Knowledge model for electric power big data based on ontology and semantic web

The construction of the electric power system has entered the era of big data, and all links in the system have accumulated massive amounts of electric power big data. Doing a better analysis of these valuable data resources will bring considerable benefits to electric power companies. The deep learning technology in the field of artificial intelligence has obvious advantages when dealing with massive data tasks. Benefit from the advancement of deep learning technology, power big data research has developed rapidly. This paper introduces the current development of machine learning algorithms, and focuses on the application of deep learning in the power industry.

In the context of big data, an in-depth understanding of the potential correlation between electric power consumption and pollutant emission concentration of industrial enterprises is of great significance for effective prediction and monitoring of pollutant emissions. In this paper, considering the properties of nonlinearity and complexity in the data of electric power consumption and pollutant emission of industrial enterprises, we apply cross-correlation statistic test, detrended cross-correlation analysis and multifractal detrended cross-correlation analysis to study the correlation between them. Our numerical example based on an industrial enterprise shows that there is indeed an association between electricity consumption data and pollutant emission concentration of the enterprise. Moreover, the correlations between them demonstrate long memory and multifractality. Our research can help to further predict the pollutant emission using the electric power big data.

Since the early 1990s, the United States Air Force has been successfully pursuing advancement in aircraft electrical power system technologies as a means of collectively establishing the capability to dramatically reduce or eliminate centralized hydraulics aboard aircraft and replace it with electrical power as the motive force for all aircraft functions. This overall approach (called the More Electric Aircraft, MEA) has been analytically determined to provide dramatic improvements in reliability, maintainability, supportability and operations/support cost as well as enhancements in aircraft weight, volume, and battle-damage reconfigurability. Advances in switched reluctance configuration electric machines and solid state power electronics has enabled demonstration of an MEA. This paper provides: (1) a brief historical treatment of technology milestones achieved which enabled the MEA approach; (2) a status of United States Air Force and Department of Defense research and development programs in electrical power generation, distribution, energy storage, systems integration and flight testing; (3) a description of some of the Air Force's planned demonstration activities in aircraft electrical power subsystems; and (4) the dual use nature of many of these technologies to enable a variety of electric and hybrid electrically-propelled military weapon systems and commercial vehicles.

International Conference on Hydrodynamics, Energy and Electric Power System (HEEPS) is an annually held conference, it aims to provide a forum for participants to exchange their experiences, share research results in all aspects about Hydrodynamics, Energy and Electric Power System and discuss the encountered practical challenges and the adopted solutions. The 2024 8th International Conference on Hydrodynamics, Energy and Electric Power System (HEEPS 2024) was held in Beijing, China from June 28th to 30th, 2024. This esteemed conference, as the eighth in its series, continues to serve as a premier platform for researchers, scholars, and industry professionals to converge, share insights, and collaborate on the latest advancements in hydrodynamics, water resources and hydropower engineering, energy systems, and electric power technologies. HEEPS 2024 was organized with the aim of fostering interdisciplinary dialogue and innovation within the rapidly evolving fields of fluid mechanics, energy systems, and power engineering. Building upon the success of the previous seven editions, this conference attracted a diverse and vibrant community of participants from around the world. The event was hosted with the support of esteemed institutions such as the University of Chinese Academy of Sciences and Universiti Putra Malaysia, further enhancing its international reach and impact. HEEPS 2024 was an outstanding three-day conference and a reference that attracted many remarkable keynote speakers, including: Professor Jizhong Zhu (South China University of Technology, China), Professor Ishak Bin Aris (Universiti Putra Malaysia, Malaysia), Professor Lin Chen (Chinese Academy of Sciences, China), Associate Professor Sohrab Mirsaeidi (Beijing Jiaotong University, China), as well as Assistant Professor Jianxiao Wang (Peking University, China). The program kicked off with a series of keynote lectures delivered by renowned experts in their respective fields, setting the tone for an intellectually stimulating conference. These presentations covered a broad spectrum of topics, ranging from fundamental research in hydrodynamics and fluid mechanics to the latest developments in energy systems and power grid technologies. Besides, during all parts of the conference, the attendees actively interacted with the speakers and each other on specific topics. The conference’s Proceedings of HEEPS 2024 contains the papers accepted and presented at this great conference. All these contributions were carefully reviewed by program committee members and took into consideration the breadth and depth of the research topics that fall into HEEPS scope. On behalf of the conference organizers, we would like to take this opportunity to express our sincere thanks to all the editors and reviewers for their tremendous efforts and dedication to the conference. We also wish to thank all the authors and speakers for their great contributions to this conference and the conference’s Proceedings. And we believe that with such earnest support and contributions, the future HEEPS conferences will also scale new heights. The Committee of HEEPS 2024 List of Committee Member are available in this pdf.

The electric power system's seasonality would mitigate the problem of the energy volatility crisis. Seasonal identification is important in energy usage analysis to make a better an organization's energy performance. Identification of the seasonal component in a time series data is essential since it defines a fluctuation within an interval of time. This seasonal component can be identified as a periodic phenomenon. Signal processing models can be used in analyzing periodic data in the representation of sinusoidal function. Seasonal variations are an important factor influencing the behavior of an electric power and energy load. This paper introduces the application of deterministic functions in the Ornstein\textendash Uhlenbeck process as a sinusoidal signal processing model in identifying seasonal components represented in periodic terms. We conducted extensive experiments to validate the model on three datasets in electric power and energy systems namely electricity load, household electric power consumption, and power consumption of the three source stations. Further, it can be obtained that the periodic continuous-time-inhomogeneous signal of Ornstein\textendash Uhlenbeck model can be used to identify the seasonal term of the very short to medium horizon forecast of the electric power and energy system. Seasonal changes in energy consumption can be used in energy management in the scope of energy efficiency connected to renewable energy plans.

<div class="htmlview paragraph">A lot of electric components have been installed in a vehicle today for comfort, safety and environment. This tendency is said to be continued in the future. Therefore, additional power supplies such as exhaust gas electricity generation system and thermal electricity generation system have been developed in the world to supply additional electricity as well as an enlargement of an alternator. However, if these new electricity supply systems are installed in a present electric power system that is controlled based on a voltage feedback, each supply system cannot be controlled effectively, because it is difficult to control output power of each system independently. An electric power based control system, <u><b>V</b></u>ehicle <u><b>E</b></u>lectric power <u><b>F</b></u>low management system (<b>VEF</b>), has been developed to avoid this problem.</div> <div class="htmlview paragraph">Sum of required electric power is calculated based on electric loads power and battery charging power. This required power is allocated to each power supply system. This assignment is performed according to an index, a running cost of electricity. This index is called <b>DENPI</b> (<u><b>D</b></u>esign of <u><b>E</b></u>lectric <u><b>N</b></u>etwork with <u><b>P</b></u>ower <u><b>I</b></u>ndex). For example, <b>DENPI</b> of the alternator changes according to an engine torque, a rotational speed and efficiency. Therefore, electric power system can supply electricity more effectively by selecting power system according to <b>DENP</b>. <b>VEF</b> automatically allocates each power supply system according to <b>DENPI</b> of each power supply system. As this function has a unique structure, it can be extensively applied to new electricity generation systems in various categories of vehicles.</div> <div class="htmlview paragraph"><b>VEF</b> has been evaluated with a test vehicle, and the results show that this structure is applicable to a real vehicle and the running cost of electricity is improved 30% compared to a conventional system.</div>

An electric power system (EPS) with high-power-delivery and low-system-mass is required for wide body all electric aircraft (AEA). Cables are an essential component of this future EPS. At the cruising height of a wide-body aircraft the pressure is about 16.8 kPa. At that pressure, heat transfer to the ambient air by convection is strongly limited, so the distribution of temperature field across the aircraft cables is expected to be different from atmospheric pressure. The temperature field across the cable depends on the velocity field of the ambient air, which depends on the pressure and temperature. Also, to obtain the electric field of DC cables in the electric aircraft power system, the conductivity of the insulation, a function of temperature and electric field, should be calculated. In this paper, a 5 kV DC cable is studied at 16.8 kPa pressure to compare the cable's electric field and temperature field at low pressure to the atmospheric pressure. In our earlier research, we suggested novel EPS topologies for wide body AEA, and 5 kV DC is the voltage level that was taken into consideration. Moreover, the maximum permissible flowing current of the cable is investigated at the pressure of 16.8 kPa regarding the thermal limits of the cable. It is shown that at low pressures the temperature of the cable is highly increased compared to atmospheric pressure, so permissible current is lower than rated current.

This dissertation contributes to our understanding of how plug-in hybrid electric vehicles (PHEVs) and plug-in battery-only electric vehicles (EVs)—collectively termed plug-in electric vehicles (PEVs)—could be successfully integrated with the electric power system. The research addresses issues at a diverse range of levels pertaining to light-duty vehicles, which account for the majority of highway vehicle miles traveled, energy consumed by highway travel modes, and carbon dioxide emissions from on-road sources. Specifically, the following topics are investigated: (i) On-board power electronics topologies for bidirectional vehicle-to-grid and grid-to-vehicle power transfer; (ii) The estimation of the electric energy and power consumption by fleets of light-duty PEVs; (iii) An operating framework for the scheduling and dispatch of electric power by PEV aggregators; (iv) The pricing of electricity by PHEV aggregators and how it affects the decision-making process of a cost-conscious PHEV owner; (v) The impacts on distribution systems from PEVs under aggregator control; (vi) The modeling of light-duty PEVs for long-term energy and transportation planning at a national scale.

Hybrid power systems are a combination of electric power generation technologies configured to meet specific customer needs such as reliable electric power, low cost, or portable power. If the power generation uses renewable sources such as wind, geothermal, solar, biomass, and waste, then the result is rightly considered a renewable system-of-systems. This is because each of the power systems can operate separately, but when combined, individual subsystems and components can be shared. In addition, the combined systems provide functionality that is not possible from any one of the sources. The discipline of systems engineering offers methods and techniques that can be applied to the engineering of hybrid renewable electric power generation. In this work, we apply systems-of-systems methods developed by systems engineering to develop a hybrid renewable electric power system. We examine customer needs for a specific renewable energy source. We then develop concepts that will meet that need by exploring multiple alternatives and their combinations. The concepts are subject to trade study against the customer needs. We then show the baseline design of a system that combines Concentrated Solar Power (CSP) with waste processing such as biomass and Pyrolysis. We conclude with a summary and suggestions for other hybrid electric power systems that can benefit from systems engineering techniques.

With the vigorous development of the global economy, the demand for electricity quality from all walks of life is also increasing, so it is essential to ensure the electric power grid’s safe, stable, and efficient operation. Multi-source electric power information fusion, as the core technology of electric power grid data processing, has become the foundation to promote the intelligent and automatic development of the electric power grid. This paper presents the first work on the survey of the methods of electricity information fusion. It first gives an overview of the process of electricity information fusion and shows the types of electricity data. Then, we provide different classifications of existing methods in view of communication annotation and electric power data, and conduct a thorough comparison and analysis of them. Moreover, we introduce the relevant data sets and evaluation criteria of electric power information and summarize the corresponding evaluation scenarios. Finally, we conclude the maturity of existing works and provide an outlook on future multi-source electric power information fusion methods.

For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.

Demand and supply-side determinants of electric power consumption and representative roadmaps to 100% renewable systems

The development of electric power technology and of super conductor devices since the discovery in 1911 of superconductivity is reviewed in detail with information on superconductor theory, materials development, helium and hydrogen refrigeration, the design and performance of superconducting devices built in the US, Europe, and Japan, potential applications of superconducting magnets and coils in the electric power system, and the benefits of improving the efficiency of power transmission by the use of still-to-be-developed superconductors which can withstand high current densities and strong magnetic fields. (LCL)

Recent developments in aircraft electrical technology, such as the design and production of more electric aircraft (MEA) and major steps in the development of all-electric aircraft (AEA), have had a significant impact on aircraft’s electrical power systems (EPSs). However, the EPSs of the latest aircraft produced by the main players in the market, Airbus with the Neo series and Boeing with the NG and MAX series are still completely traditional and based on the constant speed constant frequency (CSCF) configuration. For alternating current ones, the EPS is composed of the following: prime movers, namely the aircraft turbofan engine (TE); the electrical power source, i.e., the integrated drive generator (IDG); the command and control system, the generator control unit (GCU); the transmission and the system distribution system; the protection system, i.e., the CBs (circuit breakers); and the electrical loads. This paper presents the analysis of this system using the Simscape package from Simulink v 8.7, a MATLAB v 9.0 program, which is actually the development of some systems designed in two previous personal papers. For the first time in the literature, a complete MATLAB modelled EPS system was presented, i.e., the aircraft turbofan engine model, driving the constant speed drive system (CSD) (model presented in the first reference as a standalone type and with different parameters), linked to the synchronous generator (SG) (model presented in second reference for lower power and rotational speed) in the so-called integrated drive generator (IDG) and electrical loads.

Hive is a data warehouse architecture in cloud computing. In order to solve the inadequate of massive data storage, query, and computing power in current electric power data warehouse, a method of electric power data warehouse based on Hive is proposed. Combining data analysis demands of electric power entreprises, the integration architecture between Hive and column-oriented storage is designed in electric power data warehouse, and the process of which is also given. At last, electric power equipment condition data is used for experiment on Hadoop cluster, results show that this method can quickly achieve query and analysis in massive multidimensional data set.