Network Operation Research Articles

Multi‐objective interval planning for 5G base station virtual power plants considering the consumption of photovoltaic and communication flexibility

AbstractLarge‐scale deployment of 5G base stations has brought severe challenges to the economic operation of the distribution network, furthermore, as a new type of adjustable load, its operational flexibility has provided a potential way to promote the consumption and utilization of photovoltaic. In this paper, a multi‐objective interval collaborative planning method for virtual power plants and distribution networks is proposed. First, on the basis of in‐depth analysis of the operating characteristics and communication load transmission characteristics of the base station, a 5G base station of virtual power plants participating in the cellular respiratory demand response model is constructed. In view of the inherent contradiction between system economy and environmental performance, a multi‐objective interval optimization model for collaborative planning of virtual power plants and distribution networks is established with the lowest system investment and operating costs and the lowest carbon emissions as the optimization goals. The established model is transformed into a deterministic optimization problem, which is solved by NSGA‐II algorithm. The modified IEEE‐33 node system is used in the case analysis to analyse the impact of different planning schemes and response characteristics on the system economy. The calculation results verify the effectiveness of the proposed method.

Modelling and optimization of an existing onshore gas gathering network using PIPESIM

Pakistan has limited natural gas reserves, and most are found onshore. This article reports on the problems of an onshore gas gathering network (GGN) analysed through steady-state simulation modelling using PIPESIM software. The research methodology incorporates a comprehensive steady-state hydraulic analysis considering fluid flowing velocity limitations, liquid holdup and slugging along with other issues faced by gas gathering networks. The steady-state hydraulic analysis has led us to pinpoint specific GGN pipelines facing critically low gas velocities and consequent liquid holdup. Addressing these issues involved application of PIPESIM software for modelling, considering various operating schemes of gas-producing wells and their associated pipelines. To select an optimal operating scheme, the study utilized the Analytic Hierarchy Process (AHP) for operational optimization, to identify the most effective solution for reduced liquid holdup, improving production, and ensuring the safe operation among available alternatives. Findings from our hydraulic analysis highlight the importance of reducing GGN outlet pressure to mitigate challenges associated with liquid holdup which causes slugging and back pressure effect at source leading to low production and poor performance of the GGN. Study of three alternative cases reveals that decreasing outlet pressure lowers the liquid holdup, improve gas flowing velocities, and enhanced overall production. These findings validate our hypothesis that reducing GGN outlet pressure is a viable strategy to lower the liquid holdup in pipelines. This research offers significant value by providing a comprehensive solution to GGN liquid holdup, low flowing velocities, back pressure and low production challenges. The integration of steady-state hydraulic analysis, simulation modelling with PIPESIM, and the application of AHP for optimization contributes novel insights into the optimization of operation of gas gathering networks. Emphasizing the reduction of liquid holdup and enhancing production through outlet pressure adjustments offers a practical framework for optimizing the functionality of gas gathering networks.

Two-Stage Optimal Scheduling for Urban Snow-Shaped Distribution Network Based on Coordination of Source-Network-Load-Storage

With the widespread integration of distributed resources, optimizing the operation of urban distribution networks faces challenges including uneven source-load-storage distribution, fluctuating feeder power flows, load imbalances, and network congestion. The urban snow-shaped distribution network (SDN), characterized by numerous intra-station and inter-station tie switches, serves as a robust framework to intelligently address these issues. This study focuses on enhancing the safe and efficient operation of SDNs through a two-phase optimal scheduling model that coordinates source-network-load-storage. In the day-ahead scheduling phase, an optimization model is formulated to minimize operational costs and mitigate load imbalances. This model integrates network reconfiguration, energy storage systems (ESSs), and flexible load (FL). During intra-day scheduling, a rolling optimization model based on model predictive control adjusts operations using the day-ahead plan to minimize the costs and penalties associated with power adjustments. It provides precise control over ESS and FL outputs, promptly correcting deviations caused by prediction errors. Finally, the proposed model is verified by an actual example of a snow-shaped distribution network in Tianjin. The results indicate significant improvements in leveraging coordinated interactions among source-network-load-storage, effectively reducing spatial-temporal load imbalances within feeder clusters and minimizing the impact of prediction inaccuracies.

Методология анализа функционирования и прогнозирования развития региональной транспортной сети (на примере Европейской и Приуральской Арктики)

The article is devoted to the development of theoretical and methodological approaches to the fundamentals of analyzing the functioning and forecasting of the current and future transport network of the European and Cisural Arctic in modern economic conditions, taking into account: the location of promising sources of freight flows in the territory under consideration, data on the carrying and capacity of the network and its development prospects. Considering the incompleteness of time series of statistical indicators characterizing the operation of the transport network, the study, along with classical methods of forecasting traffic volumes, pays significant attention to scenarios for its development. The paper describes the transport network of the European and Cisural Arctic of the Russian Federation, defines strategic planning, and shows the importance of analyzing the functioning of the transport network of the region. Forecasts of traffic volumes have been obtained, their assessment and scenarios for the development of the transport network have been compiled using a combined forecasting system. A methodology has been developed for analyzing the functioning and forecasting the development of the transport network of the European and Cisural Arctic.

Stochastic cluster head selection model for energy balancing in IoT enabled heterogeneous WSN

Energy dissipation is the most important design limitation for Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs). In order to prolong the life of WSNs, the energy of nodes must be used in an effective way. Clustering is a strategy that may effectively use the energy of the sensors, extending the life and scalability by managing the network load balance. The energy usage for network operation is reduced by using an evolutionary algorithm called Genetic Algorithm (GA). The Stochastic Cluster Head Selection Model (SCHSM) is described in the proposed protocol by taking the factors such as distance, node energy, density and capacity of nodes for developing the fitness function. The proposed protocol is designed for multiple movable sink nodes and this greatly improves the energy balancing factor in the network. For minimizing the communication gap among sensors and sinks, movable sinks can be placed carefully. Simulation results are analyzed for the system effectiveness.

Realization of Reliable and Effective Authentication in Intelligent Systems by Using Visual Biometrics Methods

The main purpose of this article is to consider the aspects of ensuring security and increasing the efficiency of the authentication process in intelligent systems using visual biometrics. The work is aimed at the development and improvement of authentication systems using advanced biometric identification methods. An intelligent system has been created that ensures secure authentication of users of the current system, using a Siamese neural network. In addition to the implementation of basic security measures in the form of hashing and saving user logins and passwords, the implementation of two-factor authentication is important nowadays, which significantly strengthens the protection of user data and prevents most modern methods of hacking and stealing user data. Two-factor authentication is implemented as a technology for searching, recognizing and comparing the faces of system users, as visual biometrics is more secure than other types of two-factor authentication. Different variations of the possible implementation of Siamese neural network using Contrastive loss function and more modern Triplet loss function were reviewed and accordingly, a neural network using Triplet loss function was accomplished and trained. After training and verifying the correct operation of the neural network, it was integrated into the created intelligent system, thanks to which an effective way of recognizing the face of the system user was created, saving the received information in the database and further comparing the current user with the stored face during authentication. As a result, a secure and reliable intelligent system was created that cutting down the risk of unapproved access to the user account and uses an effective and modern method of user authentication.

OPLEM: Open Platform for Local Energy Markets

Local Energy Markets (LEMs) have been proposed as an effective solution to coordinate distributed energy resources within emerging smart local energy systems. However, LEMs are still at an early stage of development and are not widely implemented yet. Extensible open-source software tools are needed to simulate different market designs and evaluate their feasibility and effectiveness. This paper presents OPLEM, an open-source Python package for modelling and testing LEM designs. It offers a modular and flexible framework to create and test market designs adapted for distribution networks. OPLEM integrates two distinct models—one for designing and simulating local energy markets, and another for network operation. Unlike existing tools, OPLEM platform offers a comprehensive solution that bridges the gap between market design and network operation assessment, enabling stakeholders to gain deeper insights into the interactions between market dynamics and grid performance. Additionally, the inclusion of participant and asset models further enhances the tool’s versatility, allowing for a holistic analysis. Thanks to its modular structure, OPLEM allows the development of customised LEM designs and initially incorporates four popular LEM designs: Time-of-Use pricing market, centralised dispatch with distribution locational marginal pricing, bilateral peer-to-peer market and auction market. By combining market design and network modelling functionalities, the tool empowers users to explore various scenarios and optimise market clearings to enhance both economic efficiency and grid reliability.

Critical Infrastructure in Historical Perspective: The Portuguese Railroad Network in the Second Half of the Nineteenth Century

In the 1850s, Portugal initiated an ambitious public works program spearheaded by railroads. In this article, I analyze how policymakers (congressmen, government officials, engineers, and military officers) debated and managed the construction and operation of the Portuguese railroad network using the theoretical framework of critical infrastructure. I show that railroads were deemed critical to modernize the country, draw it closer to the European core nations and further from the periphery, and to attract traffic to the Portuguese harbors. The absence of railroads was considered a vulnerability that could jeopardize Portugal as a nation and it fostered a sense of urgency that motivated policymakers to act, to a large extent, hastily. The construction of the network brought about other vulnerabilities that, for different motives, could threaten the future of the country. In a parallel way, the implementation of the system was marked by vulnerabilities that originated within or surrounding it, which limited its technical potential. Balancing between a literature review and the use of primary sources (parliamentary debates, technical reports, the press, and photography), I argue that the criticality associated with railroads, as a sociotechnical construction, was central to motivate their construction, but different vulnerabilities, inherent or external to the system, limited their influence and the advantages touted by its promoters.

Research on energy storage capacity optimization of rural household photovoltaic system considering energy storage sharing.

With the promotion of the photovoltaic (PV) industry throughout the county, the scale of rural household PV continues to expand. However, due to the randomness of PV power generation, large-scale household PV grid connection has a serious impact on the safe and stable operation of the distribution network. Based on this background, this paper considers three typical scenarios, including household PV without energy storage, household PV with distributed energy storage, and household PV with centralized energy storage. Then, a calculation model for PV local consumption rate and annual net cost under different scenarios is constructed. Combined with a natural village in Shandong Province, the PV local consumption rate and annual net cost under three scenarios are compared and analyzed, and the potential of energy storage sharing in reducing storage capacity and improving PV local consumption is explored. The results show that configuring energy storage for household PV can significantly improve the power self-balancing capability. When meeting the same PV local consumption, household PV centralized energy storage can achieve smaller energy storage configuration and lower cost compared to household PV distributed energy storage. Finally, suggestions are proposed to further promote the development of household PV energy storage system. The research results can provide reference for improving the local consumption of rural household PV and accelerating the application of household PV energy storage system.

Hybrid strategy of flexibility regulation and economic energy management in the power system including renewable energy hubs based on coordination of transmission and distribution system operators

Energy management of energy hubs in the power system impacts both transmission and distribution networks and their operations. Hence, to enhance efficiency, there should be bilateral coordination between distribution and transmission networks. Moreover, thanks to including power sources, storage, and responsive loads, hubs can earn financial benefits from the energy and ancillary services market. Therefore, this paper presents the operation of distribution and transmission networks in the presence of flexible-renewable energy hubs based on transmission system operator (TSO)-distribution system operator (DSO) coordination according to the market clearing price modeling in energy and flexibility markets. The proposed scheme minimizes the sum of the expected operating costs of the networks and hubs minus the expected flexibility profit of the hubs. The scheme is constrained to optimal power flow equations of the networks, flexibility limit of the networks, and flexibility-operation model of renewable energy hubs located in transmission and distribution networks. The unscented transformation method is used to model the uncertainties of load, renewable sources, and stationary storage (aggregation of electric vehicles). Energy price and flexibility are among the dual variables of the problem. To simultaneously calculate these variables and the main variables of the problem, an integrated model of the suggested scheme based on the penalty function technique is extracted. Eventually, numerical results validate the capability of the scheme in enhancing the operation, economic, and flexibility status of the proposed scheme, in which renewable sources along with storage and responsive load in the energy hub can obtain 100 % flexibility conditions for the networks. They help enhance the economic and operation indices of distribution and transmission networks by about 26 %-44 % and 22 %-33 % compared to the case without hubs and renewable sources.

MOMTA-HN: A Secure and Reliable Multi-Objective Optimized Multipath Transmission Algorithm for Heterogeneous Networks

With the rapid development of heterogeneous network technologies, such as mobile edge computing, satellite communications, self-organizing networks, and the wired Internet, satisfying users’ increasingly diversified and complex communication needs in dynamic and evolving network environments has become a critical research topic. Ensuring secure and reliable information transmission is essential for stable network operation in these complex environments. Addressing this challenge, this study proposed a secure and reliable multi-objective optimized multipath transmission algorithm for heterogeneous networks to enhance security and reliability during data transmission. The core principle of this algorithm was that multipath transmission can provide additional protection through redundant paths. This redundancy ensured that even if one path is attacked or fails, alternative paths can maintain data integrity and reachability. In this study, we employed the Optimized Non-dominated Sorting Genetic Algorithm II (ONSGA-II) to determine the range of the initial population and filter suitable paths by optimizing them according to different demand objectives. In the path selection process, we introduced an innovative deletion graph method, which ensures that redundant paths do not share any common links with the original paths, except when there are unique links. This approach enhances the independence of transmission paths and improves the security of the transmission process. It effectively protects against security threats such as single points of failure and link attacks. We have verified the effectiveness of the algorithm through a series of experiments, and the proposed algorithm can provide decision-makers with high-reliability and low-latency transmission paths in heterogeneous network environments. At the same time, we verified the performance of the algorithm when encountering attacks, which is superior to other classical algorithms. Even in the face of network failures and attacks, it can maintain a high level of data integrity and security.

Посткоммутационное импульсное закорачивание фаз как фактор повышения безопасности эксплуатации шахтной участковой электрической сети напряжения 3,3 кВ

The efficiency of ground short-circuiting the damaged phase of the network to the ground is analyzed in the context of finding ways to increase the electrical safety of mine site 3.3 kV power network operation. In the context of ensuring human protection from electric shock, the expediency is justified and a technical solution for post-commutation pulse phase short-circuiting in the reverse EMF circuit is provided for the asynchronous motors of the power consumers within a technological mine site.

Stochastic Optimal Operation of SOP-Assisted Active Distribution Networks with High Penetration of Renewable Energy Sources

This paper introduces a mixed-integer convex model for optimizing the scheduling of soft open points (SOPs) integrated with energy storage (ES) in active distribution networks (ADNs) with high proportions of photovoltaic sources, designed to ensure zero risk of constraint violations. A stochastic optimization model for ADNs is proposed to maximize the benefits of SOPs while simultaneously minimizing system power losses, SOP power losses, voltage deviations, PV power curtailment, battery energy storage system (BESS) operation cost, and utility power purchase. Uncertainties in PV generation and load demand are considered by Monte Carlo simulation and k-means technologies. Finally, simulation cases from a 21-bus distribution network show that the curtailment of PV sources is minimized and the power fluctuations of the BESS are reduced in comparison to the case without SOP. Constraints in the nodal voltages, power outputs, energy balance, and power flow are all satisfied.

ÉVALUATION DE LA VARIABILITÉ DE TENSION DANS LES SYSTÈMES ÉLECTRIQUES

Processes in large energy systems exhibit a high variability due to the stochastic nature of electricity production and use. However, the control of the energy transfer aims to achieve steady state operation, which is mostly described by signals fully identifiable by a finite set of parameters. Part of the control system is the process of information delivered through measurements. In this paper, we analyze the impact of the measurement system deployed for reporting the RMS parameter of the voltage signal on the quality of information in LV distribution networks. The operation of such networks is highly stochastic, and the chosen models based on averaging are not always appropriate; therefore, we propose to apply a statistic metric, i.e., the coefficient of variation of the root mean square deviation CV(RMSD).

Planning natural gas supply chain pathways for energy system decarbonisation: An Australian case study

The future role of natural gas systems in a deeply decarbonised world is very uncertain. This work seeks to characterise the changes that the clean energy transition is likely to induce in the natural gas chain, across extraction and transmission, distribution networks and gas consumption/use trends, for various scenarios with different demand and supply drivers. First, the results of a least-cost macro-scale energy system planning optimisation are explored to identify future natural gas demand and supply requirements. Second, those findings are used as inputs to a detailed analysis of the full gas supply chain, from extraction to final use, to examine the evolution of i) stored resource levels; ii) transmission and distribution networks operation and financing; and iii) required capacity and siting of gas generation; all, with a realistic account of the related infrastructure. Australia is investigated as a case study that relies on natural gas for both domestic and export purposes. Results project a shift towards a more localised gas consumption to be largely supplied by fewer basins, with associated potential transmission and extraction bottlenecks. They anticipate an overall less utilised, ageing distribution network with potential challenges to asset reliability and financing. Finally, they demonstrate both the scheduled and early retirement of fossil generation assets can allow the siting of considerable amounts of new gas power firming capacity on brownfield sites, thus offering an opportunity to reduce total system costs.

Formation the coefficient of growth for the power scale of transformers taking into account the operational indicators of substations

The article describes the sequence of formation of the growth coefficient of the transformers power scale, taking into account the operational indicators of substations. For this purpose, an expression for finding the optimal power of 110 kV transformers has been developed on the basis of a technical-economic model of costs for the transformation of electrical energy. The developed expression is used to find the optimal power of transformers of 110 kV in conventional units, taking into account the load of substations, which is the basis for the formation of the growth coefficient of the transformers power. The search for optimal power was performed on the basis of deviations of the indicators of the maximum load of transformers and the time of maximum losses. The time indicators of maximum losses and maximum load are calculated according to the hourly load data of transformers, taking into account the presence of generation nodes on the secondary voltage buses. The formation of the growth coefficient of the scale of transformers is performed by finding the mathematical expectation of the optimal power and its shift based on the boundaries of the distribution of two adjacent powers of transformers. The substantiation of the formed coefficient of growth of the transformers power was performed according to the criterion of minimum technological losses of electrical energy, by comparing the daily loses schedules in transformers. According to the research results, it follows that the application of the obtained coefficient allows to reduce the level of technological losses. The study was carried out on the example of operating substations with two-winding transformers of 110 kV using the scheme of the established mode of operation of the electric network.

Multi-objective optimization strategy for the distribution network with distributed photovoltaic and energy storage

The randomness and fluctuation of large-scale distributed photovoltaic (PV) power will affect the stable operation of the distribution network. The energy storage system (ESS) can effectively suppress the power output fluctuation of the PV system and reduce the PV curtailment rate through charging/discharging states. In order to improve the operation capability of the distribution network and PV consumption rate, an optimal multi-objective strategy is proposed based on PV power prediction. First, the back propagation (BP) neural network with an improved genetic algorithm (GA) is used to predict PV power output. Furthermore, an adaptive variability function is added to the GA to improve the prediction accuracy. Then, the distribution network model containing distributed PV and the ESS is constructed. The optimal object contains network power loss, voltage deviation, and PV consumption. The model is solved based on the improved multi-objective particle swarm optimization (MOPSO) algorithm of Pareto optimality. The probabilistic amplitude is adopted to encode the particles for avoiding local optimal. Finally, the proposed optimal strategy is verified by the IEEE 33-bus distribution network. The results show that the proposed strategy has an obvious effect on reducing the network power loss and voltage deviation, as well as improving the PV consumption rate.

Analysis of the Influence of Distributed Photovoltaic Access on the Operation Quality of Asymmetry Distribution Network

Abstract Distributed photovoltaic(PV) power generation, as a highly flexible renewable energy source, is currently developing rapidly and has been widely used. However, due to its uncertainty and randomness, large-scale distributed photovoltaic integration into the distribution network will change the network power flow distribution, which will have a greater impact on the operation quality of the distribution network operation. In order to study the influence of distributed PV access on the operation of asymmetry distribution network, this paper builds a three-phase power flow model of distributed photovoltaic access to distribution network. Based on the IEEE33 node three-phase calculation example data, the impact of distributed photovoltaic access location and capacity on a series of operation indicators such as voltage deviation, three-phase unbalance and network loss under asymmetry operation of the distribution network is studied. Finally, for the asymmetry distribution network operating condition, guidance suggestions for distributed photovoltaic access based on operation quality are given.

Linear optimal power flow model for modern distribution systems: Management of normally closed loop grids and on-load tap changers

Modern distribution systems face new challenges due to the rise of small-scale renewable energy resources and the electrification of energy demand. Additionally, the complexity of network management increases with the exchange of flexibility services between distribution and higher voltage levels. The system operator's role involves optimizing the planning and operation of the distribution network. In current scenarios, this includes managing flexibility resources (such as generators, demand response, and on-load tap changers) and implementing new operating strategies (such as closed-loop topologies and dynamic reconfiguration). This paper proposes a reformulation of one of the most used linear approximations of the Optimal Power Flow model for distribution networks. The novelty of this reformulation lies in integrating equations to handle tap-changing transformers with closed-loop/meshed network operation, while preserving the original linear formulation and computational tractability.

Robust Assessment of Hosting Capacity of Renewable Generation in Distribution Systems Considering the Active Network Management

Abstract As the penetration rate of renewable distributed generation (RDG) increases, its random fluctuation characteristics have brought many problems to the safe operation of the active distribution network (ADN), such as voltage over-limit, reverse flow, and deterioration of power quality. Therefore, it has effectively affected the new energy hosting capacity of the ADN. Therefore, the effective assessment of the new energy hosting capacity of the ADN is a key part of the distribution network planning. In order to cope with the random fluctuation characteristics of new energy, this paper presents a two-stage robust assessment method of RDG hosting capacity of distribution networks by considering active network management (ANM) techniques such as network reconfiguration, reactive power compensation and on-load voltage regulation. Finally, the improved IEEE-33 distribution system is used to verify the results. The proposed method has been shown to be effective for evaluating the ADN’s RDG hosting capacity.