Transmission System Operators Research Articles

Multi‐Task Residential Short‐Term Load Prediction Based on Contrastive Learning

AbstractLoad forecasting is crucial for the operation and planning of electricity generation, transmission, and distribution. In the context of short‐term electricity load prediction for residential users, single‐task learning methods fail to consider the relationship among multiple residential users and have limited feature extraction capabilities for residential load data. It is challenging to obtain sufficient information from individual residential user load predictions, resulting in poor prediction performance. To address these issues, we propose a framework for multi‐task residential short‐term load prediction based on contrastive learning. Firstly, clustering techniques are used to select residential users with similar electricity consumption patterns. Secondly, contrastive learning is employed for pre‐training, extracting trend and seasonal feature representations of load sequences, thereby enhancing the feature extraction capability for residential load Feature. Lastly, a multi‐task learning prediction framework is utilized to learn shared information among multiple residential users' loads, enabling short‐term load prediction for multiple residences. The proposed load prediction framework has been implemented on two real‐world load data sets, and the experimental results demonstrate that it effectively reduces the prediction errors for residential load prediction. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

An Overview of Electricity Consumption in Europe: Models for Prediction of the Electricity Usage for Heating and Cooling

Although aggregate electricity consumption provides valuable information for market analysis, demand composition, including industrial, residential, illumination, and other uses, and special days, such as national or religious holidays and annual industrial shutdowns, differ for each country. This paper analyzes the hourly electricity consumption of European countries in the European Transmission System Operation for Electricity (ENTSO-E) grid from 2006 to 2018. We propose an outlier detection method to identify special days and a modulated Fourier Series Expansion model to determine the breakdown of industrial versus household consumption and heating versus cooling consumption. The proposed outlier detection method uses the time series for each hour and checks whether a day has more than a threshold number of hours with exceptional electricity consumption levels. The proposed demand prediction model has a 3% average error when electricity usage for heating is not dominant. It also allows country classification based on consumption patterns to efficiently manage regional or country-based electricity markets.

Load Flow Assignments’ Definition from Day-Ahead Electricity Market Interconnection Power Flows: A Study for Transmission Networks

The mass introduction of renewable energy sources (RESs) presents numerous challenges for transmission system operators (TSOs). The Italian TSO, Terna S.p.A., aims to assess the impact of inverter-based generation on system inertia, primary regulating energy and short-circuit power for the year 2030, characterized by a large penetration of these sources. The initial working point of the Italian transmission network has to be defined through load flow (LF) calculations before starting dynamical analyses and simulations of the power system. Terna 2030 development plan projections enable the estimation of active power generation and load for each hour of that year in each Italian market zone, as well as cross-zonal active power flows; this dataset differs from conventional LF assignments. Therefore, in order to set up a LF analysis for the characterization of the working point of the Italian transmission network, LF assignments have to be derived from the input dataset provided by Terna. For this purpose, this paper presents two methods for determining canonical LF assignments for each network bus, aligning with the available data. The methodologies are applied to a simplified model of the Italian network, but they are also valid for other transmission networks with similar topology and meet the future needs of TSOs. The methods are tested at selected hours, revealing that both approaches yield satisfactory results in terms of compliance with the hourly data provided.

Wind Power Forecasting With LSTM and Comparison With Different Machine Learning Algorithms: A Case Study of Southwestern Turkey

Wind is a renewable energy resource but its intermittent nature poses some issues for transmission system operators, wind farms, and the electricity market. To address these issues, wind power forecasting is crucial. In this study, the data were obtained from a turbine anemometer in the 1-year time horizon of 10 min for wind power forecasting. Models are designed with univariate long short-term memory, multivariate long short-term memory, multilayer perceptron (MLP), extreme gradient boosting (XGBOOST), convolutional neural networks (CNNs), long short-term memory, gated recurrent unit (GRU), and random forest (RF) algorithms. Outliers in the data are cleaned with the isolation forest algorithm. Hyperparameter optimization of the models, designed with machine learning algorithms for a selected month from each season (January, April, July, and November) was made with Bayesian optimization. The success of the models was measured by mean absolute error, root mean square error, and determination coefficient. Among the designed models, for January, April, and November, the multivariate long short-term memory model gave the most successful results with 0.926, 0.961, and 0.946 determination coefficient values, respectively. For July, the XGBOOST model provided the most successful result with 0.916 value of the determination coefficient

Phasor Measurement Unit Change-Point Detection of Frequency Hurst Exponent Anomaly With Time-to-Event

The objective of this paper is real-time detection of a change-point in the baseline distribution of the frequency signal generated by Phasor Measurement Units (PMUs) that could indicate potential for voltage collapse, false data injection, or other security threats. The alarm flags an anomaly event when the cumulative sum (CUSUM) of the log-likelihood departures of the Hurst exponent of the frequency from its baseline statistic exceeds a threshold set up as a compromise between the conflicting objectives of minimum detection delay and acceptable False Alarm Rate. As main theoretical contribution, an extra protection layer is developed that provides an estimate of the time to the alarm event, giving the Transmission System Operator (TSO) or an autonomous agent more time to deploy proactive measures to avoid large catastrophic system states. The proposed method is illustrated by a retrospective analysis of the 2012 Indian blackout that reveals that 10-12 minutes before the voltage collapse, a significant increase in the Hurst exponent of the frequency could have been detected. Conceptually, this shows that PMUs provide significant value towards ensuring autonomous cognition in the power grid by enabling the abnormal events to be fault-detected in an unsupervised fashion.

Work Domain Analysis of Electric Transmission Networks and Operation

Work Domain Analysis of Electric Transmission Networks and Operation

Reducing the effect of engine failure on the aerodynamic performance of the light transport aircraft model

Recently, aircraft engine manufacturers have shown increased interest in developing hybrid powerplants, which are a combination of gas turbine engines (GTE) with electric motor-generators. The use of the hybrid powerplant makes it possible to increase the fuel efficiency of an airplane, as well as to create new configurations with improved aerodynamic and thrust characteristics. The fuel efficiency improvement is achieved as a result of optimizing the powerplant operation mode to meet the cruising flight requirements, compensating insufficient power during the takeoff and go-around procedures by activating battery-powered electric motors. The creation of new configurations with improved performance can be ensured due to the synergetic effect of the propeller-airframe interaction. Successful flight tests of the hybrid powerplant prototypes in light aircraft configurations allow us to rely on their possible application in the future regarding the projects of new propeller-driven aircraft. The potential benefits of using new powerplants on local airlines can lead to both fuel savings and carbon emission reduction. Short-term maintaining a safe flight mode is also practical in case of one engine failure when using multiple power sources. The power, generated by an electric generator connected to the running engine, can be used both for the electric motor drive of the tip propellers and for rotating the thrust producer of the failed engine. The paper presents the study results of the critical engine failure effect on the aerodynamic performance of the light transport aircraft model obtained as under available electrical transmission as under non-available one between a running and a failed engine. Experimental studies were carried out in a low-speed wind tunnel T-102 TsAGI. The simulation of the electric transmission operation was carried out by setting the operation mode of two power-plant simulators corresponding to the half value of the load factor of one engine propeller Bo in the take-off mode.

Legal and ownership unbundling in the Turkish natural gas market: A comparative analysis

This study introduces a theoretical framework for the Turkish natural gas market based on the principles of game theory and industrial organization. It investigates the effects of the legal and ownership unbundling on consumer surplus, social welfare, and competition. The model considers a mixed oligopoly with a transmission system operator (TSO), a state-owned incumbent, and a private firm. The state-owned incumbent is assumed to maximize consumer surplus and its own profit, while the private firm is assumed to be profit-maximizing. Additionally, the state-owned incumbent is assumed to be less efficient than the private firm. The game consists of three stages. In the first two stages, the state-owned incumbent and the private firm sequentially choose contract sizes in the upstream market. In the last stage, a contract size-restricted Cournot game is played. The findings of the study suggest that legal unbundling appears to offer greater advantages for consumer surplus and social welfare compared to ownership unbundling, particularly when considering key factors such as third-party access, non-tariff discrimination, and import liberalization. The results indicate that adopting the role of a Stackelberg follower by the state-owned incumbent in the upstream market is advantageous in terms of consumer surplus, social welfare, and competition under both unbundling approaches.

Quasi-optimal domain decomposition method for neural network-based computation of the time-dependent Schrödinger equation

In this paper, we derive and analyze the performance of optimal/quasi-optimal Schwarz Waveform Relaxation (SWR) domain decomposition methods (DDM) for the time-dependent Schrödinger equation when implement with neural network-based Partial Differential Equations (PDE) solvers. Optimal SWR methods, which are based on Dirichlet-to-Neumann operators, are known to have a higher convergence rate than classical or optimized SWR methods. However, they are usually considered prohibitive due to their computational costs with standard PDE solvers. Thanks to Physics Informed Neural Network acceleration within the Schwarz waveform relaxation process and an efficient computation of Dirichlet-to-Neumann transmission operators, we demonstrate that optimal and quasi-optimal SWR methods can be performed almost as efficiently as classical or optimized SWR methods while maintaining a faster convergence rate. We present a few numerical examples to illustrate the performance and convergence of the proposed method.

Orthogonal beamforming technique for massive MIMO systems

AbstractBeamforming represents a pivotal technology in massive multiple-input multiple-output (MIMO) systems, as it facilitates the regulation of transmission and reception operations. Beamforming techniques’ categorization is based either on their hardware architecture or implementation strategy. This paper proposes an orthogonal beamforming technology founded on a specific implementation method that utilizes predetermined orthogonal beams to serve users. The suggested approach incorporates numerous orthogonal beams relying on a substantial number of antennas at the base station. The primary objective of this approach is to enhance the performance of massive MIMO systems by augmenting spectral efficiency and accommodating more users. The proposed beamforming approach is well suited for millimeter frequency bands. The purpose of this paper is to explore the suggested orthogonal beamforming technology. The concept of this approach is described at first and then followed by an evaluation of its efficacy for a single user through the allocation of orthogonal beams. The suggested approach is also examined in the context of multiuser systems, and the results are compared with the adaptive ZF beamforming technique. Furthermore, the paper presents solutions to the issues that may arise in multiuser systems, for example, ensuring that each orthogonal beam is assigned to only one user. The simulations conducted in this study demonstrate that the suggested approach outperforms the ZF technique in terms of both the spectral efficiency and the number of serviced users. Specifically, the suggested approach can enhance SE by approximately 40.6% over the ZF technique, and it can support up to double the number of users when compared to the ZF approach.

The climatological renewable energy deviation index (credi)

We propose an index to quantify and analyse the impact of climatological variability on the energy system at different timescales. We define the climatological renewable energy deviation index (credi) as the cumulative anomaly of a renewable resource with respect to its climate over a specific time period of interest. For this we introduce the smooth, yet physical, hourly rolling window climatology that captures the expected hourly to yearly behaviour of renewable resources. We analyse the presented index at decadal, annual and (sub-)seasonal timescales for a sample region and discuss scientific and practical implications. credi is meant as an analytical tool for researchers and stakeholders to help them quantify, understand, and explain, the impact of energy-meteorological variability on future energy system. Improved understanding translates to better assessments of how renewable resources, and the associated risks for energy security, may fare in current and future climatological settings. The practical use of the index is in resource planning. For example transmission system operators may be able to adjust short-term planning to reduce adequacy issues before they occur or combine the index with storyline event selection for improved assessments of climate change related risks.

Adaptive inter-area power oscillation damping from offshore wind farm and MMC-HVDC using deep reinforcement learning

The coordination of the offshore wind farm (OWF) and high-voltage direct current (HVDC) links to provide ancillary power oscillation damping (POD) services may become a mandatory requirement from the transmission system operators in the near future. However, the performances of the POD controllers (PODCs) are vulnerable to the power system uncertainties and random communication delays of the wide-area signals. To address these issues, this paper proposes the design of the coordinated PODCs by using the deep reinforcement learning (DRL) method. The DRL-based PODCs employ one of the state-of-the-art DRL algorithms, proximal policy optimization, which can learn to adapt to the system uncertainties and time-varying communication delays by interacting with the power system continuously. A detailed simulation model of an OWF connected to the IEEE-39 bus AC grid via the modular multilevel converter based HVDC link has been built as a simulation platform, and the efficacy of the proposed DRL-based PODCs has been validated across a broad spectrum of operating conditions, disturbances, and communication latency.

The boundary element method for acoustic transmission with nonconforming grids

Acoustic wave propagation through a homogeneous material embedded in an unbounded medium can be formulated as a boundary integral equation and accurately solved with the boundary element method. The computational efficiency deteriorates at high frequencies due to the increase in mesh size with a fixed number of elements per wavelength and also at high material contrasts due to the ill-conditioning of the linear system. This study presents the design of boundary element methods feasible for nonconforming surface meshes at the material interface. The nonconforming algorithm allows for independent grid generation, improves flexibility, and reduces the degrees of freedom. It works for different boundary integral formulations for Helmholtz transmission problems, operator preconditioning, and coupling with finite element solvers. The extensive numerical benchmarks at canonical configurations and an acoustic foam model confirm the significant improvements in computational efficiency when employing the nonconforming grid coupling in the boundary element method.

An angular stable ultra-broadband asymmetric transmission chiral metasurface with efficient linear-polarization conversion

Abstract In this paper, a chiral metasurface is presented to effectively attain an ultra-broadband operation of asymmetric transmission with highly efficient cross-polarization conversion. The efficiency of the asymmetric transmission operation in the frequency band ranging from 6.5 to 13 GHz is above 70%. Additionally, in the frequency range from 3.7 to 14 GHz, the cross-polarization conversion realizes greater than 90% polarization conversion ratio. Asymmetric transmission as well as cross-polarization conversion show angular stability against the incident angle of electromagnetic waves up to 45°. To validate the simulation results, the fabricated chiral metasurface is tested and compared with simulation results. The concepts of asymmetric transmission and linear-polarization conversion are demonstrated and physically explained through the distributions of surface currents over metallic layers. This anticipated work has significant applications in telecommunications and radar, as well as potential use in equipment designed for the manipulation of electromagnetic waves.

Cleaning up while Changing Gears: The Role of Battery Design, Fossil Fuel Power Plants, and Vehicle Policy for Reducing Emissions in the Transition to Electric Vehicles.

Plug-in electric vehicles (PEVs) can reduce air emissions when charged with clean power, but prior work estimated that in 2010, PEVs produced 2 to 3 times the consequential air emission externalities of gasoline vehicles in PJM (the largest US regional transmission operator, serving 65 million people) due largely to increased generation from coal-fired power plants to charge the vehicles. We investigate how this situation has changed since 2010, where we are now, and what the largest levers are for reducing PEV consequential life cycle emission externalities in the near future. We estimate that PEV emission externalities have dropped by 17% to 18% in PJM as natural gas replaced coal, but they will remain comparable to gasoline vehicle externalities in base case trajectories through at least 2035. Increased wind and solar power capacity is critical to achieving deep decarbonization in the long run, but through 2035 we estimate that it will primarily shift which fossil generators operate on the margin at times when PEVs charge and can even increase consequential PEV charging emissions in the near term. We find that the largest levers for reducing PEV emissions over the next decade are (1) shifting away from nickel-based batteries to lithium iron phosphate, (2) reducing emissions from fossil generators, and (3) revising vehicle fleet emission standards. While our numerical estimates are regionally specific, key findings apply to most power systems today, in which renewable generators typically produce as much output as possible, regardless of the load, while dispatchable fossil fuel generators respond to the changes in load.

Alignment of aFRR and mFRR prequalification process in Croatia with the target market design

Commission Regulation (EU) 2017/1485 of 2 August 2017 establishing a guideline on electricity transmission system operation defines a prequalification process as a process to verify the compliance of a reserve providing unit or a reserve providing group with the requirements set by the transmission system operator. Croatian Transmission System Operator Plc. (HOPS) carries out a prequalification process in order for (potential) ancillary service providers to prove their capability of providing ancillary services, which means that the prequalification process is a prerequisite for the provision of ancillary services. As part of the European Network of Transmission System Operators for Electricity, HOPS participates in the European implementation projects PICASSO and MARI, which aim is to establish a single European platform for aFRR and mFRR balancing services. Within the PICASSO and MARI projects, the technical characteristics of the products traded on unique European platforms were defined. This paper analyzes the difference between the requirements from the existing prequalification process rules and the technical requirements for products within the PICASSO and MARI projects, explores practice in Slovenia and Germany and suggests the required adoptions of aFRR and mFRR prequalification processes in Croatia.

THE PARTICIPATION OF RESIDENTIAL CONSUMERS IN ENERGY MARKETS THROUGH DEMAND RESPONSE

Abstract. The article considers the approach to the interaction of the transmission system operator with consumers - the demand management mechanism, as well as its role and place in the energy markets. The tools and experience of implementation of demand management are described. With the help of a natural experiment, the possibility and effectiveness of the participation of consumers with household storage hot water boilers in the balancing market was evaluated. Optimizing the participation of large numbers of consumers in energy markets is a challenging problem, especially for portfolios with thousands or millions of flexible resources. One of the aggregator's tasks is to transform the functionality of automation technologies, such as a consumer's "smart" home, into products that could be traded on energy markets. The task of optimization consists in the effective and timely management of a large number of flexible resources. A key feature of demand management is the sale of managed load on a par with generating capacity. This is explained by the fact that, from the point of view of the balance, in the energy system, one kWh not consumed equals one kWh produced. As a result, the financial benefits of managing consumer electricity demand are equivalent to the prices of balancing services and the provision of capacity reserves from other market participants. The sale of a demand-side management resource can be implemented through balancing market (BM) and ancillary service market (SMS) instruments, which use TSOs to balance the power system. Attracting additional participants in RDP and BR should stimulate competition and allow TSOs to meet their needs for auxiliary and balancing services, which will positively affect the reliability of the energy system and increase competition. In general, the level of provision of the power system with reserves depends on a wide range of factors, including: different hours of the day, weather conditions or trading strategies of market participants, etc. The optimal way to involve household consumers in responding to demand is to use the services of aggregators. But this does not mean the simple accumulation of a certain resulting power of consumers. The quantitative and qualitative composition of the aggregator's portfolio should ensure the execution of OSP commands in full, even in conditions of unavailability of part of the boilers or other aggregated units. For this, it is necessary to have a certain reserve of regulating power, for example, other boilers or energy storage units for the possibility of their prompt replacement (reconfiguration) within the portfolio. Demand management in the power system can effectively reduce the peak load of the system and delay the necessary capital investment in additional generating capacity and transmission lines. In addition, demand management facilitates the integration of renewable energy sources and reduces the costs of setting up, starting or shutting down thermal power units during peak load periods. Consumer participation in demand management requires bidirectional communication infrastructure, advanced metering, efficient economic tariffs and energy management algorithms. With the rise of smart grid technologies and automated demand response systems, demand management systems are a key element expected to provide a cost-effective alternative to traditional generation-side solutions to meet increasing demand for electricity during peak load or high prices. Demand management competes with auxiliary services provided by "traditional" providers - power plants and is used by TSOs to stabilize UES parameters when the power grid faces unforeseen situations, accordingly, the development of this sector is an important component of energy security.

The Devil in the details: The factors determining the selection of intrazonal congestion management methods across Europe

The European electricity market is becoming increasingly interconnected, raising questions about how intrazonal congestion management, typically governed by national regulations, interacts with the coupled cross-zonal markets. A major concern is the lack of information regarding intrazonal congestion management methods. This paper addresses this issue by examining different ways in which European transmission system operators (TSOs) use third-party resources to manage congestion in short-term electricity markets. We create a decision-tree-based classification to represent all identified congestion management methods and select three cases for comprehensive evaluation using predefined assessment criteria. While doing so, we identify a trade-off between efficiency and ease of implementation. The balance between these two factors is determined by the severity of the congestion. In a severely congested grid, locational signals are critical, requiring a better alignment between the network representation in the market clearing and the physical network constraints. When the congestion is less severe, TSOs can choose other congestion management methods based on factors such as the predictability of congestion and resource availability. These findings shed light on the complexities of congestion management in an integrated European market and can inform future policy decisions.

Performance analysis of the combination of a pitching wave surge energy converter and floating breakwaters

ABSTRACT Wave Energy Converters (WEC) captured the wave energy while Floating Breakwaters (FB) attenuated the wave energy to make a calm area for harbour activities. This study investigates the combination of a pitching Wave Energy Converter (WEC) and Floating Breakwater (FB) for simultaneous wave energy capture and wave attenuation in harbour areas. Three different configurations were analyzed in nine different hydrodynamic conditions to optimise the performance of both FB and WEC. The results show that the optimised combined device with rectangular draft has the most promising performance, with an average wave transmission operation of 38.8% and a captured power of 533.2 kW across all conditions. Longer arms of the device also lead to better performance. Additionally, wave steepness was found to be a significant factor in the performance of the combined device.

ANALYSIS OF THE POSSIBILITY OF APPLICATION OF HYDRAULIC MOTOR-WHEELS IN TRANSMISSIONS HIGH-SPEED TRACTORS

Goal. The purpose of the article is to assess the possibility of developing a hydraulic fluid power in accordance with the standard traction-speed characteristics of the KhTZ-17021 wheeled tractor with the of using gearless drives of the driving wheels. For this purpose, the calculation of the hydraulic fluid power of the wheeled tractor was performed when using the latest radial piston multi-cycle hydraulic motor-wheels with a wide range of rotation frequency and adjustment of the working volume. Research methodology. An analysis of the traction-speed characteristics of the KhTZ- 17021 wheeled tractor and, based on it, a review of modern high-torque radial-piston multi-cycle hydraulic motors from the point of view of meeting the characteristics of torque and rotation frequency with power limitations relative to the serial model in the full speed range of the tractor. The maximum values of the working volumes of the 4 driving hydraulic motor-wheels and the power supply pump of these hydraulic motors, the torque and pressure drop in the hydraulic drive are calculated, and the modes in which it is necessary to change the working volume of the hydraulic motors from the maximum to the minimum values to work out the traction-speed characteristics. A comparative analysis of radial-piston multi-cycle hydraulic motors was carried out, and for the hydromotor-wheel model MHP27 of the "Poclain Hydraulics" company, which was chosen for the study, the hydraulic principle diagrams were considered with the use of a hydraulic regulation system of four stages of the working volume in hydraulic motors, the use of combined parking and service brakes, as well as an anti-skid system using means of proportional electro-hydraulic automation. The results. High-torque hydraulic motor-wheels of the radial piston type were selected, which make it possible to ensure the operation of the tractor transmission without intermediate gearboxes between the hydraulic motors and wheel hubs, and the calculated value of the working volume of the axial piston pump, which ensures the operation of the tractor transmission in the full speed range. Based on the results of the calculations, it was established that the pressure in the hydraulic drive does not exceed 35 MPa, while values from 40 MPa to 50 MPa are achieved in modern pumps and hydraulic motors. The possibility of increasing the speed of the tractor from standard 35 km/h to promising 50 km/h is shown.