Search Results (48)

Pumped Energy Storage Schemes play a critical role in electricity grid stability and energy security by storing excess electricity for later use. Pressure vessels in these systems are subject to rigorous inspection regimes because of their potential risks to safety and performance. Traditional Time-Based Inspection, while effective, can be costly and inefficient. This paper investigates the application of Risk-Based Inspection methodologies to optimise inspection planning, reduce costs, and maintain safety in Pumped Energy Storage Scheme pressure vessels. The study presents a structured framework for implementing Risk-Based Inspection, demonstrates the potential for cost savings through comparative analysis, and highlights its alignment with regulatory requirements in South Africa. Full article

High-order implicit-explicit (IMEX) schemes are effective for stiff parabolic partial differential equations when temporal regularity is compatible with the active multistep stencil. In moving-interface problems, a fixed Eulerian node may undergo a rapid transition as a diffuse interface crosses the grid, allowing stored multistep history to mix incompatible local regimes. This paper develops a conditional hybrid Deep Neural Galerkin-IMEX (DNG-IMEX) framework for this order-degradation mechanism. A classical IMEX-BDF3 backbone is retained on smooth intervals, whereas flagged event windows are treated by a localized neural/subcycle bridge followed by restart-consistent history reconstruction. The formulation separates the weak parabolic setting from the additional smoothness used for pointwise interface kinematics and proves a Sobolev-level transport estimate, a weak energy estimate, and a conditional propagation result under explicit flagged/restart defect bounds. Numerical tests on a manufactured Allen–Cahn benchmark show that event-aligned restarting suppresses the dominant history-contamination defect. A benchmark diagnostic realization localizes corrections with available event information and improves the baseline when event windows are resolved and the detector remains selective. Interface-thickness and cost tests indicate that sharper interfaces require stronger event resolution and that the present correction pipeline has non-negligible overhead. These findings support selective interface-aware enhancement of classical IMEX time integration. Full article

It is projected that, by 2030, the global stock of electric vehicles (EVs) will reach approximately 85 million units. When the capacity of EV batteries declines to 70–80% of their original performance, replacement becomes necessary, as the remaining capacity is inadequate to meet the operational requirements of automotive applications. Upon removal, these batteries retain significant material value and thus require proper recycling. However, their stored energy presents substantial safety risks, necessitating a controlled discharge process to mitigate potential hazards. This study presents the design and implementation of a system that integrates a boost converter with a single-phase grid-tied inverter to facilitate the safe transfer of energy from end-of-life (EoL) EV batteries to the electrical grid. The system was simulated in PLECS using a lithium-ion battery model and a non-ideal grid. The analysis shows that the system is stable and effective at transferring energy from the battery to the grid and heating the battery at the end of the process. This study identifies circuit operating conditions and control schemes that can enable the rapid, practical, and safe discharge of EV batteries without significant voltage relaxation. Full article

As a core support for the integration of new energy and smart grids, Vehicle-to-Grid (V2G) networks face a core contradiction between user privacy protection and transaction security traceability—a dilemma that is further exacerbated by issues such as the quantum computing vulnerability of traditional cryptography, cumbersome key management in stateful ring signatures, and conflicts between revocation mechanisms and privacy protection. To address these problems, this paper proposes a post-quantum revocable linkable ring signature scheme based on SPHINCS+, with the following core innovations: First, the scheme seamlessly integrates the pure hash-based architecture of SPHINCS+ with a stateless design, incorporating WOTS+, FORS, and XMSS technologies, which inherently resists quantum attacks and eliminates the need to track signature states, thus completely resolving the state management dilemma of traditional stateful schemes; second, the scheme introduces an innovative “real signature + pseudo-signature polynomially indistinguishable” mechanism, and by calibrating the authentication path structure and hash distribution of pseudo-signatures (satisfying the Kolmogorov–Smirnov test with $D\le 0.05$), it ensures signer anonymity and mitigates the potential risk of distinguishable pseudo-signatures; third, the scheme designs a KEK (Key Encryption Key)-sharded collaborative revocation mechanism, encrypting and storing the $(I,pk,RID)$ mapping table in fragmented form, with KEK split into $KE{K}_1$ (held by the Trusted Authority, TA) and $KE{K}_2$ (held by the regulatory node), with collaborative decryption by both parties required to locate malicious users, thereby resolving the core conflict of privacy leakage in traditional revocation mechanisms; fourth, the scheme generates forward-secure linkable tags based on one-way private key updates and one-time random factors, ensuring that past transactions cannot be traced even if the current private key is compromised; and fifth, the scheme adopts hash commitments instead of complex cryptographic commitments, simplifying computations while efficiently binding transaction amounts to signers—an approach consistent with the pure hash-based design philosophy of SPHINCS+. Security analysis demonstrates that the scheme satisfies the following six core properties: post-quantum security, unforgeability, anonymity, linkability, unframeability, and forward secrecy, thereby providing technical support for secure and anonymous payments in V2G networks in the quantum era. Full article

The Modular Multilevel Matrix Converter (M3C) has the potential to contribute to onshore grid frequency response by utilizing the electrostatic energy stored in its submodules. However, in the current offshore wind power domain, control schemes for M3C-based Low-Frequency AC transmission systems (M3C-LFACs) fail to effectively exploit the capacitor energy of M3C to provide adequate inertia support. Existing M3C controls are typically grid-following and thus suffer from stability issues under weak-grid conditions. To address this challenge, a dual-port grid-forming control strategy for M3C-LFAC systems is proposed, based on an energy synchronization loop. This approach enables phase-locked-loop-free synchronization between the M3C and the grid while establishing low-frequency link voltage vectors. Building on this foundation, an optimized energy utilization method for M3C total energy is introduced, featuring a two-stage preset curve to maximize the system’s inherent energy for frequency response. Under varying levels of grid load disturbances, the proposed scheme ensures that M3C-LFAC systems can provide optimal inertia support. Finally, simulation studies in MATLAB 2024b/Simulink validate the effectiveness and advantages of the proposed method. Full article

Synthetic inertia (SI) enables wind turbine generators (WTGs) to support frequency stability by releasing stored kinetic energy during disturbances. Existing grid-code requirements, such as those of Hydro-Québec TransÉnergie (HQT) and ENTSO-E/Nord Pool, improve the first frequency nadir but often aggravate a second frequency dip (SFD) or risk rotor over-deceleration (OD) when the boost magnitude is large. This paper proposes an enhanced SI requirement that retains the stepwise boost-and-hold structure but replaces the time-based ramp-down with a rotor-speed-dependent recovery, followed by a smooth transition back to maximum power point tracking (MPPT). The proposed scheme was validated using an electromagnetic transient model of the Unison U151 wind turbine (4.569 MW, inertia constant 9.68 s), designed for Korea’s low-wind conditions. Five case studies at wind speeds of 5 and 7 m/s with varying boost levels confirmed that all methods yield identical first nadirs for a given boost, but only the proposed approach consistently maintained a higher second nadir, stabilized rotor dynamics, and prevented repeated dips. These results demonstrate that rotor-speed-dependent SI requirements, when combined with high-inertia turbines, can enhance frequency stability while protecting turbine operation, offering practical guidance for future grid-code revisions. Full article

Transition to electric vehicles has accelerated in diverse consumer sectors all over the world. Electric School Buses (ESBs) are a particular area of interest due to their environmental and financial potential benefits, including Vehicle-to-Grid (V2G) synergies. Storing electricity in times of lower demand to supply the grid at optimal times can provide significant sustainability benefits, among them a reduction in new generation capacity and financial revenue for battery owners. ESBs, with their high-capacity batteries, have significant potential to supply the grid in V2G systems. There are more than half a million school buses in the US, with a wide geographical distribution, which have significant idle times during school days and holidays. This presents very attractive investment possibilities, providing school districts with additional revenue and supplying local communities with sustainable electricity at high-demand times. This study develops a framework to financially evaluate sustainability of ESB V2G schemes in the US. It applies data analytics, GIS, and Business Intelligence to integrate and assess publicly available data to provide stakeholders with decision-making tools in selecting optimal locations and operation times for these projects. Results indicate that revenue for these projects is significant in most schools, with some locations generating very high revenue potential. Geospatial analysis for most locations and time frames indicates very promising results, with schools potentially receiving significant income from these systems. The framework provides, therefore, relevant information for stakeholders to make sustainable decisions on the development of these projects. Full article

Traditional track-based inspection schemes for caged poultry houses face issues with vulnerable tracks and cumbersome maintenance, while existing rail-less alternatives lack robust, reliable path planners. This study proposes TSO-HA*-Net, a hybrid global path planner that combines TSO-HA* with topological planning, which allows the inspection vehicle to continuously traverse a predetermined trackless route within each poultry house and conduct house-to-house inspections. Initially, the spatiotemporally optimized Hybrid A* (TSO-HA*) is employed as the lower-level planner to efficiently construct a semi-structured topological network by integrating predefined inspection rules into the global grid map of the poultry houses. Subsequently, the Dijkstra’s algorithm is adopted to plan a smooth inspection route that aligns with the starting and ending poses, conforming to the network. TSO-HA* retains the smoothness of HA* paths while reducing both time and computational overhead, thereby enhancing speed and efficiency in network generation. Experimental results show that compared to LDP-MAP and A*-dis, utilizing the distance reference tree (DRT) for h₂ calculation, the total planning time of the TSO-HA* algorithm is reduced by 66.6% and 96.4%, respectively, and the stored nodes are reduced by 99.7% and 97.4%, respectively. The application of the collision template in TSO-HA* results in a minimum reduction of 4.0% in front-end planning time, and the prior collision detection further decreases planning time by an average of 19.1%. The TSO-HA*-Net algorithm achieves global topological planning in a mere 546.6 ms, thereby addressing the critical deficiency of a viable global planner for inspection vehicles in poultry houses. This study provides valuable case studies and algorithmic insights for similar inspection task. Full article

Nowadays, standalone microgrids that make use of renewable energy sources have gained great interest. They provide a viable solution for rural electrification and decrease the burden on the utility grid. However, because standalone microgrids are nonlinear and time-varying, controlling and managing their energy can be difficult. A fractional-order proportional integral (FOPI) controller was proposed in this study to enhance a standalone microgrid’s energy management and performance. An ultra-capacitor (UC) and a battery, called a hybrid energy storage scheme, were employed as the microgrid’s energy storage system. The microgrid was primarily powered by solar and wind power. To achieve optimal performance, the FOPI’s parameters were ideally generated using the gorilla troop optimization (GTO) technique. The FOPI controller’s performance was contrasted with a conventional PI controller in terms of variations in load power, wind speed, and solar insolation. The microgrid was modeled and simulated using MATLAB/Simulink software R2023a 23.1. The results indicate that, in comparison to the traditional PI controller, the proposed FOPI controller significantly improved the microgrid’s transient performance. The load voltage and frequency were maintained constant against the least amount of disturbance despite variations in wind speed, photovoltaic intensity, and load power. In contrast, the storage battery precisely stores and releases energy to counteract variations in wind and photovoltaic power. The outcomes validate that in the presence of the UC, the microgrid performance is improved. However, the improvement is very close to that gained when using the proposed controller without UC. Hence, the proposed controller can reduce the cost, weight, and space of the system. Moreover, a Hardware-in-the-Loop (HIL) emulator was implemented using a C2000™ microcontroller LaunchPad™ TMS320F28379D kit (Texas Instruments, Dallas, TX, USA) to evaluate the proposed system and validate the simulation results. Full article

Modular multilevel converters with non-sinusoidal ac voltage output can reduce cost and volume in medium-voltage-connected electric vehicle battery charging applications. The use of full-bridge submodules in such converters enables single-stage ac/ac voltage conversion, allowing a medium-voltage grid to be directly connected to a medium-frequency isolation transformer. The application of a square wave voltage at the medium-frequency transformer’s single-phase port enhances the converter’s efficiency and power density in comparison to a sinusoidal voltage. This paper presents the analysis and modelling of a modular multilevel converter, comparing its operation with sinusoidal and square wave output voltages. A single control scheme for both output voltage waveforms is proposed for the three-phase and single-phase ac currents, circulating currents, and the energy stored in the submodule capacitors. The control strategy of the three-phase and single-phase port currents is verified through simulation and experiments using a scaled-down prototype, thereby validating its suitability for high-power bidirectional battery chargers. Full article

Global warming, pollution, and increasing energy demand have compelled electrification of the transport sector. Electric vehicles are not only an attractive and cleaner mode of transport, but they also possess the capacity to offer flexible storage alternative based on bidirectional vehicle-to-grid schemes. Vehicle-to-grid or V2G technology permits electric vehicles’ batteries to store energy and discharge it back to the power grid during peak-load periods. However, the feasibility and economic viability of V2G is still a matter of concern and needs investigation. In this paper, the authors delved into the feasibility of V2G technology by analysing the real time-charging data of a V2G demonstration project named EV-elocity, located at the University of Nottingham campus in the UK. The authors analysed the charging data and trip-status data of two charging sites and put forward some insights regarding the feasibility of V2G and the behavioural traits of the vehicles. This paper will enlighten the research community regarding the feasibility and benefits of V2G in a real-world environment by analysing the charging/discharging and vehicle behaviour and reporting the opportunities and benefits of vehicle-to-grid technology. Full article

A large amount of high-value data are stored in smart grid data centers, but since the resource diversity of a single data center is limited, data sharing becomes especially important in conducting an effective data mining process. However, traditional data-sharing models often use centralized schemes without authentication of the shared objects, making it difficult to establish trust relationships and ensure data privacy. This makes it difficult to break through the problem of data islands. To solve the above problems, this paper proposes a blockchain-based data-sharing incentive model for edge smart grid scenarios. First, the model uses blockchain and proxy re-encryption technology to achieve the security and traceability of the smart grid data-sharing process. Secondly, the data-sharing incentive algorithm is designed using game theory to maximize the willingness of data owners to share data. Finally, the model in this paper is compared and analyzed with other existing data-sharing models, and the designed performance test shows that the scheme in this paper has significant advantages over the other literature schemes in terms of functionality and computational overhead, and the increase in costs is not significant, and the model can meet the requirements for large-scale data sharing in edge smart grid scenarios. Full article

Demand response (DR) has been studied widely in the smart grid literature, however, there is still a significant gap in approaches that address security, privacy, and robustness of settlement processes simultaneously. The need for security and robustness emerges as a vital property, as Internet of Things (IoT) devices become part of the smart grid; in the form of smart meters, home energy management systems (HEMSs), intelligent transformers, and so on. In this paper, we use energy blockchain to secure energy transactions among customers and the utility. In addition, we formulate a mixed-strategy stochastic game model to address uncertainties in DR contributions of agents and achieve optimal demand response decisions. This model utilizes the processing hardware of customers for block mining, stores customer DR agreements as distributed ledgers, and offers a smart contract and consensus algorithm for energy transaction validation. We use a real dataset of residential demand profiles and photovoltaic (PV) generation to validate the performance of the proposed scheme. The results show the impact of electric vehicle (EV) discharging and customer demand reduction on increasing the probability of successful block mining and improving customer profits. Moreover, the results demonstrate the security and robustness of our consensus algorithm for detecting malicious activities. Full article

To reduce carbon emissions in the atmosphere, the utilization of renewable energy sources has been on the rise. However, as their integration level increases, grid system operators require higher performance of the frequency response service for renewable energy sources, especially wind power generators (WPGs). Conventional frequency control schemes release kinetic energy depending on the fixed and adjustable gains in the system difference loop between the standard and current system frequency; however, these conventional schemes cannot provide frequency support outside of the rotor’s speed operating region. In this work, a frequency regulation support strategy employing a WPG and lithium-ion battery based on an adaptable power reference is implemented. This is accomplished by assigning different roles to the WPG and battery. As the primary frequency control support, the WPG uses a frequency deviation loop with adaptable gain which depends on the speed of the rotor and the difference in frequency. Additionally, to assist with the frequency control support, the battery operates based on its state-of-charge (SOC) and rotor speed of the WPG. For investigating the capability of the suggested technique, an IEEE 14-bus system is employed. Qualitative wake effect analysis is further presented in the study to determine the feasibility of the proposed approach which consists of the hybrid WPP–battery system for frequency regulation. The main limitations of this study and further research studies that can be performed in the future to improve the performance of the proposed technique are presented. The scenario study results show that the minimum frequency point during a synchronous generator trip obtains a higher value than conventional ones in the suggested strategy by releasing more stored energy from the WPG and the battery. Full article

The management of energy in distribution networks has been gathering attention in recent years. The simultaneous control of generation and demand is crucial for achieving energy savings and can further lower energy pricing. The work aims to develop a control scheme for a hybrid microgrid that can provide stability to the bus voltage and effectively manage the power flow. Solar energy is the current trend in renewable energy sources (RES). There is a surge in the installation of solar PV systems both on a large scale and on a small scale, such as rooftop PV systems. Installation of RES at residential premises has to be conducted with a proper power management scheme. The hybrid microgrid for this work consists of a PV system with a boost converter to extract maximum power, a DC-DC bi-directional converter to charge or discharge the hybrid energy-storing devices, and a three-phase AC-DC interlinking converter for exchange of energy with the utility grid. The control and power management scheme checks the voltage of each unit and maintains the power flow according to operating conditions. Disturbances are introduced in the form of load switching and irradiance variation to check the system performance. The system is tested on the MATLAB (R2021a) Simulink platform for varying its different modes of operations. An experimental set-up has been developed with hardware-in-the-loop to validate the simulation results. Full article