International Journal of Electrical Power and Energy Systems

Abstract: The Russia–Ukraine conflict and subsequent European Union sanctions have reshaped Europe’s energy landscape, transforming energy from a predominantly economic commodity into a central instrument of interstate competition and strategic bargaining. Situated at the intersection of Russia’s traditional sphere of influence and the eastward expansion of the European Union and NATO, Central and Eastern Europe has long constituted a key arena in which Moscow has sought to project influence through energy relations. Existing studies often treat Russian energy assistance in broad and ambiguous terms, thereby overlooking such key dimensions as non-market concessions, political conditionality, and state-led coordination. Drawing on a state-interest perspective and combining historical analysis with contemporary evidence, this article systematically examines the mechanisms through which Russia has structured and utilized energy relations in Central and Eastern Europe. It traces the continuities and transformations from Soviet-era energy arrangements to contemporary Russian practices, arguing that energy has consistently served as a key instrument for maintaining security buffers, extending regional influence, and securing economic returns. However, the mode of engagement has shifted from planned and institutionalized subsidy-based arrangements toward more conditional and flexible practices increasingly coordinated through state-owned enterprises. Based on Russia’s differentiated strategic interests in Central and Eastern Europe, the article develops a threefold typology of partner states: “exceptional partners,” “traditional partners,” and “frontier partners.” Through case studies of Hungary, Serbia, and Moldova, it demonstrates how Russia adopts differentiated energy strategies according to the strategic position of each partner state. These include a pattern of “binding and exchange” toward exceptional partners, “redistribution and binding” toward traditional partners, and … Read More

Abstract: In industrial intelligent operation and maintenance, the bearing fault signals, after dimensionality reduction through manifold learning, tend to exhibit discontinuous "fragmented" characteristics, making it difficult to depict the continuous evolution pattern of the fault. Moreover, the absence of intermediate state samples can easily lead to diagnostic errors. Therefore, this paper proposes a fault evolution trajectory reconstruction and manifold interpolation method based on parallel transport mechanism (TR-MIPT). This method utilizes local principal component analysis to construct the manifold topology, and generates pseudo-time degradation sequences based on geodesic metric; through tangent space estimation, orthogonal Procrustes alignment and discrete Riemannian connection, it realizes the distortion-free transmission of evolution gradients across coordinate systems; and combines local normal curvature and second-order geometric retract mapping to generate virtual samples and continuous evolution trajectories. Experimental results on the datasets from Case Western Reserve University and Northeast Petroleum University show that TR-MIPT can effectively reconstruct the degradation path, reduce the reconstruction error of intermediate states, and improve the diagnostic accuracy for small sample sizes and unseen intermediate-state faults. Read More

Abstract: Multivariate, multi-step power load forecasting represents a classic complex time series modeling challenge, with its core difficulty lying in simultaneously capturing long-term dependencies and local non-stationary fluctuations. In this paper, the calculations of MSE and MAE are performed using standardized data scales. Consequently, the experimental results presented in subsequent chapters represent dimensionless errors on a standardized scale, rather than absolute errors measured in physical units such as megawatts. Thus, subtle numerical differences among models under this evaluation protocol remain clearly comparable. Read More

Abstract: Under the context of energy structure transition and rapid advancement in power electronics, DC-DC converters, as key interface circuits for efficient power conversion and stable power supply, have become core components in modern power systems. Among various DC-DC converter topologies, the CLLC resonant converter features high power density and excellent galvanic isolation. Its topology typically integrates a high-frequency transformer for energy transfer, which not only provides electrical isolation between input and output but also reduces the size of magnetic components by increasing the switching frequency, thereby enhancing system power density. However, parameter design of the CLLC resonant converter remains challenging, requiring a trade-off between gain flatness and soft-switching range in bidirectional operation, coordination of the complex coupling among multiple resonant elements and parasitic parameters, and satisfaction of frequency regulation and efficiency optimization under wide input/output voltage ranges-constraints that are numerous and mutually restrictive. During the control process, the system suffers from long settling time and slow dynamic response. To address these issues, this paper first introduces the topology of the CLLC resonant converter. In view of the difficulties in parameter design, the fundamental harmonic analysis (FHA) method is adopted to design the parameters of the CLLC resonant converter. Combined with the control strategy, a prototype design method for the CLLC converter is completed. Read More

Abstract: In high-altitude areas, resources are abundant and energy consumption is decentralized, and the energy system has not achieved interconnection. Hydrogen energy, as a clean energy source, can fully utilize the resources in high-altitude areas and achieve large-scale utilization of energy and chemicals, cross-time and regional transportation, and integration of various energy sources. Based on this, this paper constructs a multi-energy complementary system including electricity, heat, oxygen, and hydrogen, focusing on multi-path collaborative improvement of hydrogen and oxygen production, full utilization of photothermal resources, and enhancing system economic efficiency. It proposes an innovative operation framework for a photothermal-biomass combined hydrogen production plant. By integrating CO2 electrolysis oxygen circulation technology and photovoltaic green hydrogen auxiliary mechanism, a photothermal-biomass collaborative hydrogen production system is constructed. Firstly, a system mathematical model is built and chemical simulation analysis is conducted to verify the feasibility of the hydrogen production route. Secondly, the energy/energy efficiency of the hydrogen production system is analyzed from the perspectives of hydrogen/oxygen production rate and energy/energy efficiency. Finally, economic analysis is conducted to calculate the levelized hydrogen production cost to verify economic feasibility. Read More

Abstract: This paper focuses on the application of the electronic and electrical industry in the field of new energy, and comprehensively analyzes its key role in the development of the new energy industry. By describing the current development status of the new energy industry, this paper introduces in detail the application of the electronic and electrical industry in new energy power generation systems such as solar energy, wind energy, and hydropower, as well as battery energy storage, power transmission and distribution. This paper analyzes the technological innovation and efficiency improvement brought by electronic and electrical technology to the field of new energy. It aims to reveal the important significance of the deep integration of the electronic and electrical industry with the field of new energy, provide theoretical reference and practical guidance for the development of related industries, and promote the development of the new energy industry in an efficient and sustainable direction. Read More

Abstract: The precise determination of the State of Charge is crucial for Lithium Iron Phosphate batteries, yet it continues to present significant challenges. These difficulties primarily stem from the batteries' notably flat voltage profile, considerable hysteresis effects, and their high sensitivity to thermal fluctuations and aging processes. This review systematically analyzes two dominant SOC estimation methodologies: purely data-driven models and physical-data-driven hybrid models. Data-driven approaches (e.g., DNN, LSTM) excel at capturing complex nonlinearities but lack interpretability and require substantial data. Hybrid models, combining equivalent circuit models with state estimators like Kalman filters, offer a balance of physical insight and computational efficiency, yet their accuracy often depends on offline calibration. The analysis concludes that future advancements hinge on developing online adaptive algorithms and deeply integrated hybrid strategies to enhance robustness and generalization across diverse real-world operating conditions. Read More

Abstract: To address the industry challenges of mismatched power output from gas generators and dynamic downhole load demand in drilling operations, along with the lack of scientific configuration basis for the coordinated operation of energy storage systems and traditional power generation equipment, this study conducts an in-depth optimization study on a hybrid gas-energy storage power supply system using a 50DB drilling rig as the specific research object. Historical load power data of the rig during typical operating cycles were systematically collected and analyzed. Based on this, a cost optimization model for the coordinated gas-energy storage power supply was developed, aiming to minimize the total life-cycle cost. This model innovatively integrates key economic factors, including the initial investment and long-term operation and maintenance costs of the battery energy storage system, as well as the fuel consumption and maintenance costs of the gas generator sets. The optimization objectives are the lowest overall system cost and the optimal energy storage capacity configuration. The results indicate that: ① While meeting the actual power demand, the optimal capacity of the energy storage battery is 1870 kWh, and the optimal charging/discharging power is 992 kW; ② The number of gas generator sets on site can be optimized from the original 8 to 4. This allows the units to operate stably within their high-efficiency range, increasing the average operating efficiency significantly from a maximum of 22.7% before optimization to 42.6%; ③ Under extreme working conditions with the maximum load during drilling operations, the optimally configured energy storage system can independently support the full site load for 4 hours, greatly enhancing the reliability and resilience of the power supply system. Read More

Abstract: With a growing share of renewable sources providing most of our electricity generation, they will introduce many unique challenges for tomorrow's power systems,including important problems of peak load management and scheduling difficulties. Energy storage provides a flexible means to provide energy,plays a key role to solve those problems. Energy blockchain has the characteristics of decentralization, transparency and immutability,provides a new idea for the management of information in energy system, As far as the key problem of how energy storage and energy blockchain could promote the construction of intelligent grid,this work suggests the endogenous relation between energy storage and energy blockchain technology which could be supportive to the evolution of smart grid,and analyses according to its operating mechanism, transaction mode, incentive mechanism and credit mechanism. Soenergy storage and energy block chain can build a grid optimization model combining IoT and data to enhance the flexibility of systems,unleashes the vitality of the distributed power market , fully reflects multi-dimensional values and reduces operation management cost ,and provides novel ideas on how to safely and stably operate smart grids. Read More

Abstract: With the growing integration of charging piles into the smart grid, efficiently aggregating privacy-containing charging data, dynamically optimizing charging strategies, and enhancing charging efficiency have become key future development directions. Current data aggregation schemes, mostly based on homomorphic encryption, place high computational demands on charging piles and may lead to centralized data management issues. To address these challenges, a lightweight data aggregation scheme based on consortium blockchain is proposed. Firstly, non-interactive symmetric encryption and aggregate signatures are used to reduce computational and communication overhead. Symmetric encryption ensures efficient encryption and decryption processes, while aggregate signatures compress multiple signatures into one, reducing storage and verification costs. Secondly, a hierarchical distributed data aggregation model is designed to achieve decentralization, distributing aggregation tasks across multiple layers to enhance system scalability and robustness. Thirdly, a dual-layer consensus algorithm is proposed based on the architecture of charging piles and edge cloud servers. This algorithm ensures low latency and system robustness at the charging pile layer, while the edge cloud server layer can resist Byzantine attacks. By balancing efficiency and security, this approach optimizes resource utilization and enhances privacy protection. Finally, experiments demonstrate that the proposed scheme significantly reduces computational and communication overhead and improves efficiency. Read More