Electric Power Demand Research Articles

Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration

Rapid industrialization and its automation on the globe demands increased generation of electrical energy with more reliability and quality. Renewable energy (RE) sources are considered as a green form of energy and extensively used as an alternative source of energy for conventional energy sources to meet the increased demand for electrical power. However, these sources, when integrated to the utility grid, pose challenges in maintaining the power quality (PQ) and stability of the power system network. This is due to the unpredictable and variable nature of generation by these sources. The distributed flexible AC transmission system (DFACTS) devices such as distributed static compensator (DSTATCOM) and dynamic voltage restorer (DVR) play an active role in mitigating PQ issues associated with RE penetration. The performance of DFACTS devices is mostly dependent on the type of control algorithms employed for switching of these devices. This paper presents a comprehensive review of various conventional and adaptive algorithms used to control DFACTS devices for improvement of power quality in utility grids with RE penetration. This review intends to provide a summary of the design, experimental hardware, performance and feasibility aspects of these algorithms reported in the literature. More than 170 research publications are critically reviewed, classified, and listed for quick reference for the advantage of engineers and academician working in this area.

Performance Analysis of Different Types of Machine Learning Classifiers for Non-Technical Loss Detection

With the ever-growing demand of electric power, it is quite challenging to detect and prevent Non-Technical Loss (NTL) in power industries. NTL is committed by meter bypassing, hooking from the main lines, reversing and tampering the meters. Manual on-site checking and reporting of NTL remains an unattractive strategy due to the required manpower and associated cost. The use of machine learning classifiers has been an attractive option for NTL detection. It enhances data-oriented analysis and high hit ratio along with less cost and manpower requirements. However, there is still a need to explore the results across multiple types of classifiers on a real-world dataset. This paper considers a real dataset from a power supply company in Pakistan to identify NTL. We have evaluated 15 existing machine learning classifiers across 9 types which also include the recently developed CatBoost, LGBoost and XGBoost classifiers. Our work is validated using extensive simulations. Results elucidate that ensemble methods and Artificial Neural Network (ANN) outperform the other types of classifiers for NTL detection in our real dataset. Moreover, we have also derived a procedure to identify the top-14 features out of a total of 71 features, which are contributing 77% in predicting NTL. We conclude that including more features beyond this threshold does not improve performance and thus limiting to the selected feature set reduces the computation time required by the classifiers. Last but not least, the paper also analyzes the results of the classifiers with respect to their types, which has opened a new area of research in NTL detection.

Dynamic Modeling and Heat Flow Study of a Thermal Power Plant Using OpenModelica

With the integration of intermittent energy sources in the power system, the main focus of thermal power plant design is to optimize the conventional system by improving efficiency and flexibility of power generation in the start-up and base-load procedures. This paper focuses on the behavior of thermal power generation with respect to load variations, fuel variations, weather conditions and internal dynamics of the system to aid in energy planning and the optimization of power system. Dynamic modeling and subsequent simulation is to make improvements. Therefore, to model the system, this research study has used a dynamic modeling and a simulation framework (OpenModelica based on modelica language) which is an object-oriented and equation-based language. This framework allows a non-causal modeling and a flexible reuse of the models since data-flow direction is not predefined like other state of the art simulating tools i.e. MATLAB. The proposed model analyses the trend of electrical power generation of KOT ADDU thermal power plant to predict the future demand of electrical power. The achieved results show more than 90% accuracy of the proposed model in the transient operation such as start-up and base load procedure.

Разработка авиационного синхронного генератора мощностью 250 кВА с переменной частотой вращения

To meet the growing demand for electric power on board of an aircraft, a need arises to construct powerful generators that have low mass, high power performance characteristics and mechanical strength. It is expected that by furnishing an aircraft with more electricity it will be possible to obtain numerous advantages, including lower costs for aircraft operation and maintenance [3]. The most promising way of achieving this is to use synchronous generators with electromagnetic excitation. However, the development of such machines involves serious difficulties stemming from lack of well-matured methods for analyzing synchronous generators with a floating rotation frequency for capacities above 250 kVA. The article describes an approach to elaborating a comprehensive technique for designing high-capacity aircraft synchronous generators that takes into account both structural strength matters and electromagnetic and thermal processes. The results from modeling the structural arrangement of a nonsalient-pole synchronous generator with a reduced number of inductor teeth are also given. Such generator provides the nominal power output equal to 250 kVA in the entire range of its rotation frequencies from 7200 to 6000 min-1.

Enhancement transient stability of power system using UPFC with M-PSO

<span>During the last few decades, electrical power demand enlarged significantly whereas power production and transmission expansions have been brutally restricted because of restricted resources as well as ecological constraints. Consequently, many transmission lines have been profoundly loading, so the stability of power system became a Limiting factor for transferring electrical power. Therefore, maintaining a secure and stable operation of electric power networks is deemed an important and challenging issue. Transient stability of a power system has been gained considerable attention from researchers due to its importance. The FACTs devices that provide opportunities to control the power and damping oscillations are used. Therefore, this paper sheds light on the modified particle swarm optimization (M-PSO) algorithm is used such in the paper to discover the design optimal the Proportional Integral controller (PI-C) parameters that improve the stability the Multi-Machine Power System (MMPS) with Unified Power Flow Controller (UPFC). Performance the power system under event of fault is investigating by utilizes the proposed two strategies to simulate the operational characteristics of power system by the UPFC using: first, the conventional (PI-C) based on Particle Swarm Optimization (PI-C-PSO); secondly, (PI-C) based on modified Particle Swarm Optimization (PI-C-M-PSO) algorithm. The simulation results show the behavior of power system with and without UPFC, that the proposed (PI-C-M-PSO) technicality has enhanced response the system compared for other techniques, that since it gives undershoot and over-shoot previously existence minimized in the transitions, it has a ripple lower. Matlab package has been employed to implement this study. The simulation results show that the transient stability of the respective system enhanced considerably with this technique.</span>

Energy Optimization Analysis of Turbofan Engine for More-Electric Civil Aircraft

The civil aviation industry is moving into the more-electric environment where the civil aircraft uses electricity to meet the multiple energy demands of the associated aircraft subsystems. The civil aircraft’s turbofan engine, which is the largest energy supply system of civil aircraft, will thus utilize more fuel resource to provide increased electric energy besides of its conventional responsibility of maintaining the fundamental thrust requirements by aircraft. This will introduce new challenge for the energy optimization analysis of aircraft turbofan engine: it was nearly a simple optimal setting of engine’s component parameters for keeping required thrust, but under the more-electric environment it will become an optimization problem in order to minimize the fuel consumption while obeying the multiple constraints by thermodynamic limits of turbofan engine and by varying electric power demands associated with the flight profile of aircraft. We present a complete modeling in this paper for the energy optimization analysis of turbofan engine for more-electric civil aircraft and formulate it as a nonlinear programming form. We propose an algorithm based on Benders decomposition method to solve this problem; the numerical results demonstrate the economic effectiveness of the proposed modeling and algorithm.

Photocathode study of the CompactLight Collaboration for a novel XFEL development

The latest generation of light sources, the Free Electron Lasers that are capable of delivering high-intensity photon beams of unprecedented brilliance and quality, provide a substantially novel way to probe matter with a very high, largely unexplored potential for science and innovation. The CompactLight Collaboration intends to design a hard X-ray FEL facility beyond today’s state of the art using the latest concepts for bright electron photoinjectors, very high-gradient X-band structures at 12 GHz, and innovative compact short-period undulators. When compared to existing facilities, the proposed facility will benefit from a lower electron beam energy, due to the enhanced undulator performance, will be significantly more compact with a smaller footprint, as a consequence of both the lower energy and the high-gradient X-band structures, and will have a much lower electrical power demand. This paper gives an overview of different candidate photocathode materials for use in conjunction with a laser and presents the proposed design of the photocathode and the related laser. Also presented are the e-gun with solenoid selection and design, together with relevant simulation results.

Modeling, integration, and optimal selection of the turbine technology in the hybrid wind-photovoltaic renewable energy system design

Electric power demand in the remote areas can be effectively supplied by the renewable resources. In this context, hybrid wind-photovoltaic systems have attracted more attention due to the system cost reduction and higher level of the supply reliability. In the past decade, various models have been proposed for optimal sizing of the system components with various objectives. In the previous studies, a typical wind turbine for capturing wind power is considered. In this case, changing turbine parameter will change results of the problem to a large extent. In other word, selecting optimal turbine technology is not considered as an influential decision variable. In this paper, a novel formulation is proposed to incorporate turbine technology selection in the optimal hybrid wind/photovoltaic renewable energy system design. The proposed model will select the optimal turbine model among a set of the choices. Also, optimum size of the other equipment according to the problem conditions will be determined. Results of testing the model in the various scenarios demonstrate efficiency and also functionality of the proposed model in real cases.

Methodology for the characterization of the electrical power demand curve, by means of fractal orbit diagrams on the complex plane of Mandelbrot set

The present article proposes a new geometric space in the complex plane of the Mandelbrot set, framed in the diagram of orbits and attractors, to characterize the dynamics of the curves of the demand of daily electrical power, with the purpose of discovering other observations enabling the elevation of new theoretical approaches. The result shows a different method to evaluate the dynamics of the electric power demand curve, using fractal orbital diagrams. This method is a new contribution that extends universal knowledge about the dynamics of complex systems and fractal geometry. Finally, the reader is informed that the data series used in this article was used in a previous publication, but using a different fractal technique to describe its dynamics.

The influence of the global electric power system on terrestrial biodiversity

Given its total contribution to greenhouse gas emissions, the global electric power sector will be required to undergo a fundamental transformation over the next decades to limit anthropogenic climate change to below 2 °C. Implications for biodiversity of projected structural changes in the global electric power sector are rarely considered beyond those explicitly linked to climate change. This study uses a spatially explicit consumption-based accounting framework to examine the impact of demand for electric power on terrestrial vertebrate biodiversity globally. We demonstrate that the biodiversity footprint of the electric power sector is primarily within the territory where final demand for electric power resides, although there are substantial regional differences, with Europe displacing its biodiversity threat along international supply chains. The relationship between size of individual components of the electric power sector and threat to biodiversity indicates that a shift to nonfossil sources, such as solar and wind, could reduce pressures on biodiversity both within the territory where demand for power resides and along international supply chains. However, given the current levels of deployment of nonfossil sources of power, there is considerable uncertainty as to how the impacts of structural changes in the global electric power system will scale. Given the strong territorial link between demand and associated biodiversity impacts, development of strong national governance around the electric power sector represents a clear route to mitigate threats to biodiversity associated with efforts to decarbonize society over the coming century.

Transmission Investment and Expansion Planning for Systems With High-Temperature Superconducting Cables

Growing electric power demand in densely populated metropolitan areas presents problems due to the lack of availability of space to build transmission lines and due to short-circuit current limits. One of the solutions to meet the increasing demand is high-temperature superconducting (HTS) cables, which have a sufficiently high capacity and can be installed in the limited space of existing ducts. However, since the characteristics of low-impedance HTS cables result in higher system short-circuit levels, fault current limiter (FCL) HTS cables have been developed to solve the fault current problem without an upgrade of the rating of the existing circuit breakers, which is typically necessary when new power facilities in the power system are installed. This paper investigates the impacts of the installation of HTS cables on optimal transmission expansion planning (TEP). A three-stage TEP framework (identification, system analysis, and optimization) is proposed to select between plain HTS or FCL-HTS cables, and to determine the locations of new transmission expansion lines. The TEP optimization problem is formulated using mixed integer linear programming with the big-M method. The simulation results showed that the benefits of installing the FCL-HTS cable can justify their high installation costs.

ARIMAX Model for Short-Term Electrical Load Forecasting

The scope for ARIMAX approach to forecast short term load has gained a lot of significant importance.In this paper, ARIMAXmodel which is an extension of ARIMA model with exogenous variables is used for STLF on a time series data of Karnataka State Demand pattern. The forecasting accuracy of ARIMA model is enhanced by taking into consideration hour of the day and day of the week as exogenous variables for ARIMAX model. Forecasting performance is thus improved by considering these significant load dependent factors. The forecasted results indicate that the proposed model is more accurate according to mean absolute percentage error (MAPE) obtained during the testing period of the model. As the historical load data are available on the databases of the utility, researches in the areas of time series modelling are ongoing for electrical load forecasting. In the proposed paper real time demand data available on Karnataka Power Transmission Corporation Ltd. (KPTCL) website is taken to develop and test the proposedload forecasting model.The power utility system operational costs and its securitydepend on the load forecasting for next few hours. Regional load forecasting helps in the accurate management performance of generation of power plant. Today’s deregulated markets have great demand for prediction of electrical loads, required for generating companies. There has been tremendous growth in electric power demand and hence it is very much essentialfor the utility sectors to have theirdemand information in advance.

Investigations on High Temperature Low Sag (HTLS) Conductors

Electric power demand is growing at an exponential rate due to establishment of industries and economic growth in the country. Central electricity authority of India (CEA) has estimated per capita electricity consumption will increase at a rate of 6 percent per annum, this will increase the load on the transmission and distribution system. Limitations of Right of Way (ROW) has made it difficult to construct new lines, particularly in metropolitan and densely populated cities, hence high temperature low sag (HTLS) conductors are being used adopted, several projects in the country are being executed to overcome the problem of burdening of transmission/distribution system. HTLS conductors operate at 2–3 times higher ampacity and thermal rating, hence can be used for higher power transmission without upgrading the existing towers and infrastructure. The present investigation aims to understand and estimate the conductor temperature and ampacity dependent on different parameters like wind velocity, wind angle, emissivity and fault current level. The investigation highlights the dynamic thermal rating of HTLS conductor with change in wind velocity and angle, thermal performance of conductor during fault condition and thermal rating with emissivity, absorptivity and ambient temperature during flow of fault current is presented. A new experimental setup is established to investigate the performance of HTLS and Traction copper conductor in the laboratory, attempt has been made to study effect of magnetic fields and conduct EBSD analysis, some important conclusions drawn from the investigations are analyzed and presented.

Interline fuel cell (I-FC) system with dual-functional control capability

In this paper, a new system concept is presented for the grid connection of fuel cells. In conventional grid-connected systems, fuel cells ensure the generated power into a single electrical feeder and control the electrical-line through interfacing elements. In the proposed system, interline fuel cell (I-FC) system shares a common dc-dc converter tied fuel cell at the base of inverters and eliminates the additional fuel cell & dc-dc converter in a multi-feeder system. For this purpose, a fuel cell system is connected to multi-feeders through separate inverters, thereby sharing electrical power into the feeders and attenuating the harmonics at grid-side currents. In this direction, the proposed system presents an economical way for the mitigation of electrical problems for multi-feeders. In order to achieve the functional capabilities of I-FC system, dual-functional control is separately applied in the grid inverters. In the testing stage of I-FC, nonlinear loads in feeder I & feeder II create 31.29% and 27.61% total harmonic distortion (THD) at grid-side currents, respectively. With I-FC, the THD values are reduced to approximately 3% values in both feeders after the harmonic elimination capability. Also, I-FC allocates the active power to both feeders, and reduces the electrical power demand from the utility-grids. The evaluation results verify that I-FC system accomplishes the good performance to control power-sharing and attenuate the current harmonics at grid-side.

Cold load pickup model parameters based on measurements in distribution systems

The electric power demand after an outage can be significantly different from normal values. A major cause of this is the loss of statistic diversity in load devices that interact with some kind of storage. Examples are heating and cooling appliances as well as some applications of pumps and devices with integrated batteries. This phenomenon is known as cold load pickup (CLPU). Changes in load after an outage are of high relevance for investigations of power system restoration, especially active power control and balancing of generation and load. Besides the very fast inrush effects relevant for fast acting protection and short-term stability, long-term dynamics, thermal overload of equipment and active power balancing in the presence of uncontrolled distributed generation consider a time frame of minutes to hours. To predict CLPU from physical models, a lot of knowledge is required. Since this information is rarely available in the real-world applications, the authors investigate typical ranges of CLPU behaviour. The authors analyse measurement data from reconnections after real outages of medium voltage feeders in Germany and provide parameters for the exponential decay model of CLPU. The relevance of the application of the presented model for long-term stability studies is demonstrated by an example.

A NEW METHODOLOGY TO ANALYZE THE DYNAMIC OF DAILY POWER DEMAND WITH ATTRACTORS INTO THE MANDELBROT SET

The time series plot of electricity daily load demand is seasonal as shown by its regular repetitive pattern during the same period each year. Its behavior is determined by phase-space diagrams that are able to identify any of the following states of the series: fixed point, periodic, or chaotic. The first two deal with predictable systems. This paper focuses on presenting a new methodology to analyze the dynamics of the series in reference by using the curve formed by attractors that move in the complex plane over the Mandelbrot set according to the law dictated by the load curve. Because electrical power is a variable, it is also defined in the complex plane with the components of active power on the real axis and reactive power on the imaginary axis. Therefore, electrical power facilitates a new field of analysis in Mandelbrot fractal space. The obtained temporal curve confirms that the profile of the electric power demand is also mapped with the new fractal geometric space of the Mandelbrot set, thus providing a new contribution that extends knowledge about the dynamics of systems in fractal geometry.

Electrical Power Characteristics and Economic Analysis of Distributed Generation System Using Renewable Energy: Applied to Iron and Steel Plants

The intention of this paper is to respond to the increase in electric power demand and global environmental issues in iron and steel plants. In particular, the authors studied the characteristics of the power flow from a distributed generation (DG) system connected to the electrical power system of a steel plant. In addition, the authors carried out an economic analysis of the DG system by calculating the capital investment cost that could convert the profit of the DG into a certain profit. The research was conducted based on the power system configuration and basic data of a steel plant in operation in Korea. To analyze the unconnected DG of the power system, a transmission voltage target was set, and the voltage characteristics of 22.9 and 6.6 kV systems were analyzed. The authors analyzed the connected DG system in terms of the effect of link location, power factor, and output power by case. The authors also studied the power loss variation in the output power of a DG system. Various simulations with MATLAB software and NPV (Net Present Value) and IRR (Internal Rate of Return) methods were run in an economic analysis to compare the case of not introducing an energy storage system (ESS), and the case of introducing an ESS in terms of comprehensive energy utilization. The results of the economic analysis indicated that the scenario with ESS is more economically advantageous, resulting from the peak power reduction effect and the evasion cost due to the elimination of the power generation operation of the peak load. Developed countries have established best available technology (BAT) standards and developed related practices to apply them to industrial plants, actively preparing for environmental issues in the future. In Korea and in some other countries, the application of distributed generation in conjunction with the steel plant sector will be effective for improving energy efficiency and responding to environmental issues.

Optimization of Hybrid Renewable Energy System Using Homer

In this modern epoch Sustainable Energy Resources (SER) takes an upper hand in meeting the rise in power demand. Over the last few years, the increasing electrical power demand has prompted an incredible need for power from sustainable energy sources. The irradiation from solar, wind turbines are pondered as the main source of power generation since they supplement one another. For the general development of the economy, it is important that the agro-based economy would lead to the growth of the country. It is neither achievable nor affordable to dispatch power in the far away locales for a scarcely populated town. In this paper, the supplanting of energy sources with the sustainable power sources utilizing HOMER programming is performed. An independent sustainable power sources (ISPS) is used to meet the load and the cost is evaluated. The work is performed for real time data under different schemes like PV, wind and its combination. The optimization of operating cost under two scenario of using the ISPS (either PV or Wind) and using both PV & wind for real-time input taken from Sicud village in Philippines and Laboratory load data of SRMIST in India is performed. The comparison of the operating cost for the two region under two cases is executed and analyzed.

OTL-Classifier: Towards Imaging Processing for Future Unmanned Overhead Transmission Line Maintenance

The global demand for electric power has been greatly increasing because of industrial development and the change in people’s daily life. A lot of overhead transmission lines have been installed to provide reliable power across long distancess. Therefore, research on overhead transmission lines inspection is very important for preventing sudden wide-area outages. In this paper, we propose an Overhead Transmission Line Classifier (OTL-Classifier) based on deep learning techniques to classify images returned by future unmanned maintenance drones or robots. In the proposed model, a binary classifier based on Inception architecture is incorporated with an auxiliary marker algorithm based on ResNet and Faster-RCNN(Faster Regions with Convolutional Neural Networks features). The binary classifier defines images with foreign objects such as balloons and kites as abnormal class, regardless the type, size, and number of the foreign objects in a single image. The auxiliary marker algorithm marks foreign objects in abnormal images, in order to provide additional help for quick location of hidden foreign objects. Our OTL-Classifier model achieves a recall rate of 95% and an error rate of 10.7% in the normal mode, and a recall rate of 100% and an error rate of 35.9% in the Warning–Review mode.

Electricity Market Reform Support Through Enhanced Power Transaction Model: In Relation to Optimization in Applied Mathematics

Given that the electricity trading market has been specified, some of the growing demands include the establishment of long-term mechanisms, the improvement of electric power emergency mechanisms, and the strengthening of electric power demand side. Therefore, this study proposed a model for optimizing the planning of the monthly power generation. Specifically, the grey model algorithm was examined to discern some of the improvements that could be implemented. With the energy conservation development direction and the market considered, the research setting involved a regional power grid dispatch management system. A key parameter that was examined involved the monthly free energy conservation strategy and how the rate of short-term energy saving establishment could be improved. From the findings, it was evident that the proposed model for optimizing energy-saving power generation establishments poses beneficial effects in terms of power generation scheduling and improved resource allocation, hence meeting the electric power market reform needs.