Electric Power Infrastructure Research Articles

Price trends in the global electricity market

The relevance of the research topic is determined by the need to adapt to rapid global changes in the electric power industry, which is associated with a change in the structure of the energy balance, the strengthening of geopo­litical factors, the impact of climate change, economic globalization, new regulatory require­ments, and the rapid development of energy storage technologies and smart networks. These changes lead, on the one hand, to challenges in ensuring energy security, and on the other hand, contribute to significant price volatility in the electricity market. As a result of the influence of global price trends and world energy develop­ment priorities on the domestic electricity sector, the study of these trends is of great importance for Ukraine. The aim of the research is to establish the price trends of the global electricity market with the determination of the key factors of price growth in the context of challenges for Ukraine regarding the stabilization of electricity prices. The research is based on the hypothesis that the factors that determine the trajectory of price changes on the international electricity market are also characteristic of the Ukrainian electricity market. The research was conducted using the methods of statistical analysis, syn­thesis, grouping, tabular and graphical display of results. A retrospective analysis of price dyna­mics on the global energy market was carried out, which showed a faster pace of price changes for energy products than for other products, with a faster increase in oil prices than for coal. The current trends in the development of changes in electricity prices were analyzed, the reasons for their rapid growth in 2021 were identified, and it was noted that in some countries, such as the USA and China, prices remained stable. Using the example of the EU countries, it has been analytically proven that electricity tariffs depend on the price structure. The factors that affect pricing in the field of electricity in the world are determined: energy prices, global crisis pheno­mena, the amount of available supply, weather conditions, supply chain problems, grid infra­struc­ture and distribution, the structure of the electricity market, the share occupied by taxes and fees in electricity prices and the purchasing power of the population. The current state of the electricity market of Ukraine is analyzed, which is characterized by a price imbalance, especially in the retail sector, a settlement crisis between the main market participants, a lack of real competition, limited transparency of the market and opportunities for manipulation on it, and the imperfection of the legislative framework. These factors are exacerbated by external negative influences in the form of a full-scale Russian invasion due to the destruction of electric power infrastructure and loss of capacity

Design of information management model based on multiobjective optimization algorithm in intelligent electric financial system

The electric power infrastructure is the cornerstone of contemporary society’s sustenance and advancement. Within the intelligent electric power financial system, substantial inefficiency and waste in information management persist, leading to an escalating depletion of resources. Addressing diverse objectives encompassing economic, environmental, and societal concerns within the power system helps the study to undertake a comprehensive, integrated optimal design and operational scheduling based on a multiobjective optimization algorithm. This article centers on optimizing the power financial system by considering fuel cost, active network loss, and voltage quality as primary objectives. A mathematical model encapsulates these objectives, integrating equations and inequality constraints and subsequently introducing enhancements to the differential evolutionary algorithm. Adaptive variation and dynamic crossover factors within crossover, variation, and selection operations are integrated to optimize algorithm parameters, specifically catering to the multiobjective optimization of the electric power system. An adaptive grid method and cyclic crowding degree ensure population diversity and control the Pareto front distribution. They experimentally validated the approach and the comparisons conducted against AG-MOPSO, INSGA-II, and NSDE algorithms across standard test functions: ZDT1, ZDT2, ZDT3, and DTLZ4. The convergence evaluation indices for this study’s scheme on ZDT1 and ZDT2 are 0.000938 and 0.0034, respectively. Additionally, distribution evaluation indices on ZDT1, ZDT2, ZDT3, and ZDT4 stand at 0.0018, 0.0026, 0.0027, and 0.0009, respectively. These indices indicate a robust convergence and distribution, facilitating the optimization of electric power financial information management and the intelligent handling of the electric power financial system’s information, thereby enhancing the allocation of material and financial resources.

Power line Communication: Revolutionizing data transfer over electrical distribution networks

Power Line Communication (PLC) is an emerging technology that utilizes existing electrical power infrastructure for data transmission. It enables communication over power lines, allowing devices to exchange information and access the internet through the power grid. This method offers numerous advantages, including widespread availability, cost-effectiveness, and easy deployment without the need for additional cabling. PLC has found applications in various domains, including smart grid management, home automation, industrial control systems, and Internet of Things (IoT) connectivity. This abstract provides an overview of PLC, highlighting its benefits, challenges, and key technologies. It also discusses the potential of PLC in transforming power distribution networks into intelligent and interconnected systems. Additionally, emerging trends and future directions for PLC research and development are explored, emphasizing the potential for enhanced reliability, speed, and efficiency in data transmission over power lines. This paper proposed a two way communication from source to load sides using BPSK and QPSK modulation techniques. Monte Carlo simulation is used to predict the transformer theoretical channel (AWGN) and compare the efficiency of the proposed methods. Randomly selected data from 10 k to 50 k size are used to compare the performance curve. Moreover, a test sound data is sent from the source side to the load side and it is observed that using the QPSK modulation technique has almost zero Bit Error Rate (BER).

Infrastructure System Obstacles and Technology Adoption by Firms in Transition Countries

Abstract This study uses business survey data to analyze firm perceptions of infrastructure systems in transition countries as obstacles to conducting business. Factors that contribute to reported perceptions are modeled, including country macroeconomic conditions, firm characteristics, and measures of overall reforms and infrastructure system reforms. Identified obstacles arise from binding constraints that limit economic growth, reflect implicit shadow costs, and signal areas in need of policy reform or infrastructure investment. The analysis covers electric power, telecommunications, transportation, and water and wastewater infrastructure systems. Also examined is whether transition indicators of reforms, intended to reflect improvements, are associated with perceptions of obstacles. Beyond identifying infrastructure obstacles and the effects of reforms during the transition process, we also explore firm adoptions of new electronic technologies, essentially a new infrastructure system, as they use email, websites, cell phones, and high-speed Internet in their business activity.

Putin’s power play: Russia’s attacks on Ukraine’s electric power infrastructure violate international law

International humanitarian law is a branch of public international law that seeks to moderate the conduct of wars to protect those who are not taking part in the hostilities. Under international humanitarian law, belligerents may not intentionally target civilians or installations that are indispensable to the survival of the civilian population. While collateral harm to civilians and civilian infrastructure may occur, international humanitarian law prohibits attacks that may be expected to cause incidental loss of civilian life, injury to civilians, damage to civilian objects, or a combination thereof which would be excessive in relation to the concrete and direct military advantage anticipated. In practice, these principles have not always been honored or enforced. State and non-state actors have deliberately targeted civilians and/or disregarded civilian impacts, often for the purpose of pressuring political leaders to capitulate. The increasing occurrence and severity of harm to civilians and civilian infrastructure in modern conflicts calls into question the continuing relevance of what were once viewed as fundamental protections. In this paper, we present a case study involving Russia’s 2022–23 attacks on Ukraine’s electric power infrastructure, which left millions of civilians without heat, water, or other basic services for extended periods in harsh winter conditions. Considering the scope, scale, and long-term impacts of these attacks, we conclude that Russia violated international law. We also suggest that a new international protocol may be necessary in order to more effectively deter and punish attacks on civilian infrastructure in future armed conflicts and military occupations.

Implications of 5G rollout on post-earthquake functionality of regional telecommunication infrastructure

Telecommunication infrastructure (TI) is becoming increasingly vital in modern society, where information exchange is needed in almost all aspects of the built environment, business operations, and people's daily lives. The ongoing 5G rollout will lead to a paradigm shift in regional TI deployment landscape, with increased seismic hazard exposure particularly due to the densely deployed small cells. As TI is known to be vulnerable to seismic hazard impacts yet necessary for post-earthquake emergency response, this study carries out a pioneering effort in quantifying the post-earthquake TI failures and functionality to better support risk mitigation decision-making. We propose a novel seismic risk assessment framework for regional 5G TI, by holistically integrating regional seismic hazard analysis, infrastructure seismic exposure data, electric power infrastructure seismic fragility modeling and network connectivity analysis, as well as wireless TI functionality modeling. The proposed framework is evaluated based on a hypothetical regional infrastructure testbed located in Memphis, Tennessee, subjected to several earthquake scenarios. From a reference heterogeneous 5G TI deployment scenario, the results indicate that significant performance degradation of 5G TI is expected especially after major earthquake events. Enabled by the proposed framework, we further compared the efficacy of several risk mitigation strategies and pertinent implications are provided.

Analysis on the development of modern rural power grids with low carbon serving rural revitalization from the perspective of scientific and technological innovation

Abstract Our country is a large agricultural nation where the development of rural areas holds paramount importance. To achieve rural revitalization, the development of electric power infrastructure is crucial. However, to ensure sustainable growth, attention must be directed towards low-carbon initiatives. With the continuous advancement of science and technology, rural power grids are steadily transitioning towards intelligent development, marking a significant stride in our nation’s power grid evolution. The establishment of smart grids can effectively address energy consumption issues in rural areas, simultaneously aiding in the reduction of energy usage and carbon emissions. Information technology, interactivity and automation are pivotal technical features characterizing the intelligence of rural power grids, leveraging technological advancements to drive the reform of modern rural power systems. This article intends to focus on optimizing low-carbon development within the ambit of intelligent rural power grid construction, alongside a comprehensive analysis of related developments. Such efforts aim to seamlessly integrate rural power development with a low-carbon economy, offering crucial insights and guidance for the sustainable growth of rural power grids. This endeavor contributes to the overarching objectives of rural revitalization and fostering a low-carbon economy.

Methods for researching the influence of electromagnetic waves of power transmission lines on soil properties

This article is devoted to the study of the influence of electromagnetic waves from power lines on soil properties. With the increasing use of electricity and the expansion of electrical power infrastructure, there is increasing interest in understanding the effects of electromagnetic fields on the environment. This article provides an overview of current research methods used to assess the effects of electromagnetic waves on soil properties. Both laboratory and field approaches to studying this issue are considered, and the main results of research in this area are discussed. Understanding these relationships is key to developing effective land use management strategies and maintaining environmental sustainability in the face of modern anthropogenic impacts.

Assessment of changes in the efficiency of the system of maintenance and repair of equipment in the electric power sector of metallurgy

The problems of evaluating various strategies for maintenance and repair (MRO) of elements of fixed assets of the electric power infrastructure of an industrial enterprise in order to choose the optimal option are considered. The author suggests using three key indicators as criteria for evaluating the effectiveness of the considered maintenance strategy: the amount of costs for the implementation of the strategy, the coefficient of technical readiness of the equipment in question and the amount of maximum risk from the implementation of the strategy. Particular attention is paid in the article to the compliance of the chosen MRO strategy with the current equipment load and performance requirements. The paper considers an example of the application of the proposed methodology to real elements of the power supply of an industrial enterprise. The calculation of the listed indicators is made for a critical element of the energy infrastructure of an industrial enterprise of the metallurgical industry, the failure of which will lead to a halt in the production process of finished products.

A multi-model probabilistic framework to evaluate seismic resilience of UHV converter stations

Ultra-high voltage converter stations are significant electric power infrastructures with a high electric energy load. To quantitatively evaluate the seismic and recovery capability of a UHV converter station, this paper proposes a multi-model probabilistic resilience assessment framework divided into four analysis modules for hierarchical evaluation. The conditional probability set of the functional state between network nodes is determined using a matrix-based approach. Taking connectivity and power transmission capacity into account, the functional reliability model was built through the improved Bayesian network. A multi-parameter quantification of the post-earthquake recovery process was carried out by constructing the stepped functional recovery function as well as the time-varying seismic resilience function. The economic loss assessment model was built from multiple aspects. Taking a typical ± 800 kV UHV converter station as a case study for seismic resilience analysis, the probabilistic resilience assessment was realized, and variation trends of the multi-parameter expected value were obtained by mathematical expectation. This article shows that taking measures to postpone the sensitive interval of the system helps to avoid the seismic active area. This avoidance of seismic activity is the objective of optimization. The proposed framework can serve as a reference for the operation and optimization of power systems.

Economically optimal hydropower development with uncertain climate change

Climate change affects the planning, construction, operation and management of hydropower plants in various ways. Evaluating hydropower generation with nonstationary climate changes is important for planning electric power infrastructure development. For a new hydropower plant with climate change, specifying too large a reservoir may result in excessive investment if the future becomes drier, while too small a reservoir may cause insufficient utilization of hydropower resources. Whether to build a new hydropower station at once or build it dynamically in stages over time is challenged by uncertainty in future conditions. This study proposes a planning method for developing a flexible hydropower construction schedule to adapt to long-term uncertain hydrology with climate changes. Projected uncertain nonstationary hydrology scenarios were developed first, and Bayes’ theorem is used to update the probability of each scenario based on observed hydrologic conditions over time. A profit maximization model integrates stochastic dynamic programming and linear programming for a cascade hydropower system to evaluate hydropower plant expansion and how to build it dynamically with uncertain nonstationary climate conditions. In this, stochastic dynamic programming evaluates and prescribes inter-stage reservoir upgrades and linear programming prescribes inner-stage hydroelectric power generation. The case study of Jinsha cascade hydropower system in China’s Yunnan province illustrates the method. The intensity and trend of climate change effects on streamflow directly affect the optimized results. If streamflow decreases in the future, the best strategy is to build a small reservoir initially, without future changes. If streamflow increases in the future, it is better to build a small reservoir first, and gradually increase capacity according to observed changes in streamflow and economies of scale in capacity construction. If there is no clear trend in streamflow change, it is also better to build a small reservoir at first, then decide whether to expand the reservoir according to future observed changes in streamflow. This method with uncertain nonstationary climate change and upgrading adaptively with observed hydrology usually produced better results than optimization for a deterministic nonstationary hydrology.

Structural Vulnerability Analysis of Interdependent Electric Power and Natural Gas Systems

The growing use of gas-fired power generators and electricity-driven gas compressors and storage has increased the interdependence between electric power infrastructure and natural gas infrastructure. However, the increasing interdependence may spread the failures from one system to the other, causing subsequent failures in an integrated power and gas system (IPGS). This paper investigates the structural vulnerability of a realistic IPGS based on complex network theory. Different from the existing works with a focus on the static vulnerability analysis for an IPGS, this paper considers both static and dynamic vulnerability analysis. The former focuses on vulnerability analysis under random and selective failures without flow redistribution, while the latter concentrates on vulnerability analysis under cascading failures caused by flow redistribution. Also, different from the existing works with a focus on the IPGS as a whole, we not only analyze the vulnerability of the IPGS but also analyze the vulnerability of the power subsystem (PS) and gas subsystem (GS), in order to understand how the vulnerability of the IPGS is affected by its PS and GS. The analysis results show that (1) if the PS and GS are more susceptible to cascading failures than selective and random failures, the IPGS as a whole is also more vulnerable to cascading failures. (2) There are different dominant factors affecting the IPGS vulnerability under cascading failures and selective failures. Under cascading failures, the GS has a more significant impact on the IPGS vulnerability; under selective failures, the PS has a more important impact on the IPGS vulnerability. (3) The IPGS is more vulnerable to failures on the critical nodes, which are identified from the IPGS as a whole rather than from the individual PS or GS. The results provide insights into the design and planning of IPGSs to improve their overall reliability.

A novel digital twin framework of electric power infrastructure systems subjected to hurricanes

The electric power network (EPN) is one of the most critical infrastructure systems as most lifeline, economic, and social systems depend heavily on it, and any disruption in the network may affect the well-being of modern societies. Being the most vulnerable to natural hazards, the resilience of the EPN has received plenty of attention in recent years, particularly considering the increasing frequency and severity of natural hazards associated with climate instabilities. The data revolution and the recent advances in the fields of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) have prompted researchers to take the next step and expand the available predictive models toward digital twins (DT). However, there is still a lack of an applicable framework for a DT of infrastructure systems in the face of disasters. In this paper, a novel DT framework of the EPN when subjected to hurricanes is proposed that combines physics-based and data-driven models while also employing a dynamic Bayesian network (DBN). The DBN can be updated in near real-time via data sensing to provide a DT that is simple, computationally feasible, scalable, and capable of modeling and estimating the failure and performance states of the various elements of the EPN. The proposed DT framework is applied to Galveston Island's EPN, and the results are validated using historical data, demonstrating that the DT can produce detailed and highly accurate estimations to be used in decision-making for community resilience planning.

Fully Parallel Optimization of Coordinated Electricity and Natural Gas Systems on High-Performance Computing

Intensified interactions between electric power and natural gas infrastructures raise significant demands to coordinate their system operations. This paper proposes a fully parallel optimization method that can achieve a rapid decision-making on the day-ahead coordinated operation of electricity and natural gas systems on the high-performance computing (HPC) platform. The proposed method can flexibly tailor decomposition strategies to solve the optimization problem according to unique features of problem models in both electric power and natural gas systems. Particularly, the operation problem of power system is split by function and time into numbers of singe-unit subproblems and single-period network subproblems, while the operation problem of natural gas system is decomposed into multiple area subproblems. All the scalable subproblems are solved and coordinated quickly in a fully parallel manner on HPC for improving computational efficiency and tractability of complex electricity-gas co-optimization problem. By optimally coordinate electricity and natural gas systems under different operating conditions, the proposed method could improve the energy economics as well as the system resilience to various outages due to extreme events. Numerical results demonstrate the effectiveness and efficiency of our proposed co-optimization method and its HPC implementation.

Exploring the Real-Time WRF Forecast Skill for Four Tropical Storms, Isaias, Henri, Elsa and Irene, as They Impacted the Northeast United States

Tropical storm Isaias (2020) moved quickly northeast after its landfall in North Carolina and caused extensive damage to the east coast of the United States, with electric power distribution disruptions, infrastructure losses and significant economic and societal impacts. Improving the real-time prediction of tropical storms like Isaias can enable accurate disaster preparedness and strategy. We have explored the configuration, initialization and physics options of the Weather Research and Forecasting (WRF) model to improve the deterministic forecast for Isaias. The model performance has been evaluated based on the forecast of the storm track, intensity, wind and precipitation, with the support from in situ measurements and stage IV remote sensing products. Our results indicate that the Global Forecasting System (GFS) provides overall better initial and boundary conditions compared to the North American Model (NAM) for wind, mean sea level pressure and precipitation. The combination of tropical suite physics options and GFS initialization provided the best forecast improvement, with error reduction of 36% and an increase of the correlation by 11%. The choices for model spin-up time and forecast cycle did not affect the forecast of the storm significantly. In order to check the consistency of the result found from the investigation related to TS Isaias, Irene (2011), Henri (2021) and Elsa (2021), three other tropical storms, were also investigated. Similar to Isaias, these storms are simulated with NAM and GFS initialization and different physics options. The overall results for Henri and Elsa indicate that the models with GFS initialization and tropical suite physics reduced error by 44% and 57%, respectively, which resonates with the findings from the TS Isaias investigation. For Irene, the initialization used an older GFS version and showed increases in error, but applying the tropical physics option decreased the error by 20%. Our recommendation is to consider GFS for the initialization of the WRF model and the tropical physics suite in a future tropical storm forecast for the NE US.

Uncertainty-Informed Operation Coordination in a Water-Energy Nexus

The widespread deployment of smart heterogeneous technologies and the growing complexity in our modern society calls for effective coordination of the interdependent lifeline networks. In particular, operation coordination of electric power and water infrastructures is urgently needed as the water system is one of the most energy-intensive networks, an interruption in which may quickly evolve into a dramatic societal concern. The closely-intertwined ecosystem of water and power infrastructures is commonly known as water-energy nexus. This paper develops a novel analytic for uncertainty-aware day-ahead operation optimization of the interconnected power and water systems (PaWS). Joint probabilistic constraint (JPC) programming is employed to capture the uncertainties in wind resources and water demand forecasts. The proposed integrated stochastic model is presented as a non-linear non-convex optimization problem, where the non-linear hydraulic constraints in the water network are linearized using piece-wise linearization technique, and the non-convexity is efficiently tackled with a Boolean solution methodology to convert the proposed model with JPCs to a tractable mixed-integer linear programming (MILP) formulation that can be quickly solved to optimality. The suggested framework is applied to a 15-node commercial-scale water network jointly operated with a power transmission system using a modified IEEE 57-bus test system. The numerical results demonstrate the of the proposed stochastic framework, resulting in cost reduction (13% on average when compared to the traditional setting) and energy saving of the integrated model under different realizations of uncertain renewable energy sources (RESs) and water demand scenarios. Additionally, the scalability of the proposed model is tested on a modified IEEE 118-bus test system connected to five water networks.

Reducing the Vulnerability of Electric Power Infrastructure against Natural Disasters by Promoting Distributed Generation

Reducing the Vulnerability of Electric Power Infrastructure against Natural Disasters by Promoting Distributed Generation

Selecting the PID Controller Settings for an Automatic Generation Control Device in a Power System

The integration of renewable generation facilities into integrated power systems entails new challenges for maintaining a reliable and safe electric power infrastructure. It is necessary to expand the use of automatic generation control devices to ensure the ability to control the modes of power systems with a significant share of renewable energy sources. The generation control devices can be used not only for frequency control, but also for maintaining the inter-area wheeling in interconnected power systems. The article suggests application of the particle swarm method, which is one of evolutionary optimization methods, to find optimal parameter settings for proportional-integral-differentiating (PID) controllers of the automatic generation control device. The mathematical description of electric power system elements is given, and a structure of automatic generation control is given. The tuning parameters of the PID controllers of the automatic generation control device based on the particle swarm method, as well as some of classical optimization methods, have been determined. The results of tuning PID controllers obtained by different methods in the form of frequency variation characteristics in power system parts, as well as the torques of an equivalent steam turbine in response to power fluctuations in one of the power system parts are compared.

Analysis of the Impact Path of China-Pakistan Power Industry Cooperation on Poverty Reduction in Pakistan

Pakistan has been suffering from a power shortage, and the power supply is far from meeting the electricity demand of production and life in the country. The poverty of electric energy is both the cause and the result of Pakistan's poverty. So to make the people of Pakistan get rid of poverty as soon as possible, it is necessary to improve the electric power infrastructure. Since the construction of China-Pakistan Economic Corridor, the degree of China-Pakistan power cooperation has been deepened, and the development of Pakistan's power industry has ushered in a new period of opportunity. In this paper, we will analyze the basis of China-Pakistan power industry cooperation and study why cooperation between China and Pakistan can be realized. It also combines several cases to illustrate the positive impact of China-Pakistan power industry cooperation on poverty reduction in Pakistan. Of course, under domestic and international pressure, China-Pakistan power industry cooperation is facing many new difficulties and challenges. China and Pakistan must face these problems and strengthen dialogue and consultation to utilize better the role of power industry cooperation for Pakistan's economic development and social progress.

A review on condition assessment technologies for power distribution network infrastructure

Reliable performance of the electricity distribution networks is critical to avoid outages and disruptions which may lead to substantial economic losses. Some of the important components of the electricity distribution networks include overhead cables, utility poles, cross-arms, substations, and transformers. These components are subjected to deterioration with aging and pose risks of failure creating safety concerns, specially under extreme weather conditions. Efficient maintenance and the use of accurate condition assessment techniques to monitor the integrity of the aforementioned components are key factors to be considered in managing the electricity distribution assets. This article presents a review of different condition assessment techniques employed for monitoring the electricity distribution infrastructure. The conventional inspection techniques and advancements in non-destructive testing methods are discussed outlining the relative advantages and disadvantages. Other than the normal failures of distribution infrastructure due to component ageing, unexpected and less frequent extreme weather events can have significant impacts on the resilience of the electrical power infrastructure. Thus, the effects of extreme weather conditions on the reliability of the electricity distribution networks and the failure rates of assets are reviewed in this study. Further, the maintenance and decision-making approaches implemented in the power distribution networks are also discussed.