Industrial Power Grid Research Articles

Comprehensive review and analysis of photovoltaic energy conversion topologies

Energy conversion is a pivotal process with widespread applications, spanning renewable energy systems, electric vehicles, and industrial power grids. Selecting the right energy conversion topology is critical for optimizing system performance, efficiency, and reliability. This comprehensive review paper provides a thorough overview of energy conversion topologies used in photovoltaic (PV) panel systems, as well as their applicability in diverse domains. Furthermore, the paper conducts a detailed analysis of commonly employed energy conversion topologies. Each topology is meticulously examined based on its operating principles, advantages, drawbacks, and typical use cases. This comprehensive review serves as an invaluable resource for researchers, engineers, and practitioners engaged in the dynamic field of energy conversion, offering insights into both wind energy and photovoltaic panel systems.

СУЧАСНІ ТЕНДЕНЦІЇ РОЗВИТКУ СИСТЕМ КОМПЕНСАЦІЇ РЕАКТИВНОЇ ПОТУЖНОСТІ

This paper surveys current trends and developments in reactive power compensation systems, elucidating their significance in enhancing system capacity and flexibility. By analyzing the capacity factor enhancement enabled by reactive power compensation, the study underscores its role in optimizing electricity delivery, thus conserving energy resources and facilitating the integration of renewable energy sources. It explores the key models and concepts driving advancements in reactive power compensation within power grids. As modern electrical systems grow in complexity, ongoing research into improving compensation methods becomes imperative to ensure the reliability and efficiency of industrial power grids. Future endeavors will involve developing a model utilizing real-world enterprise data to investigate the effects of technological variations in filter parameters on the performance of complex reactive power compensation schemes, encompassing both filters and capacitor banks. Keywords: reactive power, compensation systems, filter-compensating circuit, industrial power grid, electric power. Context. The paper considers the current trends used in the field of reactive power compensation, and the main directions of development of modern methods of reactive power compensation. Objective. The purpose of the work is to overview of current trends in the development of reactive power compensation systems, as well as an overview of possible ways of their effective application in various industrial networks. Methods. The paper presents a key aspect of reactive power compensation is its ability to increase system capacity and flexibility. By improving the capacity factor, utilities can deliver electricity more efficiently, reducing the need for excess capacity and thus conserving energy resources. In addition, this process plays an important role in supporting the integration of renewable energy sources such as wind and solar power, which often introduce volatility into electricity generation schemes. Results. The paper presents the main models and concepts in the field of reactive power compensation in power grids. Conclusions. Given the growing complexity of modern electrical systems, it is important to continue research into improving methods and means of reactive power compensation to ensure the reliability and efficiency of industrial power grids. In further research, it is planned to develop a model using a real enterprise as an example and investigate the impact of technological deviations of filter parameters on the steady-state and transient performance of complex reactive power compensation schemes, including not only filters but also capacitor banks.

ANALYSIS OF REACTIVE POWER COMPENSATION MEANS IN ELECTRIC NETWORKS OF AZERBAİJAN

The article analyzes the existing reactive power compensation in the electrical systems of Azerbaijan, and also examines the problems and shortcomings that arise in the reliable supply of electrical energy to consumers and provides information about the sources of RP that are produced in the industry of the republic. The most important task that requires solving the problem of improving the quality of electrical energy in the country's networks, both at the design stage and at the operation stage of electrical power supply systems, is reactive power compensation. Based on this, it is necessary to select RP sources, their favorable placement, regulation and calculation of their power in accordance with the existing power supply system. Benefits RP in industrial electrical networks include many issues, the solution of which is aimed at increasing the effective power factor and stability of electrical devices, their efficiency, improving the quality of electricity and, in general, the reliability of the electrical system. Currently, there are still issues that have not been resolved and require a special approach for their implementation. Such important issues include: determining the installation of compensation devices, choosing their number, type, safe operation and protection. In the industrial power grids of Azerbaijan, issues of automatic control of RP are at the development stage and for this development, adequate mathematical models of a rational RPK system with minimal losses are being considered. To solve the above, targeted scientific methods are created. The problem of RPK in modern electrical systems of Azerbaijan is important for the following reasons: 1) the consumption of reactive energy increases due to an increase in loads with the consumption of reactive current in the country’s electrical networks; 2) the growth of RP consumption is accelerating compared to active consumption in many sectors of industrial production; 3) there is an increase in reactive energy consumption not only in large urban power grids, but also in small rural ones. Keywords: reactive power, compensating devices, electrical devices, energy, system, quality, synchronous compensator, static capacitor.

Heuristic control of power consumption by up to 1000 V electrical loads at mining enterprises

Purpose. To develop a method for synthesizing the structure and algorithm of the system for automated control of power consumption by up to 1000 V electrical receivers at mining enterprises with iron ore underground mining methods. This enables direct control of the load connection to the industrial power grid to ensure minimum power costs depending on its cost per day ahead. Methodology. The problem of controlling power consumption of electrical receivers at iron ore underground mines is formalized as a binary form of mixed integer programming. To solve it, a binary implementation of the heuristic genetic algorithm is used. The mathematical modeling method analyzes the impact of genetic algorithm settings, such as the number of phenotypes in the population, the number of elite phenotypes that pass unchanged to the next generation, and the method of phenotype crossover on its quality. Findings. As a result of the research, it is found that the most effective way to control the process of power consumption based on an evolutionary genetic algorithm is to use the Laplace crossover function and keep the percentage of elite phenotypes in the population at 10 %. Moreover, at the smallest population size, the best accuracy is observed when using the Laplace function, while at one- and two-point crossover functions, it worsens, but not significantly (no more than 0.2 %). However, as the number of elite phenotypes increases, the duration of the evolutionary search in the control process is reduced by almost a factor of two in the case of one- and two-point crossovers. Originality. For the first time, the structure of a heuristic system for automated control of power consumption by underground electrical receivers with a supply voltage of up to 1000 V at iron ore underground mines has been developed on the basis of an evolutionary genetic algorithm. Depending on the designed volumes of ore production and the daily power cost per day, this allows determining the optimal power load schedule of underground distribution substations in advance, which, subject to the accepted limits on hourly and daily power, minimizes the cost of purchasing power, and thus reduces the cost of the final product. Practical value. The architecture of a heuristic system for controlling power consumption by electrical receivers with a voltage of up to 1000 V based on an evolutionary genetic algorithm is developed and recommended when optimizing the power load schedule of transformer substations of mining and metallurgical enterprises, in particular, of iron ore underground mines operating in this voltage class.

Power Compatibility of Induction Motors in Industrial Grids Containing Synchronous Generators

Starting an induction motor causes voltage sag in the industrial grid that may disturb the operation of grid equipment. Direct-on-line starting is the simplest and most cost-effective method for starting induction motors, but also the most problematic. Large industries often use internal power plants with synchronous generators and starting powerful motors may impact the generator operations. The synchronous generators could be operated with the automatic or manual mode of voltage control. As the operation experience proves, the generator voltage control mode has a significant impact on the transient behaviours in the industrial power grid when starting a large induction motor. This article presents a case study of the synchronous generator tripping within a true medium-voltage industrial grid during the direct-on-line starting of a large induction motor driving the feed water pump. An analysis of the generator protection logs after the tripping showed that the synchronous generator was controlled in manual mode and its protection relay settings were exceeded. The transients initiated by induction motor starts were studied for possible configurations and operating conditions of the grid using a model developed on the Matlab/Simulink Software platform. The simulations have shown that concern about starting large motors in industrial grids containing internal synchronous generators needs to be solved considering the grid configurations and the coordination of generator protection and control devices.

Reinforcement-Learning-Based Proactive Control for Enabling Power Grid Resilience to Wildfire

Industrial electric power grid operation subject to an extreme event requires decision-making by human operators under stressful conditions. Decision making using system data informatics under adverse dynamic events, especially if forecasted, should be supplemented by intelligent proactive control. Power transmission system operation during wildfires requires resiliency-driven proactive control for load shedding, line switching, and resource allocation considering the dynamics of the wildfire and failure propagation to minimize the impact on the system. However, the possible number of line and load switching in an extensive industrial system during an event make traditional prediction-driven and stochastic approaches computationally intractable, leading operators to often use pre-planned or greedy algorithms. In this work, we model and solve the proactive control problem as a Markov decision process and introduce an integrated testbed for spatio-temporal wildfire propagation and proactive power-system operation. Our approach allows the controller to provide setpoints for all generation fleets in the power grid. We evaluate our approach utilizing the IEEE test system mapped onto a hypothetical terrain. Our results show that the proposed approach can help the operator to reduce load outage during an extreme event. It reduces power flow through lines that are to be de-energized, and adjusts the load demand by increasing power flow through other lines.

Cloud Server-Assisted Remote Monitoring and Core Device Fault Identification for Dynamically Tuned Passive Power Filters

Reliability and safety are crucial for the operation of a dynamically tuned passive power filter (DTPPF). Safe performance of DTTPFs implies complete normal filtering without failure within a specified period. To prevent potential disaster or economic loss, it is desirable to achieve early warning of any core device faults in a DTPPF based on its running state and to optimize its harmonic mitigation performance. In this paper, we explore effective methods for identifying core device faults in DTPPFs. First, we summarize the characteristic parameters of faults, running state parameters, parameters required for fault monitoring, and fault type parameters. Then, a cloud server-assisted remote monitoring and fault identification system for DTPPF is proposed, which consists of monitoring system’s architecture and cloud servers’ software architecture as well as software design of the back-end service layer and functional design of the front-end application layer. Our experiments demonstrate that the proposed system can monitor the real-time operational status of the DTPPF, enabling remote diagnosis and identification of core device faults. Moreover, it is user-friendly, as it is capable of optimizing equipment maintenance schedules and utilizing manufacturers’ service capacities. Therefore, this research provides a theoretical foundation for harmonic mitigation in low-voltage distribution networks and is valuable for practical engineering applications in industrial power grids.

Classification of voltage sags causes in industrial power networks using multivariate time‐series

AbstractVoltage sags are the most frequent and impactful disturbances in industrial power grids, leading to high financial losses for industrial clients. The identification of the cause and its relative location is crucial for the contractual relation between the energy provider and the industrial customers. This paper proposes a methodology to identify the origins of voltage sags based on instantaneous symmetrical components and dynamic time warping. Short‐Time Fourier and Fortescue transform are implemented in the pre‐processing step using the voltage and current waveforms. Then, a distance‐based classification strategy to identify the sources of voltage sags is used. It relies on a four‐dimension time‐series signature used as features. Moreover, a confidence index associated with the classification output is provided. The proposal offers an easy implementation in industrial applications with no previous recorded data. It has the benefit of using a reduced‐size reference database entirely composed of synthetic data. The main advantages of the proposed method are its generalization capabilities and the possibility of raising an alert based on the confidence index. The obtained classification accuracy on synthetic data with seven causes is 100%. The method reaches a classification F1‐score higher than 99% with field measurements representing five classes obtained from three different industrial sites.

Secondary Frequency Control Considering Optimized Power Support From Virtual Power Plant Containing Aluminum Smelter Loads Through VSC-HVDC Link

The growing number of renewable energy replacing conventional generators results in a loss of the reserve for frequency control in power systems, while many industrial power grids often have excess energy supply due to abundant wind and solar energy resources. This paper proposes a secondary frequency control (SFC) strategy that allows industrial power grids to provide emergency high-voltage direct current (HVDC) power support (EDCPS) for emergency to a system requiring power support through a voltage source converter (VSC) HVDC link. An architecture including multiple model predictive control (MPC) controllers with periodic communication is designed to simultaneously obtain optimized EDCPS capacity and minimize adverse effects on the providing power support (PPS) system. Moreover, a model of a virtual power plant (VPP) containing aluminum smelter loads (ASLs) and a high penetration of wind power is established for the PPS system. The flexibility and controllability of the VPP are improved by the demand response of the ASLs. The uncertainty associated with wind power is considered by chance constraints. The effectiveness of the proposed strategy is verified by simulation results using the data of an actual industrial power grid in Inner Mongolia, China. The DC voltage of the VSCs and the DC in the potlines of the ASLs are also investigated in the simulation.

Fast electromigration stress analysis using Low-Rank Balanced Truncation for general interconnect and power grid structures

Electromigration (EM) has become one of the most significant challenges considering longterm reliability in integrated circuit design. The problem is caused by the large current density in circuit interconnections. However, in most cases, we are interested in the EM stress at specific points of the interconnect, such as vias, junctions and boundaries. As a result, Model Order Reduction (MOR) techniques can provide attractive methodologies to reduce the complexity of the original systems. System-theoretic techniques like Balanced Truncation (BT) offer very reliable bounds for the approximation error, compared to moment-matching methods. In this paper, we apply a computationally efficient Low-Rank BT procedure based on the extended Krylov subspace method, that can handle large-scale models and significantly accelerate the EM stress analysis for any general interconnect or power grid structure. For the experimental evaluation, we first consider a general structure interconnect tree to demonstrate the generalizability of the proposed method and then we employ our method on the industrial IBM power grid benchmarks where the its scalability is shown. For the latter, we demonstrate that our method can achieve a speedup up to 238× over a standard transient analysis method and a speedup up to 15× over COMSOL, while exhibiting negligible error.

Improving the area of harmonic pollution and vulnerability to voltage sag for compatible and reliable operation of sensitive harmonic loads

Nowadays, sensitive harmonic loads (SHLs) are being increasingly used in the industrial sector. SHLs generate harmonics and may become disconnected from the network when voltage sags occur at the point of common coupling (PCC). Here, a new approach is proposed to reduce harmonics distortion and establish a more reliable annual operation of SHLs by reducing the area of pollution (AOP) with harmonic and the area of vulnerability (AOV) to voltage sag, respectively. The proposed approach includes an innovative optimization problem for planning passive harmonic filters which is solved by the Non-dominant Sorting Genetic Algorithm (NSGA-II) on the basis of historical data of the industrial power grid. By doing so, a solution is obtained in which the costs of passive harmonic filters and financial costs due to grid losses and voltage sags are minimized. In order to assess the new proposed approach, an Iranian large copper mine electrical network equipped with SHLs is used. Results of using the new approach show that total harmonic distortion and grid losses decrease by nearly 80% and 15%, respectively and also, the voltage value at the PCC is improved which can assure the secure operation of SHLs. Moreover, decreased financial losses is obtained since voltage sags are reduced by 65%.

Identification of Grid Impedance by Broadband Signals in Power Systems with High Harmonics

Grid impedance is an important parameter and is used to perform impedance-based stability analysis for the operation of grid-connected systems, such as power electronics-interfaced solar, wind and other distributed power generation systems. The identification of grid impedance with the help of broadband signals is a popular method, but its robustness depends strongly on the harmonic disturbances caused by non-linear loads or power electronics. This paper provides an in-depth analysis of how harmonics affect the identification of grid impedance while using broadband measurements. Furthermore, a compensation method is proposed to remove the disturbing influences of harmonics on broadband impedance identification. This method is based on exploiting the properties of the used maximum-length binary sequence (MLBS). To explain the methodology of the proposed method, the design basis for the excitation signal is discussed in detail. The analysis from simulations and a real measurement in an industrial power grid shows the effectiveness of the proposed method in compensating the disturbing influences of harmonics on broadband impedance measurements.

Charging stations for electric cars using hybrid energy storage systems

In this article, it is proposed to use energy storage devices as a part of charging stations to reduce the powerful load for the power system during the hours of the greatest energy consumption. This is due to the analysis results for the growth trends of the electric vehicles. By the example of the city Novosibirsk, according to the forecasts of analytical companies about the trend of increasing the number of electric cars (ECs) in Russia, the average energy consumption per day for charging ECs has been calculated. Based on the calculation results, the influence of charging stations on the daily schedule of the active load for the industrial power grid is shown and the capacity lack problem is identified. The experimental measurements results at traction substation No. 29 in Novosibirsk are presented.

Combining Business Model Innovation and Model-Based Analysis to Tackle the Deep Uncertainty of Societal Transitions—A Case Study on Industrial Electrification and Power Grid Management

Creating new business models is crucial for the implementation of clean technologies for industrial decarbonization. With incomplete knowledge of market processes and uncertain conditions, assessing the prospects of a technology-based business model is challenging. This study combines business model innovation, system dynamics, and exploratory model analysis to identify new business opportunities in a context of sociotechnical transition and assess their prospects through simulation experiments. This combination of methods is applied to the case of a potential business model for Distribution System Operators aiming at ensuring the stability of the electrical grid by centralizing the management of flexible loads in industrial companies. A system dynamics model was set up to simulate the diffusion of flexible electrification technologies. Through scenario definition and sensitivity analysis, the influence of internal and external factors on diffusion was assessed. Results highlight the central role of energy costs and customer perception. The chosen combination of methods allowed the formulation of concrete recommendations for coordinated action, explicitly accounting for the various sources of uncertainty. We suggest testing this approach in further business model innovation contexts.

Non-intrusive monitoring and disaggregation of industrial load based on Petri net theory

In this paper, the non-intrusive monitoring and disaggregation method of industrial load based on Petri net theory is studied. First, the basic concepts of Petri nets are introduced. On the basis of prototype Petri nets, time factor is added. Then, the Petri net with time factor is combined with industrial load production process. Considering the production sequence, start-stop time and production time constraints of industrial load, a non-intrusive monitoring and disaggregation model of industrial load is constructed. Finally, according to the actual production process of industrial load, the electricity consumption situation of each production link is calculated, and the detailed analysis results of industrial user’s electricity consumption behavior are obtained. The research could provide an important reference for realization of friendly interaction between industrial users and power grid.

Sustainable Development of Power Retailers and Industrial Parks in China’s Belt and Road Initiative

Energy infrastructure construction is a top priority and focus for the Belt and Road Initiative (BRI), and this drives dramatical demand for significant energy consumption growth and investment funds in BRI countries. In response, the concept of a regional power grid of an industrial park (RPGIP) has emerged as a new energy infrastructure, where the industrial power supply, load, and grid are integrated to form a balanced and independent regional power grid. Moreover, dramatically increased market competition on the retail side of the electricity market challenges developing countries striving to achieve sustainable development of power retailers. This paper proposes that power retailers transform into energy saving companies (ESCOs) to participate in the electricity management of an RPGIP. By using a financing scheme realized by asset securitization, power retailers can smoothly participate in the construction and operation of a power system of BRI that contributes to accelerating energy infrastructure construction, the electricity management of the RPGIP, and sustainable development of power retailers in BRI countries. Furthermore, this study provides a game analysis for achieving maximum benefits of power retailers and industrial consumers in the implementation of the financing scheme.

Prospects for IGBT application in electrical power converters for industrial high-current DC loads

The paper presents the research data of the electrical power converters used for a powering industrial vacuum DC arc furnace. The authors have analyzed energy performance of the power converter with a parametric current source (PCS) and the converter based on switched-mode power supply (SMPS) units with IGBT switches. The research shows that the converter with SMPS units has greater efficiency, thereby reducing specific energy consumption. To improve power quality in industrial power grids, which provide electricity to high-current DC loads, a converter design based on current-source-type active rectifiers is proposed. The simulations carried out by the authors have shown that desynchronization of AR switching processes in the proposed converter system allows one to reduce total harmonic distortion (THD) of the mains voltage.

Data center holistic demand response algorithm to smooth microgrid tie-line power fluctuation

With the rapid development of cloud computing, artificial intelligence technologies and big data applications, data centers have become widely deployed. High density IT equipment in data centers consumes a lot of electrical power, and makes data center a hungry monster of energy consumption. To solve this problem, renewable energy is increasingly integrated into data center power provisioning systems. Compared to the traditional power supply methods, renewable energy has its unique characteristics, such as intermittency and randomness. When renewable energy supplies power to the data center industrial park, this kind of power supply not only has negative effects on the normal operation of precision equipment, such as CPU/GPU chips and hard disk, in data center, but it would also impact the stability of the utility power grids operation. To solve this problem, this paper presents a novel tie-line power fluctuation smoothing algorithm with consideration of data center’s holistic demand response. The contributions of this paper are: (1) overcoming the limitations of treating IT load as uncontrollable workload in the traditional demand response research, we design a data center resource scheduling model to realize IT load demand response controllability; (2) two novel mechanisms are proposed: (i) the server cluster workload scheduling method with time shift mechanism, and (ii) the data center UPS (Uninterruptible Power Supply) energy storage dynamic response mechanism. (3) Combining these two mechanisms as holistic demand response of data center, we present a tie-line power fluctuation smoothing algorithm to improve power supply reliability, which is beneficial to both the high density and precision IT equipment in the data center and the utility power grid. In the experiments, the results show that the new algorithm can effectively regulate the tie-line power fluctuations under different server cluster utilization ranges and scenarios of large-scale penetration of distributed renewable energy scenarios. The new algorithm is hence able to contribute beneficially to the reliability and stability of intelligent industrial park micro-grid and utility power grids.

A 10-kV/400-V 500-kVA Electronic Power Transformer

This paper presents the design and development of a three-phase 10-kV/400-V 500-kVA electronic power transformer (EPT). The power circuit is designed in a modular fashion, i.e., the main circuit consists of many identical ac–dc–dc–ac modules (abbreviated as power modules). Each power module consists of a high-voltage power cell, a low-voltage power cell (LVPC), a medium-frequency isolation transformer, and a filter. The corresponding control and protection system is developed. A special three-stage startup strategy is designed to shorten the startup time and reduce the startup inrush current. The negative-sequence current compensation is introduced in the input stage to handle the unbalanced loads. To keep the dc-link voltages balanced, an individual dc voltage balancing controller based on regulating the output power of each parallel LVPC is proposed. The detailed control hardware design and software implementation are discussed. The functions of this 10-kV EPT prototype are verified through the laboratory and field tests. The results are shown in this paper. Currently, the prototype is operating in the industrial power grid.

Population-Based Algorithms for Optimization of the Reactive Power Distribution and Selection of the Cable Cross-Section in the Power-Supply Systems

The article is devoted to optimization of the reactive power sources arrangement in the industrial power grid to reduce the active power losses in transmission lines and select cross-sections of cable of the lines. To reduce the losses installing of additional reactive power sources in junctions of the grid are proposed. Thus, a problem of the optimal arrangement of the reactive power sources is appeared. This problem was solved by two stochastic optimization algorithms such as the Genetic and the Particle Swarm optimization algorithms. The cost-effectiveness of the suggested method is shown.