Energy Infrastructure Systems Research Articles

An Efficient Multifeature Model for Improving the Performance of Critical Energy Infrastructure

Energy infrastructure is well thought-out to be one of the complex infrastructures due to its convoluted configuration and automatic control among all of the systems. With such systems, various connections are made for the purpose of configurations. The energy system infrastructure aims to analytically evaluate each element of the system based on fundamental energy branches according to the customer demand. Developing a novel critical evaluation approach for complex energy infrastructure is pertinent to the evaluation of mixed energy system infrastructure. Considering the functional relationships between elements and their infrastructures, a system is needed to overcome the limitations of the current systems. By doing the efficient modeling of enhancing the performance infrastructure of critical energy infrastructure enable better quantitative evaluation of system. The purpose of the proposed study is to develop an evaluation approach for enhancing the performance of critical energy infrastructure. With the help of the proposed approach, efficient multifeature model for enhancing the performance of critical energy infrastructure was experimentally calculated. The experimental setup of the proposed study was done in the Super Decision tool for an efficient multifeature model for enhancing the performance. Results of the experiments reveal the effectiveness of the proposed research.

Exploring the future energy-mobility nexus: The transportation energy & mobility pathway options (TEMPO) model

• Document the approaches and methods used in the TEMPO model. • All-inclusive passenger and freight transport demand model that covers the entire U.S. • Generate scenarios of technology adoption and future energy use and emissions. • Innovative household-level representation of passenger mobility and choices. • Comparison with the EIA AEO for a business-as-usual scenario. This paper documents the approaches and methods used in the Transportation Energy & Mobility Pathway Options™ (TEMPO) model to evaluate passenger and freight demand for transportation and mobility services, project vehicle ownership and technology adoption decisions, and determine transport mode choices to derive scenarios of future energy use and emissions. TEMPO is an all-inclusive transportation demand model that covers the entire United States, with an implicit spatial resolution and an hourly temporal resolution that allows for generating time-resolved energy use profiles to assess multisectoral integration aspects. Key features of the TEMPO model include the ability to perform endogenous out-of-sample forecasting to extrapolate recent emerging trends and analyze impacts of disruptive technological breakthroughs and behavioral changes. TEMPO employs an innovative representation of passenger mobility demand stemming from household-level decisions that determine vehicle adoption, ownership, and use based on sociodemographics (e.g., income, household composition), technology attributes (e.g., travel cost, time), geography (e.g., urban, suburban, rural) and population-specific multiday mobility and travel requirements. This representation enables a more forward-looking perspective on the use of new mobility options and the adoption of alternative fuel vehicles, as well as a more accurate representation of their energy usage profiles than previous modeling approaches. A comparison with the U.S. Energy Information Administration’s Annual Energy Outlook showcases the ability of TEMPO to accurately replicate widely accepted projections by representing the key elements of the entire transportation sector at the appropriate level of resolution. TEMPO is intended to generate future scenarios of technology adoption, energy use, and emissions in the transportation sector to compare alternatives, inform decision makers, and assess integration with energy infrastructure and supply systems at an appropriate spatiotemporal resolution.

Modelling of decarbonisation transition in national integrated energy system with hourly operational resolution

In this paper, we present an optimisation integrated energy system model (IESA-Opt) for the Netherlands with the use of a linear programming formulation. This state-of-the-art model represents a scientific contribution as it integrates a European power-system model with a complete sectoral representation of the energy system technologies and infrastructure that account for all greenhouse gas emissions considered in the targets, and takes into consideration a detailed description of the cross-sectoral flexibility (e.g. flexible heat and power cogeneration, demand shedding from power-to-X and electrified industrial processes, short- and long-term storage of diverse energy carriers, smart charging and vehicle-to-grid for electric vehicles, and passive storage of ambience heat for the built environment). This model provides a detailed description of the operation of technologies and considers exogenous technological learning to simultaneously solve multi-year planning of investments, retrofitting, and economical decommissioning with intra-year operational, flexible, and despatch decisions. The model is applied to a case study of the Netherlands energy transition under the current climate policy and conservative projections for the economy and availability of resources. The results present a significant reliance on renewable energy sources, such as wind (800 PJ) and solar (300 PJ), to fuel the electrification revolution as well as biomass (550 PJ) for feedstock and heat purposes coupled with carbon capture, utilisation, and storage (CCUS) to achieve negative emissions in certain sectors. However, oil (880 PJ) and gas (1050 PJ) constitute almost half of the final energy demand as they are required for heat applications, industrial feedstock, refined oil products for export, and international transport fuel. Four different sensitivity analyses are presented for the emission reduction target, oil demand streams, biomass availability, and demand volumes. The most significant findings are as follows: 1) it is crucial to have simultaneous highly available biomass and CCUS storage capacities to achieve negative emissions and facilitate the transition; 2) even in a highly decarbonised scenario, it is necessary to simultaneously develop climate policies focused on international transport emissions, oil-based feedstock, and refined-oil product exports to completely displace oil from the energy mix; 3) (imported) biomass has the ability to decrease system costs (3% under conservative scenarios of availability and price); however, for biomass prices higher than 20 €/GJ, this effect is lower; 4) in relative terms, the system is most sensitive to demand uncertainties from the transport sector than any other sector, followed closely by the industrial sector.

A novel multi-stage distributed authentication scheme for smart meter communication.

Smart meters have ensured effective end-user energy consumption data management and helping the power companies towards network operation efficiency. However, recent studies highlighted that cyber adversaries may launch attacks on smart meters that can cause data availability, integrity, and confidentiality issues both at the consumer side or at a network operator’s end. Therefore, research on smart meter data security has been attributed as one of the top priorities to ensure the safety and reliability of the critical energy system infrastructure. Authentication is one of the basic building blocks of any secure system. Numerous authentication schemes have been proposed for the smart grid, but most of these methods are applicable for two party communication. In this article, we propose a distributed, dynamic multistage authenticated key agreement scheme for smart meter communication. The proposed scheme provides secure authentication between smart meter, NAN gateway, and SCADA energy center in a distributed manner. Through rigorous cryptanalysis we have proved that the proposed scheme resist replay attack, insider attack, impersonation attack and man-in-the-middle attack. Also, it provides perfect forward secrecy, device anonymity and data confidentiality. The proposed scheme security is formally proved in the CK—model and, using BAN logic, it is proved that the scheme creates a secure session between the communication participants. The proposed scheme is simulated using the AVISPA tool and verified the safety against all active attacks. Further, efficiency analysis of the scheme has been made by considering its computation, communication, and functional costs. The computed results are compared with other related schemes. From these analysis results, it is proved that the proposed scheme is robust and secure when compared to other schemes.

Household multidimensional energy poverty and its impacts on physical and mental health

This paper aims to measure multidimensional energy poverty at the household level and study its impacts on health status. Based on Chinese General Social Survey (CGSS) data, we evaluated multidimensional energy poverty at the household level using the entropy method. We then examined the effects of energy poverty on health status from both physical and psychological perspectives. The empirical results indicate that multidimensional energy poverty harms both physical and mental health. We further conducted regional and urban–rural comparative analyses. The findings demonstrate that the health of residents in less developed provinces is more severely affected, and multidimensional energy poverty deteriorates the physical health of rural residents but impacts the mental health of urban residents. For developing countries like China, the first priority should be multidimensional energy poverty reduction through modern energy infrastructure system construction and subsidies for energy poor households, and improving the medical security system should be considered as next step. There is also an urgent need of policy measures focusing on mitigating regional and urban–rural disparities at the same time.

Optimizing the resilience of interdependent infrastructures to regional natural hazards with combined improvement measures

Critical infrastructure systems are important for continuous functioning of the modern society. This paper proposes a model for developing infrastructure resilience improvement strategy to natural hazards on a regional scale, with combined pre- and post-disaster resilience improvement measures (RIMs). The main objective of the model is to maximize the expected value of the resilience of interdependent infrastructure systems. The interdependencies between infrastructure systems, the requirements on the proactive and reactive capacities of the interdependent systems, and the limit of specialized resources are incorporated in the model. A numerical solution method applying heuristics and Monte Carlo simulations is presented. The proposed model is validated using a case study on the Greater Toronto Area energy infrastructure systems. The results show that: (i) comparing with individual RIM, the combined RIMs can increase the resilience value of interdependent infrastructure systems while keeping the system properties within acceptable levels; (ii) the optimal combination of RIMs changes with the requirements on the proactive and reactive capacities; and (iii) the intensity of natural hazards and the response time of restoration activities have significant impacts on the optimal combination of RIMs. The proposed model can assist the decision makers to select effective combined RIMs under different regional natural hazard scenarios.

Impact Analysis of Seismic Events on Integrated Electricity and Natural Gas Systems

Seismic events can cause devastating impacts on both overground and underground energy system infrastructure. This paper proposes a methodology to evaluate the impact of seismic events on the security of integrated electricity and gas system, mainly focusing on pipelines leakage and connection loss of electricity transmission lines. A stochastic model is used to formulate the damage level based on earthquake severity. The seismic impact on the integrated system is classified according to the levels of pipe leak and electricity line failure. Load curtailment due to limited generation capacity and overloaded transmission lines is thereafter quantified. Seismic intensity is generated randomly based on Monte Carlo simulation so that a certain seismic intensity can be related to relevant load curtailment. An integrated energy system with a 30-busbar electricity system and a 6-node natural gas network is used to demonstrate the effectiveness of the proposed method. The results clearly illustrate damage consequences under seismic events in terms of both probability and severity levels. This work can inform resilience enhancement scheme design based on the vulnerability performance and impact of both systems.

A Hierarchical Approach to Multienergy Demand Response: From Electricity to Multienergy Applications

Due to proliferation of energy efficiency measures and availability of the renewable energy resources, traditional energy infrastructure systems (electricity, heat, gas) can no longer be operated in a centralized manner under the assumption that consumer behavior is inflexible, i.e., cannot be adjusted in return for an adequate incentive. To allow for a less centralized operating paradigm, consumer-end perspective and abilities should be integrated in current dispatch practices and accounted for in switching between different energy sources not only at the system but also at the individual consumer level. Since consumers are confined within different built environments, this article looks into an opportunity to control energy consumption of an aggregation of many residential, commercial, and industrial consumers, into an ensemble. This ensemble control becomes a modern demand response (DR) contributor to the set of modeling tools for multienergy infrastructure systems.

Thermal Energy Storage for the Complex Energy Systems

Thermal energy systems (TES) systems contribute to the on-going process leading to greater integration between different energy systems in order to achieve cleaner and more sustainable use of energy resources. This paper reviews the current literature showing the development and deployment of TES-based solutions in power grid-connected systems. These solutions integrate the energy system to gain new potential for energy management, make better use of renewable energy (RES) resources, modernize energy system infrastructure, facilitate network operation practices that include energy conversion and service delivery. The network is cost-effective, facilitating. This paper provides a complementary look at other investigations into energy storage technologies and materials for TES and TES building applications and electrical energy storage aids for network applications. The main aspects discussed are the features, parameters, and models of TES systems, the deployment of TES in variable RES systems, small networks, multi-power networks, and emerging trends for TES applications.

Thermal Energy Storage for Grid Applications: Current Status and Emerging Trends

Thermal energy systems (TES) contribute to the on-going process that leads to higher integration among different energy systems, with the aim of reaching a cleaner, more flexible and sustainable use of the energy resources. This paper reviews the current literature that refers to the development and exploitation of TES-based solutions in systems connected to the electrical grid. These solutions facilitate the energy system integration to get additional flexibility for energy management, enable better use of variable renewable energy sources (RES), and contribute to the modernisation of the energy system infrastructures, the enhancement of the grid operation practices that include energy shifting, and the provision of cost-effective grid services. This paper offers a complementary view with respect to other reviews that deal with energy storage technologies, materials for TES applications, TES for buildings, and contributions of electrical energy storage for grid applications. The main aspects addressed are the characteristics, parameters and models of the TES systems, the deployment of TES in systems with variable RES, microgrids, and multi-energy networks, and the emerging trends for TES applications.

A new distributed co-simulation architecture for multi-physics based energy systems integration

Abstract Simulating energy systems integration scenarios enables a comprehensive consideration of interdependencies between multimodal energy grids. It is an important part of the planning for the redesign of the current energy system infrastructure, which is essential for the foreseen drastic reduction of carbon emissions. In contrast to the complex implementation of monolithic simulation architectures, emerging distributed co-simulation technologies enable the combination of several existing single-domain simulations into one large energy systems integration simulation. Accompanying disadvantages of coupling simulators have to be minimized by an appropriate co-simulation architecture. Hence, in the present paper, a new simulation architecture for energy systems integration co-simulation is introduced, which enables an easy and fast handling of the therefore required simulation setup. The performance of the new distributed co-simulation architecture for energy systems integration is shown by a campus grid scenario with a focus on the effects of power to gas and the reversal process onto the electricity grid. The implemented control strategy enables a successful co-simulation of electrolysis coupled with photovoltaics, a hydrogen storage with a combined heat and power plant and a variable power consumption.

CyPhyR: a cyber‐physical analysis tool for measuring and enabling resiliency in microgrids

This study presents a tool to study the cyber-physical resiliency (CyPhyR) of critical energy infrastructure system, in particular the effect of cyber attacks on the microgrid's resiliency. The developed tool enables measuring resiliency using data from cyber and physical systems and suggests control decisions for resilient planning and operation of the microgrid. The microgrid resiliency is formulated based on graph theory based indices and cyber-power system characteristics. A Common Vulnerability Scoring System based metric called the Cyber Asset Impact Potential is developed and used in the planning phase, and another metric, Cyber Impact Severity is introduced to study the system performance in the operational phase. The information from these two phases is provided to the operator to make informed and proactive decisions to ensure the resilient operation of the microgrid. The performance of the developed tool has been tested using comprehensive real-time cyber-power testbed for a Consortium for Electric Reliability Technology Solutions microgrid test system.

Network selection criterion for ubiquitous communication provisioning in smart cities for smart energy system

With the expansion of urbanization, energy becomes one of the foremost requirements of a smart city. Low energy consumption, renewable energy, and carbon footprints reduction are prime targets of a smart city. A smart city needs to be energy efficient and technology driven. Information and Communication Technology (ICT) helps to improve system efficiency and creates a way for the end consumer to communicate with utilities and the network service provider. The two-way communication model of a smart grid makes possible reliable, stable and efficient communication between utility and consumer by using ICT. The major issue in smart energy system is the lack of necessary interoperability and integration of communication standards, which hampers the effective deployment of communication networks. In this paper, we present a hierarchical architecture to resolve this issue, which will support smart energy system infrastructure and services in smart cities for provisioning of ubiquitous communication. It consists of two computing zones (fog computing and cloud computing) along with two implementation phases (initial and final). Fog computing will help to offer low latency response to anomalous and hazardous events in real time while reducing a burden on the cloud for computing as well as storage. To provide ubiquitous communication in smart energy system for data acquisition, a network selection algorithm has been proposed. TOPSIS MADM technique is employed for network selection in a heterogeneous environment at HAN/NAN (Bluetooth, Zigbee, Z-Wave, WLAN, LoRaWAN) and WAN (GPRS, UMTS, LTE, and WiMAX) levels of smart energy system's multilayer communication infrastructure. Coverage area, data rate, power consumption and security level attributes are employed for network selection. The results revealed that WLAN performed better in case of HAN/NAN environment, whereas LTE worked best at WAN level.

Rethinking Risk Assessment for Public Utility Safety Regulation.

To aid in their safety oversight of large-scale, potentially dangerous energy and water infrastructure and transportation systems, public utility regulatory agencies increasingly seek to use formal risk assessment models. Yet some of the approaches to risk assessment used by utilities and their regulators may be less useful for this purpose than is supposed. These approaches often do not reflect the current state of the art in risk assessment strategy and methodology. This essay explores why utilities and regulatory agencies might embrace risk assessment techniques that do not sufficiently assess organizational and managerial factors as drivers of risk, nor that adequately represent important uncertainties surrounding risk calculations. Further, it describes why, in the special legal, political, and administrative world of the typical public utility regulator, strategies to identify and mitigate formally specified risks might actually diverge from the regulatory promotion of "safety." Some improvements are suggested that can be made in risk assessment approaches to support more fully the safety oversight objectives of public regulatory agencies, with examples from "high-reliability organizations" (HROs) that have successfully merged the management of safety with the management of risk. Finally, given the limitations of their current risk assessments and the lessons from HROs, four specific assurances are suggested that regulatory agencies should seek for themselves and the public as objectives in their safety oversight of public utilities.

Climate proofing island energy infrastructure systems: Framing resilience based policy interventions

One of the most discernible impacts of climate change is the increasing severity and unpredictability of extreme weather conditions. Small island developing states are particularly vulnerable to these conditions, with one of the impacts being on energy supplies due to damaging energy infrastructure, resulting in power outages and economic losses. Drawing on resilience theory to frame the discourse, we present an updated overview of how island energy infrastructures have been and continue to be negatively impacted. This same framework also provides a lens through which we identify the challenges involved in recovery, rebuilding and returning energy security in these contexts.

Sustainable and Resilient Design of Interdependent Water and Energy Systems: A Conceptual Modeling Framework for Tackling Complexities at the Infrastructure-Human-Resource Nexus

A modeling framework was conceptualized for capturing the complexities in resilience and sustainability associated with integration of centralized and decentralized water and energy systems under future demographic, climate, and technology scenarios. This framework integrates survey instruments for characterizing individual preferences (utility functions) related to decentralization of water and energy infrastructure systems. It also includes a spatial agent-based model to develop spatially explicit adoption trajectories and patterns in accordance with utility functions and characteristics of the major metropolitan case study locations as well as a system dynamics model that considers interactions among infrastructure systems, characterizes measures of resilience and sustainability, and feeds these back to the agent-based model. A cross-scale spatial optimization model for understanding and characterizing the possible best case outcomes and for informing the design of policies and incentive/disincentive programs is also included. This framework is able to provide a robust capacity for considering the ways in which future development of energy and water resources can be assessed.

A Methodology Concept for Territorial Metabolism – Life Cycle Assessment: Challenges and Opportunities in Scaling from Urban to Territorial Assessment

To allow for the assessment of regional-scale geographically non-contiguous production system derived environmental impacts, a combined method of Territorial Metabolism – Life Cycle Assessment (TM-LCA) is proposed. By creating a two-pronged framework for the development of background system modelling, the TM-LCA method allows for process-based environmental impact modeling at a regional scale utilizing the concept of a production territory for the assessment of changes to durable production systems, such as energy infrastructure and agricultural systems. The TM-LCA framework creates the opportunity for direct assessment of environmental impacts, incorporation of system dynamics, and the use of multi-criteria decision analysis, which might be difficult or impossible to implement in other regional scale environmental impact assessment frameworks.

Building Foresight in Long-Term Infrastructure Planning Using End-Effect Mitigation Models

This paper applies the end-effect mitigation models to build foresight into long-term infrastructure planning problems. This paper describes the phenomenon of end effects; presents four different models that address it, namely extended simulation, salvage value, and primal and dual equilibria; and applies them to long-term energy system planning problems with finite resources for investments. The planning model is a simultaneous multiperiod linear optimization model that plans for energy system infrastructures at the national scale. Two instances of this model are considered: 1) a small-scale five-node model; and 2) a medium-to-large-scale 13-node model. These instances are used to assess and quantify: 1) the end effects of using investment solutions; and 1) the efficacy of each mitigation methods in terms of accuracy and computational time. The illustrations demonstrate that, without attributing the long-term infrastructure planning with some level of foresight about the future cost and performance of the technologies, the resulting portfolio will have end effects in terms of: 1) investment bias toward low-cost resources at the end years; and 2) adopting low-cost quick fixes (such as excess cofiring) to meet near-term emission targets, both of which may render the model to lose sight of long-term targets and economics.

Transition of Future Energy System Infrastructure; through Power-to-Gas Pathways

Power-to-gas is a promising option for storing interment renewables, nuclear baseload power, and distributed energy and it is a novel concept for the transition to increased renewable content of current fuels with an ultimate goal of transition to a sustainable low-carbon future energy system that interconnects power, transportation sectors and thermal energy demand all together. The aim of this paper is to introduce different Power-to-gas “pathways”, including Power to Hydrogen, Power to Natural Gas End-users, Power to Renewable Content in Petroleum Fuel, Power to Power, Seasonal Energy Storage to Electricity, Power to Zero Emission Transportation, Power to Seasonal Storage for Transportation, Power to Micro grid, Power to Renewable Natural Gas (RNG) to Pipeline (“Methanation”), and Power to Renewable Natural Gas (RNG) to Seasonal Storage. In order to compare the different pathways, the review of key technologies of Power-to-gas systems are studied and the qualitative efficiency and benefits of each pathway is investigated from the technical points of view. Moreover, different Power-to-gas pathways are discussed as an energy policy option that can be implemented to transition towards a lower carbon economy for Ontario’s energy systems.

The short-term operation of microgrids in a transactive energy architecture

The transactive energy framework provides value-driven control schemes that facilitate power delivery with higher efficiency, sustainability and economic soundness while ensuring the reliability and security of the energy infrastructure system. This article addresses the challenges and solution frameworks for the short-term operation of distributed energy resources, controllable demands, and microgrids in a transactive energy architecture, with a focus on the distributed energy management of hybrid AC/DC microgrids.