An Integrated Planning Approach for Distributed Generation Interconnection in Cyber Physical Active Distribution Systems

Liu, Wenxia; Chen, Ye; Wang, Lingfeng; Liu, Nian; Xu, Huiting; Liu, Zongqi

doi:10.1109/tsg.2019.2925254

Cited by 29 publications

(11 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the continuous maturity and commercialization of P2G technology, the electric-and gas-coupled system composed of gas turbine and P2G facilities makes the two-way flow of energy possible. The comprehensive energy system model constructed in the paper focuses on the energy interconversion process between the power grid subsystem and the gas network subsystem, mainly through the electric gas transfer technology and gas turbine equipment realization [17]. This article takes the regional comprehensive energy system with electric-gas coupling system containing P2G as an example.…”

Section: Figure 1: Comprehensive Energy Dividementioning

confidence: 99%

A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm

Lin¹,

Gong²,

Shi³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

The integrated energy systems, usually including electric energy, natural gas and thermal energy, play a pivotal role in the energy Internet project, which could improve the accommodation of renewable energy through multienergy complementary ways. Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network, a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper. The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm, and thereby achieved a hierarchical and non-repeated sampling. Then, the improved RelieF algorithm is used to identify the feature vectors, calculate the feature weights, and select the preferred feature subset according to the initially set threshold. In addition, a correlation coefficient method is applied to reduce the feature subset, and further eliminate the redundant feature vectors to obtain the optimal feature subset. Finally, the softmax classifier is used to obtain the early warnings of the integrated energy system. Case studies are conducted on an integrated energy system in the south of China to demonstrate the accuracy of fault risk warning method proposed in this paper.

show abstract

Section: Figure 1: Comprehensive Energy Dividementioning

confidence: 99%

A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm

Lin¹,

Gong²,

Shi³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

show abstract

“…In the power transaction of VPPs, multi‐level and multi‐dimensional perception and control of modern power systems in an ADN require accurate and real‐time data exchange. The VPP relies on the close coupling between the physical system and the cyber system of the ADN so that the VPP network reflects the characteristics of typical cyber‐physical system (CPS) 6 . In the CPS network of the VPP, the power flow changes from a unidirectional flow of the traditional distribution network into a bi‐directional flow, causing uncertainty related to the power information exchange 7 .…”

Section: Introductionmentioning

confidence: 99%

“…Studies on the vulnerability of the power grid structure were generally based on the complex network theory, especially the analysis and verification of small‐world (SW) characteristics and scale‐free characteristics in power systems 9,10,11,12,13 . However, some scholars focused on the vulnerability analysis of ADNs 5,6,14 . Cao et al 5 proposed a routing algorithm based on the link‐state protocol to determine the optimum data transmission paths in cyber networks.…”

Section: Introductionmentioning

confidence: 99%

“…The expected load curtailment and expected fault coverage were used to quantify potential system losses using Monte Carlo simulations. Liu et al 6 proposed a cyber‐physical active distribution system to minimize the construction and operation cost of CPSs and maximize the penetration level of distributed generation. Srikantha et al 14 proposed a population game using real‐time and adaptive defense mechanisms based on data aggregation to mitigate the adverse effects of the Stackelberg game attacks that used malicious actuation of large number of small‐scale loads residing in a distribution network.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robustness assessment of the cyber‐physical system against cascading failure in a virtual power plant based on complex network theory

Gao

Yang

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary The combination of a virtual power plant (VPP) and an active distribution network (ADN) can be used to aggregate distributed energy resources of prosumers. The bi‐directional power flow and information flow between prosumers ensure close coupling and interdependence of the power system and the cyber system so that the VPP gradually evolves into a typical cyber‐physical system (CPS). However, even a small cyber attack on the CPS system significantly affects the security and integrity of the VPP. To study robustness of CPS in the VPP, a novel stochastic cascading failure model based on the complex network theory is introduced, considering the impact of various interdependencies and network relationships. First, the centralized and decentralized multi‐agent system (MAS) structures in the VPP are investigated, and the fault propagation mechanism and cascading failure process of the CPS network are established. Secondly, a simple and effective comparison method is proposed to analyze the different network relationships and coupling interdependencies. Thirdly, A new multiple‐to‐multiple inter‐links addition strategy is proposed to enhance the protection of key nodes, and mainly focus on researching the intra‐ and inter‐links addition sensitivity analysis. The numerical simulation shows that optimal network relationship, coupling interdependency, and intra‐links addition strategy are determined by the proposed robustness metrics.

show abstract

“…EV charging model in CPPSs is established [3], but the impact of power generation fluctuations from renewable sources on power system operation is not considered. Multi-objective optimization models are established [4]. These models are employed to realize power flow control and improve power quality.…”

mentioning

confidence: 99%

A Multi-Objective and Multi-Constraint Optimization Model for Cyber-Physical Power Systems Considering Renewable Energy and Electric Vehicles

Zhang

Fei

Sun

et al. 2023

IEEE/CAA J. Autom. Sinica

View full text Add to dashboard Cite

To tackle the global challenges of climate change and energy security, building low carbon energy systems has become a research hotspot. Cyber-physical power systems (CPPSs) is an important infrastructure to link both energy and transport systems, two major sectors that are difficult to decarbonize, and it is necessary to establish CPPSs model to consider the integration of both renewable energy and electric vehicle (EV).It is often extremely challenging to describe the topological structure of CPPSs due to their topological complexities and scales. The aim of this letter is to establish an optimization model with multiobjective and multi-constraint by considering renewable energy and EV. Firstly, the topological structure and the coupling characteristics of power grid and communication network for CPPSs are analyzed. Secondly, to formulate the optimization indexes of power grid and communication network, multiple control objectives are established. The coupling relationship between CPPSs layers is also described and analyzed. Thirdly, the interior point method and fminbnd function are used to solve multi-objective functions. Finally, experimental results confirm that this model can achieve precise control from both power grid and communication network. Related work: CPPSs aim to intelligently integrate the behaviors and actions of all stakeholders in energy supply chain to efficiently deliver sustainable, economic, and secure electric energy. To make energy supply more flexible, portable and safer, CPPSs control must enhance the cooperation and interaction between power grid and communication network [1][2]. EV charging model in CPPSs is established [3], but the impact of power generation fluctuations from renewable sources on power system operation is not considered. Multi-objective optimization models are established [4]. These models are employed to realize power flow control and improve power quality. However, most of these models only consider single objective, while real power grid model needs to meet multiple different control objectives. A CPPS conceptual is established based on the concepts of complex network theory [5], which however does not provide mathematical models for CPPSs that can be used for the optimization purpose. State space models of CPSs are developed [6-7], which provided mathematical representations of dynamic behavior and structural characteristics of CPSs, but these models lack physical meanings, hence it is difficult to yield meaningful results. Table Ⅰ. Comparison of the Proposed and Related Energy Models Renewable energy power grid communication network

show abstract

An Integrated Planning Approach for Distributed Generation Interconnection in Cyber Physical Active Distribution Systems

Cited by 29 publications

References 21 publications

A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm

A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm

Robustness assessment of the cyber‐physical system against cascading failure in a virtual power plant based on complex network theory

A Multi-Objective and Multi-Constraint Optimization Model for Cyber-Physical Power Systems Considering Renewable Energy and Electric Vehicles

Contact Info

Product

Resources

About