Support Network Operators Research Articles

Critical infrastructure monitoring in CBRNe scenarios: a reliable and robust communication network for distributed multimodal sensors

The malicious misuse of CBRNe agents can inflict extensive damage to critical infrastructure and terrorize public society. The effects of such attacks can range from financial or structural drawbacks to significant casualties. Recent terror attacks in Cucuta (2021) or Kabul (2021) demonstrate the need to protect infrastructures such as airports, power plants, and transportation infrastructure. In the face of these modern-day threats, the need for a reliable and effective monitoring system for critical infrastructure has become increasingly important. In a first contribution to the long-term development, we present an initial version of a concept that requires the implementation paradigm of diverse redundancy and secure communication using MQTTS relying on the included cipher suite. An initial set of node types is defined and assigned requirements for implementation. The software tools architecture we propose based on these requirements is designed to support network operators and developers by providing standard features for network management and sensor node implementation. This includes the definition of a secure semi-automatic onboarding process for new sensor nodes, which is presented in detail. We strive for independency from specific hardware platforms, software frameworks, and network technologies to enable an open standard for communication within a critical infrastructure sensor network and also between such networks in the future.

Graph-based Data Mining, Pattern Recognition and Anomaly Detection for Intelligent Energy Networks

Intelligent Energy Networks play an important role in the contemporary landscape of energy production and distribution, and the large amount of data produced by their smart sensors recently caused a great deal of interest in Data Analysis and Data Mining strategies to support network operators in optimizing operations, reliability and profitability. This work proposes for the network operator an unified data analytics framework, composed by clustering, anomaly detection and knowledge propagation algorithms, and based on a graph representation of the measurements dataset. The usage of the graph is particularly suited with multivariate and high-dimensional time series characterizing large and complex energy networks, it allows to express additional attributes on the data points and hence incorporate previous expert’s knowledge, and the leveraging of the graph structure and connectivity naturally captures dependencies among data for discovering energy patterns and anomalies in the original energy network. The effectiveness of the presented graph-based framework is validated on a number of real-world cases and private operators of District Networks.

Traffic-Aware Energy-Efficient Resource Allocation for RSMA Based UAV Communications

Traffic measurement will play an essential role in future networks to reveal the traffic requirements of the users, which will support network operations like resource allocation. In this paper, we study the traffic-aware resource allocation problem for downlink rate-splitting multiple access (RSMA) based unmanned aerial vehicle (UAV) communications. Specifically, with the help of traffic measurement, user requirements on achievable rate are known as prior knowledge to the UAV. Considering user requirements, we maximize the energy efficiency of the UAV by jointly optimizing the UAV deployment, beamforming, rate allocation, and subcarrier allocation. To overcome the non-convexity of the above problem, a joint optimization is developed to solve it iteratively. First, a heuristic approach is proposed to find the three-dimensional location of the UAV. Then, successive convex approximation approach is utilized to optimize RSMA parameters. Moreover, we formulate the subcarrier allocation problem as a many-to-one two-sided matching game, which is tackled by the swap matching algorithm. Numerical results suggest that the proposed subcarrier allocation scheme outperforms benchmark schemes, and RSMA based schemes perform close to that based on non-orthogonal multiple access, which all outperform orthogonal frequency division multiple access based scheme.

Avoiding Overconfidence in Predictions of Residential Energy Demand Through Identification of the Persistence Forecast Effect

Forecasting domestic electricity consumption is important for a wide range of modern power system solutions and smart applications that support network operation, grid stability, and demand-side management, most of which depend on robust and accurate predictions. The methods producing these predictions infer future load from statistical regularity in historical data. If such regularity is lacking, predictions then regress towards the most recently observed consumption value used in the input set. Predictions then follow the actual load data one step behind in time, potentially affecting the robustness of predictions and functionality of applications. Current evaluation methods do not detect this behaviour which may result in overconfidence in prediction results. In this study, we I) define and systematically analyse this behaviour, which we label the Persistence Forecast Effect and illustrate its impacts, II) propose a novel method, called 1-Step-Shifting, to detect its presence, and III) analyse and establish the relationship between irregularity in data and the effect. Further, we provide a case study applying state-of-the-art forecasting techniques to a real-world dataset of electricity consumption data from 69 households in order to demonstrate the Persistence Forecast Effect, its implications, and its relationship to statistical regularity in historical data.

DIVE: A distributed ID assignment and topology discovery protocol for underwater acoustic networks

This paper presents the DIVE protocol, which is designed to self assign unique node IDs in an underwater acoustic network. DIVE, which stands for Distributed Id assignment and topology discoVEry, is fully distributed and does not assume any prior knowledge of the network. One of the objectives of the DIVE protocol is the assignment of short IDs to the node, thus reducing the number of bits required to encode this information. Link quality information is explored to increase the robustness of the protocol against message losses. While discovering the network and assigning short node IDs, control data is shared to collect additional information about the network nodes, such as the type (static or mobile) and the number of hops to reach them. This information then can be used to support network operations. The protocol performance has been evaluated via simulations and during two at-sea campaigns: the 2016 Recognized Environmental Picture exercise (REP16), conducted in the Atlantic Ocean, and the 2017 Communications Network trial (CommsNet17), conducted by the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (CMRE) in the Gulf of La Spezia, Italy. A variety of networking scenarios have been explored to validate the proposed solution, including node mobility as well as node addition and removal. The results show that DIVE is an efficient and reliable solution for node ID assignment and network discovery that scales with the network size in the presence of an unreliable communication channel. Additionally, when compared to a state-of-the-art solution, the usage of short IDs can significantly reduce the energy consumption and prolong the network lifetime.

Automatic Identification of Different Types of Consumer Configurations by Using Harmonic Current Measurements

Power quality (PQ) is an increasing concern in the distribution networks of modern industrialized countries. The PQ monitoring activities of distribution system operators (DSO), and consequently the amount of PQ measurement data, continuously increase, and consequently new and automated tools are required for efficient PQ analysis. Time characteristics of PQ parameters (e.g., harmonics) usually show characteristic daily and weekly cycles, mainly caused by the usage behaviour of electric devices. In this paper, methods are proposed for the classification of harmonic emission profiles for typical consumer configurations in public low voltage (LV) networks using a binary decision tree in combination with support vector machines. The performance of the classification was evaluated based on 40 different measurement sites in German public LV grids. This method can support network operators in the identification of consumer configurations and the early detection of fundamental changes in harmonic emission behaviour. This enables, for example, assistance in resolving customer complaints or supporting network planning by managing PQ levels using typical harmonic emission profiles.

Distributed Control of Clustered Populations of Thermostatic Loads in Multi-Area Systems: A Mean Field Game Approach

Thermostatically controlled loads (TCLs) can effectively support network operation through their intrinsic flexibility and play a pivotal role in delivering cost effective decarbonization. This paper proposes a scalable distributed solution for the operation of large populations of TCLs providing frequency response and performing energy arbitrage. Each TCL is described as a price-responsive rational agent that participates in an integrated energy/frequency response market and schedules its operation in order to minimize its energy costs and maximize the revenues from frequency response provision. A mean field game formulation is used to implement a compact description of the interactions between typical power system characteristics and TCLs flexibility properties. In order to accommodate the heterogeneity of the thermostatic loads into the mean field equations, the whole population of TCLs is clustered into smaller subsets of devices with similar properties, using k-means clustering techniques. This framework is applied to a multi-area power system to study the impact of network congestions and of spatial variation of flexible resources in grids with large penetration of renewable generation sources. Numerical simulations on relevant case studies allow to explicitly quantify the effect of these factors on the value of TCLs flexibility and on the overall efficiency of the power system.

Water Loss Management in Small Municipalities: The Situation in Tyrol

Water losses in water distribution networks (WDNs) are unavoidable. Water losses are evaluated based on performance indicators (PIs) and used for future recommendations for network operators to take measures against water losses. However, these evaluations primarily focus on large and medium sized WDN and do not deal with the challenges of small WDNs (e.g., technical, and financial limitations, missing data). Therefore, an appropriate water loss management is a major challenge for operators in the federal state of Tyrol (Austria) due to the high number of small WDNs, e.g., low income in combination with long network lengths. In this regard, this work specifies and discusses state funding in Austria to support network operators to reduce water losses. To assess the impacts on management strategies, 40 WDNs, supplying 200 to 16,000 inhabitants, are investigated in detail. As the comparison of different PIs shows, a volume related PI (e.g., water loss volume divided by total water demand) is recommend as the decision criterion for local authorities due to minimal efforts and its easy calculation. Moreover, public funding helps to significantly reduce water losses in individual systems, but countermeasures should be different for small and larger WDNs. For example, leakage detection campaigns and rehabilitation planning based on pipe age should be established in future for larger WDNs in Tyrol. In contrast, an online flow metering system to monitor system inflows is suggested for small WDNs. Based on measurement data, leakages and burst can be detected and repaired swiftly.

Migration Paths for Smart Grids and Their Evaluation Using a Case Study

This contribution will deal with the topic of migration paths in the Smart Grid domain. Migration paths - defined as development steps from one development stage to the next - will be investigated to support network operators in planning the processes and technologies necessary to meet the future requirements of the energy system transformation. For this purpose, a process model was developed which is presented and applied on the basis of a case study. The dependencies and influences between the dimensions considered are investigated and an algorithm is developed and used for their qualitative evaluation. By analyzing and evaluating the migration paths, particularly critical development steps on the entire roadmap that require special control can be shown to the distribution grid.

Control of Energy Storage

In the attempt to tackle the issue of climate change, governments across the world have agreed to set global carbon reduction targets. [...]

Optimal design of Information Centric Networks

Information-Centric Networking (ICN) has recently gained momentum as a promising paradigm for the next-generation Internet architecture. The first prototypes for ICN-capable routers have already been developed; however, to migrate the devices to this novel architecture, non-negligible investments should be made. Therefore, it is of utter importance to provide clear quantitative insights of the expected economic benefits that operators will experience by switching to the ICN paradigm. For these reasons, in this paper we tackle the content-aware network-planning problem, and we formulate a novel optimization model to study the migration to an ICN, in a budget-constrained scenario. Our formulation takes into accurate account traffic routing and content caching. We prove that the optimization problem is NP-Hard, then we formulate heuristics to efficiently solve it. An extensive simulation campaign with real network topologies shows that our greedy heuristic cuts the computation time while finding close to optimal solutions, and therefore can effectively support network operators to evaluate the effects of a migration to ICN.

Recovery and Resource Allocation Strategies to Maximize Mobile Network Survivability by Using Game Theories and Optimization Techniques

With more and more mobile device users, an increasingly important and critical issue is how to efficiently evaluate mobile network survivability. In this paper, a novel metric called Average Degree of Disconnectivity (Average DOD) is proposed, in which the concept of probability is calculated by the contest success function. The DOD metric is used to evaluate the damage degree of the network, where the larger the value of the Average DOD, the more the damage degree of the network. A multiround network attack-defense scenario as a mathematical model is used to support network operators to predict all the strategies both cyber attacker and network defender would likely take. In addition, the Average DOD would be used to evaluate the damage degree of the network. In each round, the attacker could use the attack resources to launch attacks on the nodes of the target network. Meanwhile, the network defender could reallocate its existing resources to recover compromised nodes and allocate defense resources to protect the survival nodes of the network. In the approach to solving this problem, the “gradient method” and “game theory” are adopted to find the optimal resource allocation strategies for both the cyber attacker and mobile network defender.

Electric Vehicle Scenario Simulator Tool for Smart Grid Operators

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operators’ planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

Balancing Autonomy and Security Over Geotracking Patients with Alzheimer's Using a Personalized Geotracking System with Social Support Network

Systems for geotracking Alzheimer's Disease patients with dementia are reported to raise ethical issues and concerns. Studies stated possible loss of freedom and autonomy for patients, along with violations of their privacy, which may lead to loss of prestige/dignity. In this study, a personalized geotracking system that aims to balance patient security and need for privacy and autonomy is proposed. In addition, the system tries to form and organize a social support network among family caregivers to help each other locating patients during wandering episodes. The system introduces a personalized, four-level temporal geofence based tracking, warning and notification protocol that incorporates a safety check mechanism operating over Global System for Mobile Communications network. It is under development using Java and will be evaluated by using both qualitative and quantitative methods. In this paper, personalization, system architecture and social support network operation principles are presented.

Active contribution of PV inverters to voltage control – from a smart grid vision to full-scale implementation

For demonstrating future smart grid concepts the MetaPV project, funded by the European Commission, is investigating the additional services of smart photovoltaic (PV) systems for grid support and hosting capacity extension. In this paper the concept of hosting capacity is introduced and illustrated to analyze the impact of expected PV development scenarios on the distribution network selected for the demonstration. Investigations showed that the hosting capacity is currently almost fully exhausted and that network reinforcement would be necessary in order to host the expected PV generation by 2020. Also, the concept of smart PV inverters, which are under development in the frame of the project, is introduced. Such inverters should support network operation through their active and reactive power control possibilities for standalone and supervisory operations and enable the enhancement of the hosting capacity. A short overview on the next steps towards demonstration is provided.

On using nomadic services for distributed intelligence

This paper presents a next generation integrated IN architecture among Flexible Intelligent Network Elements (FINE) based on the multimedia multimode (client, server and agent) IN Service Node concept (Proc. ICCE '97, Cannes (1997) 77), to perform a crafty Unified Media Communications Service (UMCS) across heterogeneous networks. The FINE architecture represents a network of configurable interworking elements allowing user access to a Unified Message Store (UMS) and Universal Communications Channel (UCC) via traditional PSTN/ISDN/PLMN equipment such as telephones, pagers and fax machines on the one side, and networked computers and mobile terminals equipped with mail readers and Web browsers on the other side, to enable both on-line and off-line interactions. A virtual cluster of FINEs within an integrated personal communications network is dynamically configured in a distributed or centralised manner according to user profile requirements, network size and performance to provide artful messaging, telephony and I 3E services (Intelligent Inter-, Intra- and Extranet) in a changing environment. The FINE consists of a Channel Matrix Switch (CMS), several Resource Platforms (RP) containing Media Conversion Processors (MCP) and Channel Managers (CM) to perform the media translation and routing in the required interchange formats, an Internet Gateway (IG) to hold the subscribers' mailboxes and provide the internet connectivity, and a FINE Controller (FINEC) to realise the FINE Service Logic (FSL) and manage the FINEs. Each FINEC can be deployed in some of the three modes — independent (server), dependent (client) and autonomous (agent) — with respect to the user/network configuration, thus allowing a dynamically configurable (per user/ per node/ per service) centralised or distributed service architecture. The FINE itself is organised along with other nodes by a Network Operation Support Environment (NOSE), a service oriented and TMN compliant Operation, Administration & Maintenance Centre. Service logic can be transferred, installed and mounted on demand among the FINE Controllers and the terminal equipment to provide optimal QoS.

Computer‐aided protective relay setting system for large power networks

AbstractThis paper introduces a protective relay setting system capable of handling a large network up to 10,000 buses. The remarkable features are such useful functions as network analysis (fault analysis, load flow calculation, zero‐sequence current calculation, etc.), relay operation simulation, and automated setting coordination tasks.Fault currents in the maximum and the minimum operation networks are calculated to examine the setting values. The protection zones are searched automatically along the network connection. Protection coordination tasks among the primary and the backup relays composed of different types of relays can be performed by the relay operation simulation.The system is built on an engineering workstation, which works in cooperation with other network operation support systems. Its graphical user interface helps every engineer to examine the relay setting using a variety of databases.

Using fuzzy sets to model the uncertainty in the fault location process of distribution networks

In the computerized fault diagnosis of distribution networks the heuristic knowledge of the control center operators can be combined with the information obtained from the network database and SCADA system. However, the nature of the heuristic knowledge is inexact and uncertain. Also the information obtained from the remote control system contains uncertainty and may be incorrect, conflicting or inadequate. This paper proposes a method based on fuzzy set theory to deal with the uncertainty involved in the process of locating faults in distribution networks. The method is implemented in a prototype version of the distribution network operation support system. >

大規模系統の故障解析・動作検証機能を備えたリレー整定支援システム

This paper introduces a protective relay setting system capable of handling a large network up to 10,000 buses. The remarkable features are such useful functions as network analysis (fault analysis, load flow calculation, zero-sequence current calculation, etc.), relay operation simulation, and automated setting coordination tasks. Fault currents in the maximum and the minimum operation networks are calculated to examine the setting values. The protection zones are searched automatically along the network connection. Protection coordination tasks among the primary and the backup relays composed of different types of relays can be performed by the relay operation simulation. The system is built on an engineering workstation, which works in cooperation with other network operation support systems. Its graphical user interface helps every engineer to examine the relay setting using a variety of databases.

Family support networks among elders in a native American community: Contact with children and siblings among the prairie band potawatomi

Although a great deal is known about family support networks among older whites, little is known about the workings of family support networks among elderly Native Americans. Face-to-face interviews focused on the availability and proximity of kin and the frequency of nine common family activities with each child and sibling. The effects of proximity, gender, marital status, and the equity of helping relationships on family support network operation are analyzed revealing similarities and differences with previous research findings among Anglos. Differences with previous research findings include that the strongest sibling tie is between brothers rather than between sisters, the presence of a spouse insulates elders rather than invigorates contact within the network, and marital dissolution (whether through widowhood, divorce or separation) does not isolate elders from children or siblings. The study concludes with suggestions for future research to refine our understanding of family support network operation.