A coordinated operation method of wind-PV-hydrogenstorage multi-agent energy system

Wind-photovoltaic(PV)-hydrogen-storage multi-agent energy systems are expected to play an important role in promoting renewable power utilization and decarbonization.In this study,a coordinated operation method was proposed for a wind-PVhydrogen-storage multi-agent energy system.First,a coordinated operation model was formulated for each agent considering peer-to-peer power trading.Second,a coordinated operation interactive framework for a multi-agent energy system was proposed based on the theory of the alternating direction method of multipliers.Third,a distributed interactive algorithm was proposed to protect the privacy of each agent and solve coordinated operation strategies.Finally,the effectiveness of the proposed coordinated operation method was tested on multi-agent energy systems with different structures,and the operational revenues of the wind power,PV,hydrogen,and energy storage agents of the proposed coordinated operation model were improved by approximately 59.19%,233.28%,16.75%,and 145.56%,respectively,compared with the independent operation model.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

Operation Control Method of Relay Protection in Flexible DC Distribution Network Compatible with Distributed Power Supply

A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.

Identification of Key Links in Electric Power Operation Based-Spatiotemporal Mixing Convolution Neural Network

As the scale of the power system continues to expand,the environment for power operations becomes more and more complex.Existing risk management and control methods for power operations can only set the same risk detection standard and conduct the risk detection for any scenario indiscriminately.Therefore,more reliable and accurate security control methods are urgently needed.In order to improve the accuracy and reliability of the operation risk management and control method,this paper proposes a method for identifying the key links in the whole process of electric power operation based on the spatiotemporal hybrid convolutional neural network.To provide early warning and control of targeted risks,first,the video stream is framed adaptively according to the pixel changes in the video stream.Then,the optimized MobileNet is used to extract the feature map of the video stream,which contains both time-series and static spatial scene information.The feature maps are combined and non-linearly mapped to realize the identification of dynamic operating scenes.Finally,training samples and test samples are produced by using the whole process image of a power company in Xinjiang as a case study,and the proposed algorithm is compared with the unimproved MobileNet.The experimental results demonstrated that the method proposed in this paper can accurately identify the type and start and end time of each operation link in the whole process of electric power operation,and has good real-time performance.The average accuracy of the algorithm can reach 87.8%,and the frame rate is 61 frames/s,which is of great significance for improving the reliability and accuracy of security control methods.

DSS Scheme for Operation Optimization Problem on Power Plants

Based on the target analysis of the operation optimization for power plants, a novel system scheme called operation optimization decision support system (OODSS) is brought forward. According to the structure and design thinking of decision support system (DSS), the overall structure of the OODSS is studied, and the scheme of the sub systems in the OODSS such as the user interface system, the problem processing system, the database system, the model base system, the expert system (ES) and the data mining sy...

A low-carbon economic dispatch model for electricity market with wind power based on improved ant-lion optimisation algorithm

Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.

Study on integrated development and hybrid operation mode of nuclear power plant and pumped-storage power station

The nuclear power plant is suitable for base-load operation, while the pumped-storage unit mainly gives play to capacity benefit in the electric power system;hence, the integrated development and hybrid operation mode of the two can better meet the needs of the electric power system. This article first presents an analysis of the necessity and superiority of such mode, then explains its meaning and analyzes the working routes. Finally, it proposes the business modes as follows: low price pumping water electricity plus nuclear power in the near term;nuclear power shifted to pumped storage power participating in market competition in the middle term;and, in the long term, nuclear power shifted to pumped storage power as primary and serving as an electric power system when needed.

Wind power operation capacity credit assessment considering energy storage

Research on wind power capacity credit at the operational level plays an important role in power system dispatching.With the popularity of energy storage devices,it is increasingly necessary to study the impact of energy storage devices on wind power operational capacity credit.The definition of wind power operational capacity credit is given.The available capacity model of different generators and the charging and discharging model of the energy storage are established.Based on the above model,the evaluation method of wind power operation credible capacity considering energy storage devices is proposed.The influence of energy storage on the wind power operation credible capacity is obtained by case study,which is of great help for the power system dispatching operation and wind power accommodation.

Similarity matching method of power distribution system operating data based on neural information retrieval

Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of data-driven operation management,intelligent analysis,and mining is urgently required.To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation,maintenance experience,and knowledge by rule and line,a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology.Based on the processing flow of the operating data of the power distribution system,a technical framework of neural information retrieval is established.Combined with the natural graph characteristics of the power distribution system,a unified graph data structure and a data fusion method of data access,data complement,and multi-source data are constructed.Further,a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed.The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set.The model is verified on the operating section of the power distribution system of a provincial grid area.The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.

Large-Scale Distributed Photovoltaic Power Dispatching and Operation Management Review

Distributed photovoltaic power (PV) is the main development model of distributed generation. It is necessary to research on dispatching and operation management with large-scale distributed PV connected. This paper analyzes development status, technical requirement and dispatching and operation management situation of distributed PV in Germany and China. Then introduce the preparation of distributed PV dispatching and operation management criterion. Through summarizing the experiences and lessons of large-scale distributed PV development in Germany, it gives advice to the development of distributed PV dispatching and operation management in China.

Energy-Efficient Operation of Water Systems through Optimization of Load Power Reduction in Electricity Markets

Demand response(DR) is gaining more and more importance in the architecture of power systems in a context of flexible loads and high share of intermittent generation. Changes in electricity markets regulation in several countries have recently enabled an effective integration of DR mechanisms in power systems. Through its flexible components(pumps, tanks), drinking water systems are suitable candidates for energy-efficient DR mechanisms. However, these systems are often managed independently of power system operation for both economic and operational reasons. Indeed, a sufficient level of economic viability and water demands risk management are necessary for water utilities to integrate their flexibilities to power system operation. In this paper,we proposed a mathematical model for optimizing pump schedules in water systems while trading DR blocs in a spot power market during peak times. Uncertainties about water demands were considered in the mathematical model allowing to propose power reductions covering the potential risk of real-time water demand forecasting inaccuracy.Numerical results were discussed on a real water system in France, demonstrating both economic and ecological benefits.

Daily Operation Optimization of a Residential Molten Carbonate Fuel Cell Power System Using Genetic Algorithm

To decrease the cost of electricity generation of a residential molten carbonate fuel cell （MCFC） power system, multi-crossover genetic algorithm （MCGA）, which is based on ＂multi-crossover＂ and ＂usefulness-based selection rule＂, is presented to minimize the daily fuel consumption of an experimental 10kW MCFC power system for residential application. Under the operating conditions obtained by MCGA, the operation constraints are satisfied and fuel consumption is minimized. Simulation and experimental results indicate that MCGA is efficient for the operation optimization of MCFC power systems.

基于调和概率语言术语集的Power平均算子

实践发现现存概率语言Power平均算子在应用中存在概率信息丢失、计算过于繁琐等问题,针对这些问题,提出一种基于调和概率语言术语集的Power平均算子。结合新的基本运算法则与新的支撑度,给出新的概率语言Power平均算子、概率语言Power几何平均算子、概率语言Power加权平均算子、概率语言Power加权几何平均算子,同时论证分析了这几类新型算子的性质。最后通过实验数据,将提出的算子与现存算子进行对比分析,验证了所提算子的有效性与可行性。

A method for cleaning wind power anomaly data by combining image processing with community detection algorithms

Current methodologies for cleaning wind power anomaly data exhibit limited capabilities in identifying abnormal data within extensive datasets and struggle to accommodate the considerable variability and intricacy of wind farm data.Consequently,a method for cleaning wind power anomaly data by combining image processing with community detection algorithms(CWPAD-IPCDA)is proposed.To precisely identify and initially clean anomalous data,wind power curve(WPC)images are converted into graph structures,which employ the Louvain community recognition algorithm and graph-theoretic methods for community detection and segmentation.Furthermore,the mathematical morphology operation(MMO)determines the main part of the initially cleaned wind power curve images and maps them back to the normal wind power points to complete the final cleaning.The CWPAD-IPCDA method was applied to clean datasets from 25 wind turbines(WTs)in two wind farms in northwest China to validate its feasibility.A comparison was conducted using density-based spatial clustering of applications with noise(DBSCAN)algorithm,an improved isolation forest algorithm,and an image-based(IB)algorithm.The experimental results demonstrate that the CWPAD-IPCDA method surpasses the other three algorithms,achieving an approximately 7.23%higher average data cleaning rate.The mean value of the sum of the squared errors(SSE)of the dataset after cleaning is approximately 6.887 lower than that of the other algorithms.Moreover,the mean of overall accuracy,as measured by the F1-score,exceeds that of the other methods by approximately 10.49%;this indicates that the CWPAD-IPCDA method is more conducive to improving the accuracy and reliability of wind power curve modeling and wind farm power forecasting.

Carbon Emission Factors Prediction of Power Grid by Using Graph Attention Network

Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calculating node carbon emission factors based on the carbon emissions flow theory requires real-time parameters of a power grid.Therefore,it cannot provide carbon factor information beforehand.To address this issue,a prediction model based on the graph attention network is proposed.The model uses a graph structure that is suitable for the topology of the power grid and designs a supervised network using the loads of the grid nodes and the corresponding carbon factor data.The network extracts features and transmits information more suitable for the power system and can flexibly adjust the equivalent topology,thereby increasing the diversity of the structure.Its input and output data are simple,without the power grid parameters.We demonstrated its effect by testing IEEE-39 bus and IEEE-118 bus systems with average error rates of 2.46%and 2.51%.

Generation of input spectrum for electrolysis stack degradation test applied to wind power PEM hydrogen production

Hydrogen production by proton exchange membrane electrolysis has good fluctuation adaptability,making it suitable for hydrogen production by electrolysis in fluctuating power sources such as wind power.However,current research on the durability of proton exchange membrane electrolyzers is insufficient.Studying the typical operating conditions of wind power electrolysis for hydrogen production can provide boundary conditions for performance and degradation tests of electrolysis stacks.In this study,the operating condition spectrum of an electrolysis stack degradation test cycle was proposed.Based on the rate of change of the wind farm output power and the time-averaged peak-valley difference,a fluctuation output power sample set was formed.The characteristic quantities that played an important role in the degradation of the electrolysis stack were selected.Dimensionality reduction of the operating data was performed using principal component analysis.Clustering analysis of the data segments was completed using an improved Gaussian mixture clustering algorithm.Taking the annual output power data of wind farms in Northwest China with a sampling rate of 1 min as an example,the cyclic operating condition spectrum of the proton-exchange membrane electrolysis stack degradation test was constructed.After preliminary simulation analysis,the typical operating condition proposed in this paper effectively reflects the impact of the original curve on the performance degradation of the electrolysis stack.This study provides a method for evaluating the degradation characteristics and system efficiency of an electrolysis stack due to fluctuations in renewable energy.

Assessment of Axial Power Peaking Factors in GHARR-1 LEU Core: A Decadal Simulation Analysis

This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the MCNPX code for analysing neutron behavior and the PARET/ANL code for understanding power variations, to get a clearer picture of the reactor’s performance. The analysis covers the initial six years of GHARR-1’s operation and includes projections for its whole 60-year lifespan. We closely observed the patterns of both the highest and average PPFs at 21 axial nodes, with measurements taken every ten years. The findings of this study reveal important patterns in power distribution within the core, which are essential for improving the safety regulations and fuel management techniques of the reactor. We provide a meticulous approach, extensive data, and an analysis of the findings, highlighting the significance of continuous monitoring and analysis for proactive management of nuclear reactors. The findings of this study not only enhance our comprehension of nuclear reactor safety but also carry significant ramifications for sustainable energy progress in Ghana and the wider global context. Nuclear engineering is essential in tackling global concerns, such as the demand for clean and dependable energy sources. Research on optimising nuclear reactors, particularly in terms of safety and efficiency, is crucial for the ongoing advancement and acceptance of nuclear energy.

Operation Indices for Smart Power Dispatch Center Design

With the development of power systems, power grid within a control area becomes much more complicated due to increasing number of nodes and renewable energy interconnections. The role of power system control center is more critical in maintaining system reliable and security operations. Latest developed information and communication technologies provide a platform to enhance the functions and performance of power system control center. Smart power dispatch concept will be the trend of future control center development. In this paper, we start from the human factors of control center design and propose operation indices to reduce the information presented to the system operator. The operation indices will be the important criteria in situation awareness of a power grid. Past, present, future and capability states of a power grid are also proposed to provide better visions to the operator of system conditions. The basic ideas of operation indices and operation states are discussed in the paper. In the end, the design factors for a power dispatch cockpit are discussed.

The Low-Carbon Operations in Ecotourism Service Supply Chain Management

The ecotourism has quickly developed as the fastest growing industry in recent years. Ecotourism is one kind of tourism industry that also consists of complex service providers like travel agents, hotels, transportations （such as airplane, bus, and ship） restaurants, and destinations, connecting with operational diversity; therefore, those of supported services are linked with a supply chain together, and its management is called ecotourism service supply chain management （ESSCM）. Moreover, a low-carbon operation management has also become an important challenge to ecotourism nowadays. Based on the problems of service and low-carbon operation management made together above, exploring an effective solution into ecotourism is worthy. Using ESSCM as a strategy for solving industrial problems of service and low-carbon operations management in ecotourism is explored in this paper. The contributions here include clearly explanations of what ESSCM is and how ESSCM is used with low-carbon operations as a sustainability strategy, and finally a practical case study is also examined in the end.