Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Discussion on the Integrated Communication System of Local Electric Power Network in China

This paper describes current situation and special requirements of local electric power communication network in China. The paper discusses the disadvantages of SDH and fiber loop carrier system applied to electric power communication network. It presents a new Communication System-IDS-2000 integrated digital communication system. The paper introduces the characteristics and application of IDS-2000 system in the local electric power communication network.

Intelligent UAV Based Energy Supply for 6G Wireless Powered IoT Networks

In this paper,we develop a 6G wireless powered Internet of Things(IoT)system assisted by unmanned aerial vehicles(UAVs)to intelligently supply energy and collect data at the same time.In our dual-UAV scheme,UAV-E,with a constant power supply,transmits energy to charge the IoT devices on the ground,whereas UAV-B serves the IoT devices by data collection as a base station.In this framework,the system's energy efficiency is maximized,which we define as a ratio of the sum rate of IoT devices to the energy consumption of two UAVs during a fixed working duration.With the constraints of duration,transmit power,energy,and mobility,a difficult non-convex issue is presented by optimizing the trajectory,time duration allocation,and uplink transmit power of concurrently.To tackle the non-convex fractional optimization issue,we deconstruct it into three subproblems and we solve each of them iteratively using the descent method in conjunction with sequential convex approximation(SCA)approaches and the Dinkelbach algorithm.The simulation findings indicate that the suggested cooperative design has the potential to greatly increase the energy efficiency of the 6G intelligent UAV-assisted wireless powered IoT system when compared to previous benchmark systems.

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

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.

Design of Power Communication Data Network Management System and Implementation of Data Acquisition Module

The power communication network is a separate network from the power grid whose primary purpose is to ensure the power grid's safe operation.This paper expounds the composition of the comprehensive network management architecture of the power communication data network and the implementation of the data acquisition module in the network management system through theoretical analysis,for the reference of relevant personnel,in order to better promote the collection of power grid communication network data.

Utilization of Data Communication according to the IEC61850 Standard for Nuclear Power Plant Electrical Equipment Testing

This paper deals with an integration of directly measured electrical parameters with data acquired by data communication from protections and terminals into an advanced monitoring system. Based on the periodic test, the authors of this paper present the possibility of an extended evaluation and more accurate analysis of transient and failure events. For periodical testing, as implemented during the commissioning of power plants in the Czech Republic, a monitoring system of electrical equipment has been used, to record the courses of important electrical parameters and thus, proving the proper functioning of complex technological systems in various operation modes. Data from monitoring system were used to prove the successful results of the test or as a base data for further analysis of failures. The monitoring system has proved itself as a very useful device also when recording unexpected failure events, the cause of which was very quickly and accurately detected by the follow-up analysis. Initially, only the voltage and current data from measuring transformers, analogue transducers and contact relays were used as input data for the monitoring system. After the implementation of new digital protection technology and controlling terminals with inner data recorder, the data from digital devices could be also utilized for the monitoring system.

Fault Diagnosis Based on Graph Theory and Linear Discriminant Principle in Electric Power Network

In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discriminant are identical. The main technical contributions and innovations in this paper include, introducing global information into electric power network, developing a novel topological analysis to fault diagnosis. Graph theory algorithms can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. And the linear discriminant is a procedure used to classify an object into one of several a priori groupings dependent on the individual characteristics of the object. In the study of fault diagnosis in electric power network, graph theory algorithms and linear discriminant technology must also have a good prospect of application.

Application of Network Information Communication Technology in Power System

Network information communication technology in power systems is the key to ensuring the safe and efficient operation of power grids.The network information communication technology itself has advantages in automation operation and information transmission,thus is widely applied to the power system.In the case of ensuring that the power system is compatible with the network information communication technology,the control of the power system can be strengthened,and the operational efficiency of the power system can be improved.This paper mainly analyzes the specific application of network information communication technology in power system.

Development and Implementation of GSM-Based Distribution Automation System with Graphic User Interface in Nigeria Electric Power Distribution Network

Lack of up-to-date information on efficient operation and maintenance of EPDS （electric power distribution systems）, Nigeria is addressed by designing and implementing an indigenous real-time monitoring and diagnosis system. The system encompasses the development of software driven hardware positioned at the remotely located sub-stations at the low voltage level to keep track of the network in real-time. The detection of faults exploits threshold passing algorithm through continuous monitoring of the network power quality. Communication between the RTU （remote terminal unit） and the DCC （distribution control center） which is based on GSM is initiated by disturbance. The DCC performs fault evaluation processing using the received data and predetermined faults signatures to determine the nature of disturbance and presents the result in graphic user interface environment. A fault reporting time of 2 s was achieved. The developed system exhibits a high degree of accuracy and manifests no spurious reports during testing. The resultant system limits the effects of interruption and increases power availability by reducing the down time. The system strengthens engineering and management capabilities required to enhance reliability by providing information about the network health status.

Load Balancing-Based Routing Optimization Mechanism for Power Communication Networks

In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.

Distributed robust power control in two-tier vehicle networks under uncertain channel environments

This paper proposes a novel optimization scheme to support stable and reliable vehicle-to-everything connections in two-tier networks,where the uplink channel of the cellular user is reused by underlay vehicle-to-vehicle communications.However,considering complex channel fading and high-speed vehicle movement,the cer-tainty assumption is impractical and fails to maintain power control strategy in reality in the traditional statical vehicular networks.Rather than the perfect channel state information assumption,the first-order Gauss-Markov process which is a probabilistic model affected by vehicle speed and fading is introduced to describe imperfect channel gains.Moreover,interference management is a major challenge in reusing communications,especially in uncertain channel environments.Power control is an effective way to realize interference management,and optimal power allocation can ensure that interference of the user meets the communication requirements.In this study,the sum-rate-oriented power control scheme and minimum-rate-oriented power control scheme were implemented to manage interference and satisfy different design objectives.Since both of these schemes are non-convex and intractable,the Bernstein approximation and successive convex approximation methods were adopted to transform the original problems into convex ones.Furthermore,a novel distributed robust power control al-gorithm was developed to determine the optimal solutions.The performance of the algorithm was evaluated through numerical simulations,and the results indicate that the proposed algorithm is effective in vehicular communication networks with uncertain channel environments.

Covert Communication in Integrated High Altitude Platform Station Terrestrial Networks

In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.

New Optimal Power Allocation for Bidirectional Communications in Cognitive Relay Network Using Analog Network Coding

Cognitive radio and cooperative communication can greatly improve the spectrum efficiency in wireless communications.We study a cognitive radio network where two secondary source terminals exchange their information with the assistance of a relay node under interference power constraints.In order to enhance the transmit rate and maintain fairness between two source terminals,a practical 2-phase analog network coding protocol is adopted and its optimal power allocation algorithm is proposed.Numerical results verify the superiority of the proposed algorithm over the conventional direct transmission protocol and 4-phase amplify-and-forward relay protocol.

Create Your Own Data and Energy Integrated Communication Network:A Brief Tutorial and a Prototype System

In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.

Power Allocation for Cooperative Communications in Non-Orthogonal Cognitive Radio Vehicular Ad-Hoc Networks

To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to the main system in a controllable range.We propose a three-slot one-way vehicle system model where the mobile vehicle nodes complete information interaction with the assistance of other independent nodes by borrowing the unused radio spectrum with the primary networks.The end-to-end SNR relationship in overlay and underlay cognitive communication system mode are analyzed by using two forwarding protocol,namely,decode-and-forward(DF)protocol and amplify-and-forward(AF)protocol,respectively.The system outage probability is derived and the optimal power allocation factor is obtained via seeking the minimum value of the approximation of system outage probability.The analytical results have been confirmed by means of Monte Carlo simulations.Simulation results show that the proposed system performance in terms of outage under the optimal power allocation is superior to that under the average power allocation,and is also better than that under other power allocation systems.

Communication Networking Schemes for Wide Area Electric Vehicle Energy Service Network

Electric vehicles (EVs) are an emerging type of mobile intelligent power consumption devices in Smart Grid as new green transport tools. In order to provide a powerful automation and intelligence support for wide area electric vehicles energy service network, we analyze the network infrastructure and communications demands of various terminals, devices and monitoring systems distributed in wide area electric vehicle energy service network. According to interactive user services scenarios and energy operations intelligent monitoring, we propose multimode communication integration architecture for wide area electric vehicle energy service network by means of the fusion of the Internet of Things (IoT) technology. Then, we design different networking schemes in access networks and backbone transmission networks meeting multi-scene and multi-operation interaction requirements. The networking schemes will provide efficient technical support to implement intelligent, cross-regional, interactive energy services for electric vehicle users.

Protection Strategies against Cascading Failure for Power Systems of Ring Network

Power grid vulnerability is a key issue with large blackouts, causing power disruption for millions of people. The complexity of power grid, together with excessive number of components, makes it difficult to be modeled. Currently, researchers use complex networks to model and study the performance of power grids. In fact, power grids can be modeled into a complex network by making use of ring network topology, with substations and transmission lines denoted as nodes and edges, respectively. In this paper, three protection schemes are proposed and their effectiveness in protecting the power network under high and low-load attacks is studied. The proposed schemes, namely, Cascaded Load Cut-off (CLC), Cascaded Load Overflow (CLO) and Adaptive-Cascaded Load Overflow (A-CLO), improve the robustness of the power grids, i.e., decrease the value of critical tolerance. Simulation results show that CLC and CLO protection schemes are more effective in improving the robustness of networks than the A-CLO protection scheme. However, the CLC protection scheme is effective only at the expense that certain percentage of the network will have no power supply. Thus, results show that the CLO protection scheme dominates the other protection schemes, CLC and A-CLO, in terms of the robustness of the network, improved with the precise amount of load cut-off determined.

Global Harmonic Rate Assessment in the Electricity Distribution Network in Niamey City:Case Studies of Domestic,Industrial and Hospital Substations

Like others countries of the world, in Niger also, we are witnessing an increasing use of non-linear electric loads in the domestic, hospital and industrial sectors. However, these loads degrade the shape of the electrical signal and cause disastrous effects to the equipment of the distribution system and the devices which are connected to the network. This article highlights the presence of electric harmonics in the distribution network in Niamey city. In order to do this, measurements were taken at the secondary level of the substations using an energy quality analyze r (FLUKE 1735). By using this measuring instrument, we quantified the voltage and current Total Harmonic Distortion (THD) in the three substations. The results obtained show that, although the statutable rates set by the standards are not exceeded for phase conductors, the neutral contains a very critical percentage of distortion on the residential and hospital substations. Moreover, this assessment made it possible to observe the variation of harmonics in the presence of voltage drops.