化运行策略。该方法基于层次结构,包括滚动优化和调整。根据最新的预测和状态信息,建立了滚动优化来调度操作。然后利用CCA根据超短期调整对滚动调度进行调整。同时,考虑了信息传输环境对实时调度的影响,针对非理想通信条件下的策略实施,改进了鲁棒CCA。通过案例分析和结果讨论,证明了该方法的有效性,实现了需求和供给之间更好的匹配。
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引用次数: 1
Guest editorial: Secure and resilient operations of cyber-physical urban energy systems 嘉宾评论:网络物理城市能源系统的安全和弹性运行
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-05-19 DOI: 10.1049/esi2.12074
Yan Li
<p>Security and resilience of energy systems have become major concerns in energy engineering. Several recent power grid attacks, including the first known devastating cyber-attack in 2015 and the first US ‘denial of service’ attack to the western power grid in March 2019, remind us of the global challenge represented by energy system attacks launched through the cyber-communication network. Meanwhile, attacks on energy systems are growing in number, causing severe impacts on public health and national security.</p><p>Resilience is playing an essential role in operating a dynamic cyber-physical energy system, such as microgirid. Thus, it is necessary to systematically understand the operation mechanism of a dynamic energy system, to implement proper strategies to improve its resilience subject to disturbances or attacks. To advance those fields, scientific research is needed to study and develop novel technologies, including but not limited to resilience study, resilient control, attack detection, defense strategies, machine learning, and data analytics.</p><p>This Special Issue of IET Energy Systems Integration focuses on Secure and Resilient Operations of Cyber-Physical Urban Energy Systems. Brief descriptions of each of the three papers in the Special Issue are provided below. We encourage the readers to refer to the papers for more details.</p><p>In “Resilience Assessment Methodologies and Enhancement Strategies of Multi-Energy Cyber Physical Systems of the Distribution Network”, Yang et al. introduced an extensive review on the state-of-the-art-research of power systems resilience. They give a definition of the Multi-Energy Cyber Physical Systems resilience and summarise its related characteristics, and the models of extreme disasters and equipment vulnerability are analysed. The qualitative resilience assessment curve, indexes and process of the Multi-Energy Cyber Physical Systems are developed. They present the key improvement measures for the planning and operation of MECPSs resilience and the focus of future research.</p><p>In “Attack and Defence methods in cyber-physical power system (CPPS)”, Yang and Liu focus on dealing with the attacks against complex CPPS, by profiling the structure of CPPS and the potential threats, conducting an in-depth analysis of CPPS attack modes from the cyber and physical subsystems, and summarising the three-level security defense methods for CPPS in detail. The future technological development prospects of CPPS security research are explicitly addressed, which will provide technical support for building reliable, safe, and robust energy systems. Overall, this paper analyses and summarises the typical attack patterns and multi-dimensional defense methods of CPPS and presents four problems that need to be deeply studied and solved in CPPs defense, so as to provide a reference for the subsequent technical development. First, the existing research studies on CPPS security are based on the attacks that have bee
能源系统的安全性和弹性已成为能源工程中的主要问题。最近几次电网攻击,包括2015年首次已知的破坏性网络攻击和2019年3月美国对西方电网的首次“拒绝服务”攻击,提醒我们通过网络通信网络发起的能源系统攻击所代表的全球挑战。与此同时,针对能源系统的攻击越来越多,对公众健康和国家安全造成了严重影响。弹性在运行动态网络-物理能源系统(如微电网)中起着至关重要的作用。因此,有必要系统地了解动态能源系统的运行机制,实施适当的策略,以提高其在受到干扰或攻击时的弹性。为了推进这些领域,需要科学研究来研究和开发新技术,包括但不限于弹性研究、弹性控制、攻击检测、防御策略、机器学习和数据分析。本期IET能源系统集成特刊重点关注网络物理城市能源系统的安全和弹性运行。以下是特刊中三篇论文的简要介绍。我们鼓励读者参考论文了解更多细节。在“配电网多能网络物理系统的弹性评估方法和增强策略”中,Yang等人对电力系统弹性的最新研究进行了广泛的回顾。给出了多能网络物理系统弹性的定义,总结了其相关特征,分析了极端灾害和设备脆弱性模型。建立了多能网络物理系统的定性弹性评估曲线、指标和流程。提出了mecps弹性规划与运行的关键改进措施和未来研究的重点。Yang和Liu在“网络物理电力系统(CPPS)的攻击与防御方法”一文中,通过对CPPS的结构和潜在威胁进行分析,从网络子系统和物理子系统深入分析了CPPS的攻击方式,并详细总结了CPPS的三级安全防御方法,重点研究了针对复杂CPPS的攻击处理。明确了CPPS安全研究的未来技术发展前景,为建设可靠、安全、稳健的能源系统提供技术支撑。总体而言,本文对CPPS的典型攻击模式和多维防御方法进行了分析和总结,提出了CPPS防御中需要深入研究和解决的四个问题,为后续技术发展提供参考。首先,现有的CPPS安全研究都是基于已检测到或已拦截的攻击,缺乏对未知攻击的识别和防御的有效研究。因此,对未知攻击进行无先验信息的识别和主动防御,对提高CPPS的安全性具有重要意义。其次,由于攻击组合的多样性和攻击检测的难度,协同网络物理攻击(CCPA)比网络攻击更具破坏性和隐蔽性。然而,针对CCPA的研究很少,因此针对CCPA的新防御方法是一个值得探索的有趣话题。第三,随着以深度学习和强化学习为代表的新一代人工智能技术的发展,在CPPS攻击检测和安全防御领域显示出强大而良好的应用效果。有必要建立全面的信息收集机制和统一的CPPS攻击样本库。它可以在世界各国之间协作共享。其四,离线仿真主要用于研究CPPS攻防的动态过程,难以体现CPPS中网络子系统和物理子系统复杂、快速的动态演化。因此,迫切需要建立一个真实的试验场,这将对促进CPPS系统风险分析、链故障传播、资源调配和动态武装等方面发挥极其重要的作用。Wang等人在《微电网遭受连续DoS攻击时二次控制系统脆弱性分析》中提出了微电网遭受DoS攻击时的脆弱性评估方法。提出了攻击动作和“N-1”偶然性动作的序列模型来寻找遍历表达式。 通过遍历法,提出的综合脆弱性度量可以解释微网的脆弱性因素,为理解微网二次控制系统的脆弱性提供了一种直观、简便的方法。该指标由四个基本指标组成,这些指标不仅关系到DoS攻击结束时微电网的最终状态,而且关系到微电网的动态过程。为了验证所提出的度量,还提出了两种缓解方法:自适应系数法和容错法,以减轻DoS攻击对物理系统的影响。最后,构建了包含8个dg的33节点微网平台,对提出的脆弱性评估方法进行了测试。研究结果表明,网络程度高的节点是易受攻击的节点,容错方法的平均度量值为9.41,优于自适应系数法的平均度量值9.03。
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引用次数: 0
A framework of system integration and integration value analysis: Concept and case studies 系统集成框架与集成价值分析:概念与案例研究
IF 2.4 Q4 ENERGY & FUELS Pub Date : 2022-05-09 DOI: 10.1049/esi2.12071
Hongjie Jia, Huiyuan Wang, Yan Cao, Yunfei Mu, Xiandong Xu, Xiaodan Yu

In modern society, system integration that enables multiple subsystems to function as one is emerging in various fields like industry, commerce, and infrastructure. Although it has been proved that integration value could be tapped to the maximum with controllable cost by optimising the integration schemes in certain fields, there is still a lack of a general method for modelling and analysing the process of system integration. To address this need, this paper proposes an analysis framework of system integration. The concepts of integration object, integration strategy, integration time, integration cost and integration value are introduced to describe the integration process. Further, three optimisation models of the local optimisation (OPT1), phase optimisation (OPT2) and integration optimisation (OPT3) are constructed. The proposed framework can also supervise and compare the performance of intermediate processes of different integration schemes. Two case studies in the commerce and energy fields are analysed to illustrate the function of the proposed framework.

在现代社会中,能够使多个子系统作为一个子系统工作的系统集成正在工业、商业和基础设施等各个领域中出现。虽然已经证明在某些领域通过优化集成方案可以在可控的成本下最大限度地挖掘集成价值,但目前还缺乏一种通用的方法来对系统集成过程进行建模和分析。针对这一需求,本文提出了一个系统集成的分析框架。引入了集成对象、集成策略、集成时间、集成成本和集成价值等概念来描述集成过程。在此基础上,构建了局部优化(OPT1)、相位优化(OPT2)和集成优化(OPT3)三种优化模型。该框架还可以对不同集成方案中间过程的性能进行监督和比较。分析了商业和能源领域的两个案例,以说明所提出的框架的功能。
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引用次数: 4
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IET Energy Systems Integration
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