Electric Grid Research Articles

Structural characterisation for the synthesis of large‐scale combined electric–gas networks

AbstractIn this paper, the authors present a methodology for building realistic synthetic test cases to model combined electric and natural gas infrastructure networks. Because these networks are synthetic, that is, fictitious, they are able to be freely shared; hence, they serve to support research and development in the area of coupled‐infrastructure analysis with large‐scale realistic test cases that do not contain non‐public information. We anchor our process for building these synthetic networks in a structural characterisation of actual electric and natural gas networks. Supply and demand nodes are geographically placed, based on a combination of publicly available information from several sources and a clustering‐based method to match the right fraction of each node type, taking into account the intersection points between the electric and gas grids. Then the networks are connected with pipelines and transmission lines using a systematic graph construction method, validated against network properties including degree distribution, clustering, graph diameter, and degree of planarity, along with operational validation to ensure the simulated solution is realistic. The methodology is demonstrated by creating and validating a test case with 6717 electric buses and 2451 gas nodes.

Operational greenhouse gas emissions of various energy carriers for building heating

The decarbonisation of the building heating sector requires a shift from decentralised fossil fuel heating appliances to systems converting energy carriers with low greenhouse gas (GHG) emissions. However, for certain energy carriers, a considerable portion of GHG emissions arises upstream during production, processing and transportation, rather than during energy conversion. Accurately quantifying these indirect GHG emissions typically requires life cycle assessments, which are often resource-intensive and impractical during the early stages of energy system design. This study introduces operational GHG emissions as a pragmatic metric for the preliminary assessment of energy carrier environmental impact in building heating applications. These operational GHG emissions include both direct CO2 emissions and indirect CO2, CH4 and N2O emissions. Based on a comprehensive literature analysis, average estimates are proposed for the operational GHG emissions of various energy carriers within a European context, including natural gas, oil, coal and wood, as well as the average European and Belgian electricity grid, and hydrogen from various production methods. The findings underscore the significant contribution of indirect GHG emissions, as the selection of the energy carrier with the lowest environmental impact hinges on whether direct emissions alone or the broader operational GHG emissions are considered. By integrating operational GHG emissions into the early design stages of energy systems, stakeholders can make more informed decisions about which energy systems warrant further investigation, thereby facilitating more sustainable energy system development from the outset.

Synchronized Measurement of the Fundamental Voltage and Harmonic, Interharmonic, and Subharmonic Components of the Electrical Grid Using an Adaptive Kalman Filter

The effects of harmonics, interharmonics, and subharmonics on low-voltage distribution networks, leading to a deterioration in electrical power quality, have become more evident in recent years. The main harmonic sources are power electronic devices due to their implicit nonlinearity. Interharmonic and subharmonic components are mainly caused by a lack of synchronization between the grid frequency and the switching frequency of the power converters. This can be caused by asynchronous modulated devices, or more commonly by fluctuations in the fundamental grid frequency. Interharmonic currents cause interharmonic voltage distortions that affect grid-synchronized or frequency-dependent systems. The IEC-61000-4-7 proposes a general guide on harmonics, interharmonic measurements, and instrumentation in current supply systems. However, the techniques proposed in the standard are intended for measurement and do not enable a precise identification of the interharmonic components in a signal. This work proposes new definitions for the spectral energy aggrupation to improve signal component detection for the IEC standard. Furthermore, an adaptive Kalman filter algorithm is developed that enables the exact identification in real time of the frequency, amplitude, and phase of these components. The proposed system will become the basis for the implementation of a new range of measurement systems that provide improved accuracy and real-time operation. The work is supported by simulated results analysing various scenarios (including transients after changes in harmonic content in the grid voltage) that demonstrate the effectiveness of the proposed method.

Flexible operation of nuclear hybrid energy systems for load following and water desalination

Nuclear hybrid energy systems (NHES) have the potential to provide dependable and emission-free electricity to the grid while also increasing the flexibility and reliability of the electrical grid. Molten salt reactor (MSR) technology can provide consistent, carbon-free electricity while also increasing efficiency, security, and sustainability and reducing nuclear waste. This study investigates the integration of Molten Salt Reactors (MSR) and conventional Pressurized Water Reactors (PWR) with desalination technologies: Direct Contact Membrane Distillation (DCMD), Multi-Stage Flash Distillation (MSFD), and Reverse Osmosis (RO). Dynamic first-principles models were developed and tested using real grid data from the New York Independent System Operator. The results demonstrate that nuclear power is capable of flexibly responding to changing grid demand while simultaneously producing clean water, particularly during periods of low electricity demand. The MSR-RO system was found to be the most efficient in electricity generation and water production, and all hybrid systems reduced CO2 emissions by 356,000 to 682,000 tons annually. Economic analysis reveals that nuclear desalination technologies are cost-competitive with conventional systems, especially when paired with RO. These findings confirm the technical feasibility and environmental benefits of nuclear hybrid systems for sustainable electricity and water production.

Aggregate power flexibility of multi-energy systems supported by dynamic networks

The multi-energy system, encompassing electricity networks, district heating networks (DHNs), and hydrogen-enriched compressed natural gas (HCNG) networks, provides an alternative for promoting intermittent renewable energy accommodation and enhancing operational flexibility. This paper investigates the aggregate flexibility of the multi-energy system based on dynamic network models and admissible power fluctuation regions of decomposed subsystems. The dynamic processes within HCNG networks/DHNs are analyzed, and the inner-box method is employed to approximately quantify the individual flexibility of the dynamic networks. Furthermore, the optimal dispatchable regions of decomposed subsystems, accounting for internal gas/heating load uncertainties, are evaluated based on distributionally robust optimization. Through distribution-level power aggregation, the flexibility of the multi-energy system is quantified utilizing geometric methods. Numerical results on two test systems verify the effectiveness of the proposed methodology.

A novel energy management of public charging stations using attention-based deep learning model

Electricity grids are complex systems that must balance the supply and demand of electricity in real-time. However, with the increasing adoption of electric vehicles (EVs), managing the grid’s stability has become more challenging. EV charging can cause spikes in electricity demand, leading to peak demand periods that strain the power grid’s infrastructure. With the help of load forecasting, this effect on the grid can be mitigated by predicting the charging demand of electric vehicles in advance. This will help utilities adjust their energy supply in real-time, ensuring enough energy is available to meet demand, and preventing overloads or under utilization of the grid. Moreover, the EV charging demand is influenced by a wide range of factors, including charging station locations, weather, and time of day. Therefore, advanced deep learning models are required to learn these complex relationships and identify patterns in EV charging demand, enabling utilities to make more informed decisions. In this research, an attention-based deep learning approach is proposed for more accurate prediction of EV load demand. This novel approach integrates attention mechanisms with traditional deep learning models like LSTM and GRU, allowing the model to dynamically weight the importance of different features and focus on the most relevant information. The outcomes are compared to conventional deep learning and machine learning algorithms. To test the efficacy of the proposed framework, an actual ACN dataset for public EV charging stations is utilized.

Optimal control of a doubly fed induction generator of a wind turbine in cooperation with weak and rigid grids

In this article a control method for a rotor side converter (RSC) of a doubly fed induction generator of a wind turbine is developed. The doubly-fed induction generator (DFIG) system of a wind energy power plant that improves grid symmetrization was applied. The issue of optimal control was treated as an extended linear quadratic regulator (ELQR) having an extra set of exogenous inputs, which are source voltages of the electric grid. No additional knowledge of equations modelling the exogenous inputs was assumed. The proposed method is much more efficient than the currently available linear quadratic control methods. The control objective for a weak grid was to maintain the given value of the voltage module on load terminals and the given value of active power transferred from the stator’s winding. First harmonic components of relevant waveforms were used for this purpose. This task also required the DFIG system to provide reactive power to the grid. In the case of a rigid grid, this reactive power would be too high. Therefore, in this case, it was assumed that the system would supply only part of the required active and reactive power, based on its capabilities. It was required that the voltage and current ratings of the system, mainly the DFIG, were not exceeded. Therefore, the parameters of the network in these difficult failure cases were corrected only partially. The behaviour of the grid in the conditions of failure, as well as the return to the steady state after failure disappearance, were studied.

AOBL-IPACO: A novel and optimized algorithm to mitigate losses in electrical grid systems

AOBL-IPACO: A novel and optimized algorithm to mitigate losses in electrical grid systems

Оптимизация потребления сети MicroGrid с учетом потребностей на электроэнергию

Electricity grid is a product of urbanization expansion and rapid development of various infrastructures worldwide and over the past centuries. Although power companies are located in diverse regions, they typically use the same technologies to generate and distribute electricity. Proper implementation of the demand response (DR) program should be provided with some equipment to make subscribers aware of electricity price at any time and accordingly provide a proper response to the grid to reduce costs. This, in turn, reduces demand during peak hours. The intelligent grid, using the two-way communication network and the transmission of information to subscribers, and an advanced metering network provide a good structure for fully implementing DR programs. The present study applies a demand response economic model to implement DRs. The model uses price elasticity of demand, which provides subscribers a more precise consumption behavior regarding the factors influencing demand (e.g., electricity prices, bonuses, and fines). Applying the model to the microgrid, the operating cost significantly decreases in both operating modes.

Optimization of monitoring systems power cable lines

RELEVANCE. The length and complexity of the geography of medium voltage cable lines is at a high level. Such lines extend underground, on supports in the air. In order to constantly maintain the reliability of city power supply at a high level, any interruptions and accidents should be promptly corrected.TARGET. The main goal of the work is to develop the theory of medium voltage CL research, to practically and theoretically substantiate the search for the most convenient and effective installation for CL diagnostics, to study and develop possible modifications of CL diagnostic installations.METHODS. A variant of CL diagnostics based on the CPDA-60 installation is proposed, which makes it possible to find and localize the places where defects occur in the insulation based on the measurement and analysis of partial discharges (PD). Suitable for insulation monitoring in all types of high voltage cables. The CPDA installation can be used when testing new cable lines being put into operation, and to analyze the condition of old cables in operation.RESULTS. Cable lines require an integrated approach to diagnostics and monitoring, since the reliability of modern authentication systems for the generation and distribution of electricity is largely determined by the electrical reliability of electrical equipment. Technical diagnostics of equipment is a key link, the quality of which determines the efficiency of the processes of organizing production activities, strategic planning and renovation of electric grid assets.CONCLUSION. The study and analysis of the presented data and research allows us to form a conclusion regarding the method of measuring and localizing partial discharges (PD) in power cable lines (CL) using the Online Wire Testing System (OWTS) diagnostic system. The OWTS system allows real-time measurements without interrupting cable lines, making it especially valuable to the energy industry. Thanks to the introduction of advanced technologies and signal processing algorithms, the method has high accuracy and sensitivity to minimal manifestations of private discharges, which allows not only to detect, but also to accurately localize the location of defects in the insulation. The use of this method can significantly increase the service life of power cables, reduce the likelihood of sudden accidents and, as a result, reduce the cost of repair and maintenance of electrical power equipment. Ultimately, improvements in diagnostic and monitoring techniques, including the method of measuring and localizing PD in power lines using OWTS, represent a significant step towards improving the reliability and safety of electrical power systems. This will not only reduce operating costs, but also ensure uninterrupted and high-quality power supply to consumers.

Co-Design of a Wind–Hydrogen System: The Effect of Varying Wind Turbine Types on Techno-Economic Parameters

Green hydrogen is crucial for achieving climate neutrality and replacing fossil fuels in processes that are hard to electrify. Wind farms producing electricity and hydrogen can help mitigate stress on electricity grids and enable new markets for operators. While optimizing wind farms for electricity production is well-established, optimizing combined wind–hydrogen systems is a relatively new research field. This study examines the potential profit of wind–hydrogen systems by conducting a case study of an onshore wind farm near the North Sea. Varying turbine types from high wind-speed turbines (with high annual energy production) to low wind-speed turbines (with high full-load hours) are examined. Findings indicate that in a combined hydrogen system, the low wind-speed turbines, which are sub-optimal for mere electricity production, yield lower levelized costs of hydrogen at a higher hydrogen production. Although high wind-speed turbines generate higher profits under current market conditions, at high hydrogen prices and low electricity prices, low wind-speed turbines can yield higher total profit at this site. Therefore, an integrated optimization approach of wind–hydrogen systems can, in certain cases, lead to better results compared to an isolated, sequential optimization of each individual system.

Feasibility of upcycling red mud for low-CO2 cement via calcination: A comparative study with FA and GGBFS based in China

This study examines the feasibility of developing low-CO2 cement using calcined red mud (RM) and explores positive scenarios that simultaneously attain technical, environmental, and economic benefits in reference to conventional fly ash (FA) and ground granulated blast furnace slag (GGBFS) cements. Based on the variables of RM's content and calcination temperature, we investigated the fresh properties (paste rheology and mortar flowability), strength development, microstructure, embodied CO2 emissions, and cost of the RM-blended cement. The results show that there was an optimal range of RM's calcination temperature (400–600 °C) that improved the cement paste viscosity while attaining a higher strength than that of FA cement. Considering the cradle-to-gate CO2 emissions and cost of cement production, the optimal cement composition is comprised of up to 30% RM calcined at 600 °C, where the cement cost is lowered by 19.3% compared to the FA reference having a comparable CO2 footprint. According to the geographical analysis, the calcined RM shows minimal advantages over GGBFS but could substitute FA as a cleaner, cheaper, and more reactive supplementary cementitious material in regions where electricity grid is dominated by clean energy. Therefore, RM offers a plausible solution to future low-CO2 cement in light of the increasing shortage of FA led by the declining use of coal-powered electricity.

Sensor Fusion-Based Pulsed Controller for Low Power Solar-Charged Batteries with Experimental Tests: NiMH Battery as a Case Study

Solar energy is considered the major source of clean and ubiquitous renewable energy available on various scales in electric grids. In addition, solar energy is harnessed in various electronic devices to charge the batteries and power electronic equipment. Due to its ubiquitous nature, the corresponding market for solar-charged small-scale batteries is growing fast. The most important part to make the technology feasible is a portable battery charger and the associated controllers to automate battery charging. The charger should consider the case of charging to be convenient for the user and minimize battery degradation. However, the issue of slow charging and premature battery life loss plagues current industry standards or innovative battery technologies. In this paper, a new pulse charging technique is proposed that obviates battery deterioration and minimizes the overall charging loss. The solar-powered battery charger is prototyped and executed as a practical, versatile, and compact photovoltaic charge controller at cut rates. With the aid of sensor fusion, the charge controller is disconnected and reconnects the battery during battery overcharging and deep discharging conditions using sensors with relays. The laboratory model is tested using a less expensive PV panel, battery, and digital signal processor (DSP) controller. The charging behavior of the solar-powered PWM charge controller is studied compared with that of the constant voltage–constant current (CV–CC) method. The proposed method is pertinent for minimizing energy issues in impoverished places at a reasonable price.

Numerical study of a hybrid system of solar panels, a diesel generator, and a wind turbine using a battery system

This paper gives an overall quantitative analysis of a hybrid renewable energy system (HRES) incorporating solar photovoltaic system, wind system, diesel generator and battery storage system. The system is aimed at coordination the management of the energy resources for providing the off-grid or remote facilities. The best intervention is thus to increase the consumption of renewable energy sources to minimize the reliance on diesel generators. The findings show that the hybrid system is capable of supplying different levels of power, which is pumped from the solar PV panels at maximum of 30.38 kW for the photovoltaic system at maximum solar intensity, and the wind power system to a maximum of 3213 kW of power generation under standard wind potential. The diesel generator serves a backup power source, which ranges from 91.24 kW and 864 at a rate of 250 kW during high activity and 5 kW during high-demand periods. Battery storage integration has a crucial part in matching the short-term supply-demand imbalance problem. The study suggests that the hybrid system reduces diesel use, emissions, and improves energy sustainability making the system a worthy proposition for remote areas. The findings therefore affirm the use of hybrid systems in off grid electrification since they operate economically and are eco-friendly.

Last mile delivery with drones: A carbon emissions comparison

The development and potential adoption of drones or unmanned aerial vehicles as delivery vehicles creates incredible opportunities and unique challenges for last mile delivery. This research first presents a last mile delivery fleet model with drones that can be further modified and expanded over time. The model shows the optimal number of drones needed based on deterministic or stochastic demand using both traditional charging and battery swapping. The research then compares the carbon emissions of four delivery modes: traditional internal combustion delivery vehicles, all-electric vehicles, plug-in hybrids, and drones within the context of last mile delivery. Findings reveal that the breakdown of carbon emissions by delivery modality depends on parameter assumptions, ambient temperature, delivery radius, electric grid pollution rate, and number of customers.

Entangled Mathematics as a Tool of Reasoning in the Mid-Twentieth-Century UK Electricity Industry

In the mid-twentieth century, the identity of those who oversaw the UK electricity grid tentatively and slowly began to shift from those who joined the electricity industry directly from secondary school to a university-educated elite with a higher level of technical education. At the same time, electricity infrastructure became increasingly centralised, leading to the creation of a national grid in 1938, meaning that control of electricity became concentrated in the hands of an ever-smaller group and increasing the stakes in debates over strategy. By using the case studies of power engineer Paul Schiller and mathematician Maurice Davies, this paper traces how the boundaries of what mathematics could or could not be used for were renegotiated between factions within the UK electricity industry. Schiller unsuccessfully attempted to use mathematics, including the authority of academic mathematicians, to reinforce controversial arguments about the strategic direction of the industry in the 1940s. Such arguments failed to resonate with a class of, as Schiller put it, “practical men” that still held considerable influence. Davies on the other hand was employed by the industry in the 1950s to improve efficiency, and was able to implement lasting measures in this effort by using the weather to forecast electricity demand, and successfully defended the usefulness of his work in the 1970s against colleagues who felt that forecasting could be done better with mathematical models without weather inputs. The contrast between these two stories shows how the influence of mathematical thinking was contingent upon existing power dynamics, and reinforce how the history of mathematics should be socially embedded.

Forecasting solar irradiance for the strategic integration of hybrid hydro and solar photovoltaic systems in rural Indian regions

ABSTRACT Conversion of the conventional electrical grid into a smart and sustainable grid involves several considerations. The primary factors, however, are renewable energy penetration, associated storage systems, and energy generation costs. This research endeavors to conduct a thorough survey and analysis of the solar irradiance on various hydropower locations in India, including Run-of-River (RoR), Run-of-River with Pondage (RoRP), Reservoir Storage (S), Multi-Purpose Storage (MP) and Pumped Storage Systems (PSS). The hydroelectric projects in rural Indian regions have been the subject of the proposed case study. As a preliminary study, the probabilistic variables like minimum, maximum, and mean solar irradiance are calculated for 252 High-Scale Hydropower Plant locations (HSHPs) using the past 40 years day ahead solar radiation data to identify the high-irradiance hydropower plant location in each state of India. This study concludes that the maximum mean solar irradiance location in each state as these sites are well suited for hybrid PV-hydro systems. The identified high-irradiance locations 40 years day ahead data sets are analyzed employing 8 machine learning models and 2 deep learning models. This analysis aims to forecast solar irradiance, serving as a crucial foundation for the initial phase of the implementation of hybrid PV-hydro.

Molten Salt Modulation of Potassium-Nitrogen-Carbon for the Breaking Kinetics Bottleneck of Photocatalytic Overall Water Splitting and Environmental Impact Reduction.

Sluggish interfacial water dissociation and the O2 evolution reaction (OER) kinetics are the main obstacles that limit the photocatalytic overall water-splitting performance. A molten salt modulation of potassium-nitrogen-carbon is herein demonstrated as the formation of highly crystalline potassium-doped poly(triazine imide) (KPTI). The in situ X-ray diffraction patterns and theoretical calculation show that the KCl melt can significantly reduce the free energy for the polycondensation of triazine building blocks owing to the formation of a kinetically stable KPTI. Benefiting from the presence of potassium-carbon-nitrogen moiety, the catalyst not only weakens the excitonic confinement to improve the separation efficiency of photogenerated charge carriers but also enhances the stability of carbon sites by suppressing the undesired C═O formation. Moreover, KPTI accelerates water dissociation by forming interfacial K·H2O clusters with an ordered structure, which supplies sufficient protons for the H2 evolution reaction and lowers the energy barrier to enhance the kinetics of OER. Therefore, a stable photocatalytic overall water-splitting performance can be achieved over KPTI with a stoichiometric generation of products (H2 and O2). Life cycle assessment shows that a carbon-neutral scenario can be achieved on KPTI production in the near term with an increase in green power in the electricity grid.

Analysis of the efficiency of a Solar Photovoltaic Power Plant linked to the electrical grid

The growing need for energy in emerging nations gives rise to apprehensions over energy security, so underscoring the criticality of harnessing the potential of renewable resources. Empirical evidence has demonstrated that photovoltaic systems integrated into the network are the optimal options for large-scale renewable energy. The analysis of the performance of these network-connected centrals can enhance the design, operation, and maintenance of new systems. The commissioning of a 12 MW photovoltaic solar power plant in Sidi Bel Abbès, located in the Dhaya region, has established it as one of the largest solar power plants in Algeria. The site yields a mean solar radiation of 5.21 kilowatt-hours per square metre per day and an average yearly temperature of 18.9 degrees Celsius. The present work provides an analysis of the yearly performance and conceptual aspects of the photovoltaic central unit. We compare the performance outcomes of the power plant with the simulated values generated by the SolarGis PvPlanner program. Analysis of real-world performance in relation to simulations allows for the detection of inconsistencies and the enhancement of future initiatives. SolarGis PvPlanner is an essential modelling program for accurately forecasting performance and effectively strategising solar projects, therefore guaranteeing sustainable and dependable energy for the future.

Estimation of the Effect of Electric Vehicles on the Aging of Distribution Transformers Using Fuzzy Logic

Depending on industrialization and technological advancements worldwide, the demand for electrical energy, recognized as clean and dependable energy, is on the rise. Presently, electric energy consumption has notably increased alongside the rise in Electric Vehicles (EVs). The surge in EVs necessitates a thorough examination of the situation, anticipating the widespread adoption of Electric Vehicle Fast Charging Stations (EVFCS) in the near future and the subsequent escalation of their adverse impact on the grid. To mitigate these negative effects on the grid, proactive measures are essential. EVs function as capacitive loads due to their battery composition, and the harmonics produced during their grid connection detrimentally affect the quality of grid electricity, leading to constraints. Furthermore, the escalating EVFCS loads resulting from the rapid growth in EV numbers distribute the burden on distribution networks, posing a threat to network adequacy and reliability. Therefore, integrating EVFCS with distribution and generation units to minimize overloading, additional losses, and voltage fluctuations in the grid will enhance the efficiency of both systems. In addition, each EVFCS is only connected to the distribution transformer assigned to it or to the distribution transformers considered suitable in the city. Depending on the current drawn by one or more EVFCS linked to the feeder of each transformer, it can lead to overloading in transformers and chemical changes in windings and oils, resulting in the aging of transformers. In this context, a FL-based estimation is conducted to assess the impact of EVs' charging loads on transformer aging. The FL method utilizes transformer current load, EVFCS load, transformer temperature, and harmonic power quality data. The data utilized are derived from statistical information about a local distribution network and measured values from a feeder, and the aging effects on EVFCS distribution transformers are examined.