Network Assets Research Articles

Network operators and the transition to decentralised electricity: An Australian socio-technical case study

A socio-technical transitions theory approach is used to consider the extent to which network operators in Western Australia are perceived as facilitating, or blocking, a transition towards a distributed generation-based network. A total of 48 semi-structured, in-depth interviews with community, industry and government representatives were performed in 2015. This research finds that network operators are perceived as ‘pushing back’ on distributed generation by increasing the complexity, cost and unreliability of connection applications, by restricting further connection of distributed generation to the network, and by requiring consumers to invest in technology for grid protection. Interview respondents suggest network operators do this because: distributed generation creates technical issues at the distribution-scale of the network; distributed generation can reduce financial revenue for the network operator; as a response to a lack of strategic direction on how network operators should respond to distributed generation; and due to a ‘risk averse’ engineering culture that rejects the unknown. Government intervention may be required to direct network operators to address technical implications of increased distributed generation and redevelop tariff models to allow fair cost recovery of network assets. However, government intervention may lead to adverse outcomes, including in relation to the cost-recovery of state-owned assets.

Procuring load curtailment from local customers under uncertainty.

Demand side response (DSR) provides a flexible approach to managing constrained power network assets. This is valuable if future asset utilization is uncertain. However there may be uncertainty over the process of procurement of DSR from customers. In this context we combine probabilistic modelling, simulation and optimization to identify economically optimal procurement policies from heterogeneous customers local to the asset, under chance constraints on the adequacy of the procured DSR. Mathematically this gives rise to a search over permutations, and we provide an illustrative example implementation and case study.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'.

Integrating multivariate techniques in bridge management systems

The use of bridge management systems (BMS) by infrastructure stakeholders has led to the collection and retention of large quantities of data concerning the condition states of bridges throughout national and regional networks. The database for the BMS is often populated by the results of routine visual inspections, based on a prescribed scale for defining the condition state of the bridge’s individual elements, and of the bridge structure as a whole. The populating of the database also leads to the storage of large quantities of so-called metadata; which can describe the physical parameters of the bridge. The availability of this data allows the assessment of the BMS using multivariate techniques to enhance the life-cycle assessment of bridge networks, through advanced descriptive and predictive techniques applied to deteriorating network assets. Multivariate techniques such as principal component analysis have been demonstrated by the authors to be effectively applied as a descriptive tool to an existing BMS, and the results of a case study of a large dataset of bridges indicate its viability to be integrated into data-based approaches to infrastructural asset management.

Frequency response services designed for energy storage

Energy Storage Systems (ESS) are expected to play a significant role in regulating the frequency of future electric power systems. Increased penetration of renewable generation, and reduction in the inertia provided by large synchronous generators, are likely to increase the severity and regularity of frequency events in synchronous AC power systems. By supplying or absorbing power in response to deviations from the nominal frequency and imbalances between supply and demand, the rapid response of ESS will provide a form of stability which cannot be matched by conventional network assets. However, the increased complexity of ESS operational requirements and design specifications introduces challenges when it comes to the realisation of their full potential through existing frequency response service markets: new service markets will need to be designed to take advantage of the capabilities of ESS. This paper provides new methods to analyse and assessing the performance of ESS within existing service frameworks, using real-time network simulation and power hardware in the loop. These methods can be used to introduce improvements in existing services and potentially create new ones. Novel statistical techniques have been devised to quantify the design and operational requirements of ESS providing frequency regulation services. These new techniques are demonstrated via an illustrative service design and high-resolution frequency data from the Great Britain transmission system.

A cross-sector analysis of human and organisational factors in the deployment of data-driven predictive maintenance

Domains such as utilities, power generation, manufacturing and transport are increasingly turning to data-driven tools for management and maintenance of key assets. Whole ecosystems of sensors and analytical tools can provide complex, predictive views of network asset performance. Much research in this area has looked at the technology to provide both sensing and analysis tools. The reality in the field, however, is that the deployment of these technologies can be problematic due to user issues, such as interpretation of data or embedding within processes, and organisational issues, such as business change to gain value from asset analysis. 13 experts from the field of remote condition monitoring, asset management and predictive analytics across multiple sectors were interviewed to ascertain their experience of supplying data-driven applications. The results of these interviews are summarised as a framework based on a predictive maintenance project lifecycle covering project motivations and conception, design and development, and operation. These results identified critical themes for success around having a target- or decision-led, rather than data-led, approach to design; long-term resourcing of the deployment; the complexity of supply chains to provide data-driven solutions and the need to maintain knowledge across the supply chain; the importance of fostering technical competency in end-user organisations; and the importance of a maintenance-driven strategy in the deployment of data-driven asset management. Emerging from these themes are recommendations related to culture, delivery process, resourcing, supply chain collaboration and industry-wide cooperation.

Scalable Anti-Censorship Framework Using Moving Target Defense for Web Servers

Although the Internet has become a hub around which every aspect of our lives—from commerce to leisurely activities—is centered, many around the world are not able to freely access information over the Internet. Some governments censor what the people can and cannot see. In this paper, regardless of the socio-political view points, we focus on the design of anti-censorship technology that can be implemented on the side of the information purveyors. The primary objective is to develop a framework for combating censorship. Our approach aims to make it too expensive and impractical for the adversary to censor Web sites. In particular, we propose the use of Mobile IPv6 to form a moving target defense strategy, where the Web servers logically behave as if they are the mobile nodes (without actually moving). The potential efficacy of this framework is modeled analytically. Probabilistic models are used to derive important metrics and parameters. One key factor termed swarming ratio enables hosting sites to reason about the amount of resources needed to force the adversary’s costs over practical limits. This model is used to guide the performance goals and architectural setup of the prototype implementation (modifications are made on the server-side software and Kernel without changing the standard Mobile IPv6 protocol). Hence, the solution can be utilized without any changes to the existing network infrastructure. Furthermore, we introduce a novel, credit-based accounting strategy for grouping of users to drastically shift resource requirements in our favor. Lab-based tests are used to measure performance overheads, and based on the findings, targeted optimizations are performed to consider practical deployment scenarios. The end result is a solution that may also be combined with existing anti-censorship methods (that are end-user-based and/or assisted by friendly network assets) to form a robust anti-censorship solution.

Global Vehicle Supply Chains in Humanitarian Operations: A Network Analysis Approach

International humanitarian organizations (IHOs) respond to mega disasters while maintaining development programs in the rest of the world (ROW). This means an IHO’s asset supply network must perform the challenging task of supporting a fast disaster response while simulta- neously maintaining cost-effective ROW development programs. We study how supply network asset flows are impacted during a mega disaster response and find that resource fluidity, the capability to reallocate resources quickly, impacts both mega disaster and ROW program asset flows within these supply networks. Using data from a large IHO’s response to a mega disaster and econometric models, we find a dependency between ROW asset flow and mega disaster asset flow in IHOs with resource fluidity. As mega disaster flow increases, there is a decrease in hub-to-hub ROW asset flows and an increase in other ROW asset flows. This is contrary to most humanitarian operations research, which typically assumes independent asset flows. Because of resource fluidity, the combination of these flows does not compromise ROW operations. We use these empirical results to feed a simulation analysis that extends our research to IHOs without resource fluidity and provides actionable insights for varying types of IHOs in various demand scenarios. Simulation insights illustrate that resource fluidity impacts IHO asset supply network costs and optimal configurations.

Subjective perception scoring: psychological interpretation of network usage metrics in order to predict user satisfaction

Experiences of users determine their actions and therefore have great influence on the business result of service providers. Thus, it is highly important to know and control these experiences. Decisions and actions are most effective if they are based on individual users and their detailed experience history. Currently available methods for measuring user experience fail in providing sufficient detail or continuous availability. This paper introduces a big data analytics method, which predicts every user’s satisfaction with the service provider. This is performed using an analytics algorithm, adding psychological interpretation to the measured and individually perceived user’s quality of experience. The result is a score that enables individualized marketing and allows understanding the cause of dissatisfaction. It is also able to assign a subjective quality score to network assets.

Organization of Public Safety Networks: Spillovers, Interoperability, and Participation

We analyze trade‐offs in the organization of public safety networks when network assets are distributed across districts and a district values network assets in its own and other districts. Comparing centralized, decentralized, and mixed organization forms, we capture two critical properties: interoperability among distributed technology‐based network assets and the ability of districts to opt‐in or opt‐out of the centralized form. We model the provision of public safety networks, where network assets are chosen by each district or by a federal government, where these assets have a positive cross‐district spillover that depends on interoperability, where investments in effort can be made to improve interoperability, and where districts can opt‐in or opt‐out of centralized provision. With the adoption of centralized, decentralized, or mixed provision as a result of districts' opt‐in or opt‐out choices, we identify conditions that determine when the districts deviate from the social optimum and thus regulatory intervention is beneficial to incent the socially optimal organization form. We show how the socially optimal organization form can be achieved through policy instruments such as a sharing rule for the cost of interoperability effort and direct government grants.

Study of Failure Mode and Effect Analysis (FMEA) on Capacitor Bank Used in Distribution Power Systems

Failure Mode and Effect Analysis (FMEA) is the systematic procedure for the analysis and assessment of the potential failure of the equipment. Failure modes of the equipment, causes and effects of the failure modes, detection methods and mitigation methods, as well as the severity of the effects and frequency are specified in the FMEA. This study is a part of the project consultancy services for preparation of network asset maintenance standards & associated asset management documentation which are carried out by Monenco consulting engineering company (Iran) for Majan Electricity Company SAOC (Oman). This paper presents FMEA and related worksheets for capacitor banks used in Oman distribution power system and consist of following items: component of the equipment, functions of the component, failure modes of the component, failure causes, failure effect (local and final), detection method, compensating provision, severity of the effect and eventually frequency of the failure modes. This method can be utilized for FMEA execution of all other equipment of the power distribution system. The output of the FMEA can be utilized for critically analysis, Reliability centered maintenance (RCM) and risk based maintenance initiatives.

Hierarchical and distributed control concept for distribution network congestion management

Congestion management is one of the core enablers of smart distribution systems where distributed energy resources are utilised in network control to enable cost-effective network interconnection of distributed generation (DG) and better utilisation of network assets. The primary aim of congestion management is to prevent voltage violations and network overloading. Congestion management algorithms can also be used to optimise the network state. This study proposes a hierarchical and distributed congestion management concept for future distribution networks having large-scale DG and other controllable resources in MV and LV networks. The control concept aims at operating the network at minimum costs while retaining an acceptable network state. The hierarchy consists of three levels: primary controllers operate based on local measurements, secondary control optimises the set points of the primary controllers in real-time and tertiary control utilises load and production forecasts as its inputs and realises network reconfiguration algorithm and connection to the market. Primary controllers are located at the connection point of the controllable resource, secondary controllers at primary and secondary substations and tertiary control at the control centre. Hence, the control is spatially distributed and operates in different time frames.

Utility-Scale Estimation of Additional Reinforcement Cost From Three-Phase Imbalance Considering Thermal Constraints

Widespread three-phase imbalance causes inefficient uses of low voltage (LV) network assets, leading to additional reinforcement costs (ARCs). Previous work that assumed balanced three phases underestimated the reinforcement cost throughout the whole utility by more than 50%. Previous work that quantified the ARCs was limited to individual network components, relying on full sensory data. This paper proposes a novel methodology that will scale the ARC estimation at a utility level, when the data concerning the imbalance of circuits or transformers are scarce. A novel statistical method is developed to estimate the volume of assets that need to be invested by identifying the relationship between the triangular distribution of circuit imbalance and that of circuit utilization. When there are more data available in future, accurate probability distributions can be constructed to reflect the network condition across the whole system. In light of this, two novel generalized ARC estimation formulas are developed that account for generic probability distributions. The developed methodology is applied to a real utility system in the UK, showing that: 1) three-phase imbalance leads to ARCs that are even greater than the reinforcement costs in the balanced case; 2) a 1% increase in the demand growth rate, the maximum degree of imbalance (DIB) and the maximum nominal utilization rate leads to over 10%, approximately 1% and 2% increases in the ARCs, respectively; and 3) the ARC is not sensitive to the minimum DIB values and the minimum nominal utilization rates.

Assessing preferences for sewer network asset management in France

This article aims to contribute to the limited literature dealing with the disturbance caused to local residents by malfunctioning sewer networks. It explores the preferences of residents in the Eurometropole de Strasbourg (France), with the aim of redefining priorities for sewer network asset management. Valuation is performed using the contingent ranking method and results are compared to a recoded choice experiment. Comparison of results from both methods reveals that price influences the ranking of the different alternatives given to the respondents, but does not influence respondents' preferred alternative. In other words, the price of the alternatives is only considered by respondents later in the decision process. For residents, the trade-offs between the potential disruption caused by a network malfunction favour the reduction of the risk of flooding (either in terms of their frequency or attained water levels). These findings highlight the challenges of asset management.

Cognitive Radio Based Sensor Network in Smart Grid: Architectures, Applications and Communication Technologies

The cognitive radio-based sensor network (CRSN) is envisioned as a strong driver in the development of modern power system smart grids (SGs). This can address the spectrum limitation in the sensor nodes due to interference cause by other wireless devices operating on the same unlicensed frequency in the Industrial, Scientific and Medical band. These sensor nodes are used for monitoring and control purposes in various components of a SG, ranging from generation, transmission, and distribution, and down to the consumer, including monitoring of utility network assets. A reliable SG communication network architecture is required for transferring information which needed by the SG applications, alongside the monitoring and control by CRSN. Hence, this paper investigates and explores the CRSN conceptual framework, and SG communication architecture with its applications; vis-a-vis the communication access technologies, including implementation design with quality of service support. Consequently, this paper highlights various research gaps, such as implementation design model, utilization of LPWAN for CRSN based SG deployment, and so on. This includes discussion on the future direction for various aspects of the CRSN in SG. To address these research gaps, we introduced a smart unified communication solution to improve the efficiency of the SG and mitigate various associated challenges.

Assessing preferences for sewer network asset management in France

Assessing preferences for sewer network asset management in France

A regulatory framework for an evolving electricity sector: Highlights of the MIT utility of the future study

The electric power sector is once again evolving. A variety of distributed energy resources and improving computation, communication, and control technologies create an unprecedented degree of choice for electricity consumers, choices that are poorly guided by electricity rates and other incentives designed for a comparatively simpler era. These technologies also create new tools for regulated utilities, competitive suppliers, and other businesses to employ in the provision of electricity services. This paper summarizes the findings of a two-year, multidisciplinary MIT Energy Initiative research effort, the Utility of the Future study, and outlines a framework for proactive electricity regulation, market, and policy reform designed to enable the efficient evolution of the power sector over the next decade and beyond. Recommendations include a comprehensive system of efficient prices and charges for all electricity users, enhanced regulation of distribution utilities, careful reconsideration of industry structure to avoid conflicts of interest, and improvements to electricity markets. Together, this framework is intended to establish a level playing field for the provision and consumption of electricity services and enable the integration of a cost-effective combination of centralized generation, conventional network assets, and emerging distributed resources, whatever that mix may be.

Agent-based unified approach for thermal and voltage constraint management in LV distribution network

Rapid proliferation of the distributed energy resources (DERs) poses operational challenges for the low-voltage (LV) distribution networks in terms of thermal overloading of the network assets along with voltage limit violations at the connection points. A number of market-based and direct control approaches have been widely developed to tackle these challenges with different objectives. While most of the techniques aim to solve the problems separately, an integrated and efficient method is missing to handle such correlated issues simultaneously. In this study, a unified approach combining local voltage control mechanism with a centralized congestion management scheme is proposed by utilizing an agent-based hierarchical architecture. The feasibility of the proposed approach is validated with a simulation analysis for a representative Dutch urban LV network considering up to 100% penetration of solar PV and electric heat pumps (HPs). The quantitative analysis reveals that, local voltage control strategies can essentially aid mitigating thermal overloading of the network assets. Thus, integrating a local voltage control method with a coordinated congestion management mechanism can enhance the system flexibility while maintaining the network constraints and the comfort levels of the consumers simultaneously.

A Cost-Sensitive Entropy-Based Network Security Situation Assessment Model

Network intrusion attempts have been on the rise recently. Researchers have shown an increased interest in assessing the security situation for entire network instead of single asset. A considerable amount of assessment models have been designed. However, there is a lack of solid and standard guidelines to define the importance of network asset. In addition, based on our knowledge, no research has been found that adequately covered the cost factor in the assessment model. Thus, the purpose of this paper is to propose a cost-sensitive entropy-based network security situation assessment model. With the aid of Analytic Hierarchy Process (AHP), the model can quantitatively determine the importance of assets in the network by considering the tangible and intangible criteria. To verify the performance of proposed model, a simulation of National Advanced IPv6 Centre (NAv6)’s network environment has been setup. The simulation results regarding security situation in particular time-interval are promising. Hence, the proposed model is able to provide network administrator a more reliable reference before any further decision making for the organization’s network.

Transmedia space battles: reference materials and miniatures wargames in 1970s Star Trek fandom

During the 1970s, Star Trek expanded transmedially not through traditional spin-offs in television and film (although those would come later) but through the work of craft-oriented fans who materialised and embroidered the franchise’s fictional universe while converting it to inhabitable and playable form. In conversation with fan-created reference materials such as Franz Joseph’s Starfleet Technical Manual and Star Trek Blueprints (1975), Trek-themed miniatures games such as Lou Zocchi’s Star Trek Battle Manual (1972) and Stephen V. Cole/ Task Force Games’s Star Fleet Battles (1979) danced on the legal lines of licensed versus unlicensed work. Laying the groundwork for the expansive, interactive, networked assets of the contemporary transmedia franchise, this early form of grassroots affirmational fandom provides an alternative origin story to the strategies of corporate coordination that typify the convergence era, suggesting that – in contrast to the narrative of inevitability that often frames Trek’s fifty-year success story – the truth is lumpier and less industry-friendly: an ongoing process of negotiation and appropriation, leakage and containment that has both fed and complicated the franchise’s development.

Multistage Generation and Network Expansion Planning in Distribution Systems Considering Uncertainty and Reliability

This paper describes the incorporation of uncertainty and reliability in the dynamic expansion planning of distribution network assets and distributed generation. Several alternatives for the installation of feeders, transformers, and distributed generation are considered. Thus, the optimal expansion plan identifies the best alternative, location, and installation time for the candidate assets under the uncertainty related to demand and renewable energy sources. To that end, an iterative algorithm is devised to yield a pool of high-quality candidate solutions in terms of total investment and operational costs. Each candidate solution results from a stochastic-programming-based model driven by the minimization of the expected investment and operational costs. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program for which finite convergence to optimality is guaranteed and efficient off-the-shelf software is available. Standard metrics are subsequently applied to each candidate solution to characterize its reliability so that valuable information is provided to the distribution system planner. Numerical results illustrate the effective performance of the proposed approach.