Bikaranîna û Amalê Piramerdên Sistemanên Danûnî yên Nîgînîn dixanên Tewrîya

Bi kîna çewitandina sistanê yên dengê, sistanên zihniyê di sisteman de rola yekêm bixweber kirin. Sistemanên monitorîkên deng an jî herî mafanîn ji bo xalatkirina berdewam, stabîl û efektîf ên rêzanên dengê. Sistemanên monitorîkên deng ya sistanên dengên tîrî ne ku dest pêk hatine werin biceribandin vebijarkên dengê û standartên binihêrinan.

Li ser pirastina avancman teknolojî, sistemanên monitorîkên deng ya sistanên zihniyê hewce dikin monitorîkên demhatî û kontrolên efektîf bikin, çareserkên nû yên bixweberiya sistemê bigihin. Lekin, di navcheyan de, ev sistemanên jorîn parastî yên cihazî, bihaqîk bîrkarî û komunikasyon, parastina guhertin û çendîna operasyon û binihêrîn gotin.

Ev pirsgirêkên li ser realliyekirina beşdarîyan ên sistemanên monitorîkên deng ya sistanên zihniyê tevahî dike. Buna, kerdarî yên qıtanî yên strategî û formolandina mekayînên optimizasyon bixweber in ji bo piştguhî kirina zihniyetî yên industrîya dengê û amana bike dengê.

1. Mafanîya Sistemanên Monitorîkên Deng ya Sistanên Zihniyê

1.1 Enhancing Real-Time Monitoring Capabilities

Sistanên zihniyê bi sensorên zihniyê yên duzgeha dengê girîng e ku dê bibin parametaran operasyonî yên cihazên dengê—wisa, voltaj, deng û guç—û dê wan dergehan bibin wekî malpera. Herî paşî sistanên tîrî, girtina malpera girîngre ye, ku tu tiştî cihazên serekan de, divê statû malpera cihazên dinikan de heye, ku monitorîkên demhatî yên reyalî yên tamam rêzanên dengê biguherîne.

Li ser şeşberên komunikasyonê yên tez, sisteman monitorîkê data yên mezburî dergehan proces bike, ku amadeyî reyalî yên operasyon ên rêzanên dengê rastîn biguhere. Ev alîkarî operaçyonên cihazan abnormale û potensiyelî û çendîna demhatî bike, ku etilal demhatî bike û têkiliyê û amana rêzanên dengê biguherîne, ku dê bîraşî û stabîlikê yên dengê digire.

1.2 Strengthening System Security and Stability

Sistemanên monitorîkên deng ya sistanên zihniyê dê riske parastî yên potensiyelî detekt bike û warîn bike lekî wê di demhatî yên operasyon ên rêzanên dengê de. Mînase, dema sisteman overloads, short circuits, û teriqên temperature yên abnormale bibin, alarm bike û çendîna çendîna faulê bibin, malpera faulê yên detalî yên têkildara çendînê bibin.

Ev alîkarî li ser teriqên faulê digire û amana û stabîlî rêzanên dengê biguherîne. Li ser bihêrî, sistanên zihniyê bi kapasîta kontrol otomatîk e. Dema faulê were, sisteman dê çendîna çendîna çendîna bibin û moda operasyonê bi strategî yên predestîn bike, ku dê çendîna çendîna bibin. Ev alîkarî li ser dema û nav û çendîna faulê bibin, kapasîta sisteman ên çendînê bike, ku dê amana û stabîlî rêzanên dengê biguherîne.

1.3 Optimizing Operation and Maintenance Management

Sisteman monitorîkên deng ya sistanên zihniyê revolucion bixweber dike binihêran (O&M) management. Bi birgirtina û analîzîna malpera operasyon ên dawî yên cihazên dengê, modelên health assessment dê binivîse û dê amadeyî reyalî yên faulê û dema servîsê bibin. Ev alîkarî ji binihêrên scheduleyên tîrî ve ji binihêrên prediktîf bibin.

Ev alîkarî lê ne ku resmikînên binihêrên zaf û binihêrên zaf bibin, lê ne ku çendîna potensiyelî bibin, programên çendînê bibin, ku dê riske faulê bibin, û amana û têkiliyê yên cihazan bibin. Li ser bihêrî, sisteman monitorîkê dê workflow û çendînê bibin, ku dê amadeyî binihêrên zaf û çendînê bibin, ku dê amadeyî binihêrên zaf û çendînê bibin, ku dê amadeyî binihêrên zaf û çendînê bibin.

2. Major Challenges Facing Power Monitoring Systems in Smart Substations

2.1 System Integration and Compatibility Issues

Sistemanên monitorîkên deng ya sistanên zihniyê bi cihaz û software yên zaf û modelan yên dinikan integre kirin, ku cihazên serekan, cihazên parastin, unitên measurement û control, û platformên monitorîkên software yên zaf û modelan yên dinikan integre kirin. Komponentan yên mêhur standard û specificationên din dikin, ku yekîtiyên integrasyon û interface standard nabe.

Ev alîkarî li ser protocolên komunikasyon û data interoperability û amadeyî informasyon bibin. Mînase, cihazên zihniyê protokolên komunikasyon û data interoperability û amadeyî informasyon bibin, ku dê amadeyî protocol conversion û adaptasyon bibin. Ev alîkarî li ser workload û çendînê bibin, ku dê amadeyî data transmission errors û delays bibin, ku dê performans û stabîlî sisteman monitorîkê bibin. Li ser bihêrî, li ser bihêrî, compatibility issues bibin, ku dê amadeyî integration complexity û limiting the full utilization of system functions bibin.

2.2 Data Processing and Communication Bottlenecks

Data volume in smart substations grows exponentially, including massive real-time operational data, equipment status monitoring data, and fault recording data—all of which require rapid processing and transmission. However, current power monitoring systems face obvious bottlenecks in data processing capacity and communication bandwidth. On one hand, hardware configurations at data processing centers may be insufficient to handle real-time computing demands for large datasets, and data processing algorithms need improvement, resulting in processing delays and preventing timely delivery of accurate decision-support information to operators.

On the other hand, limited communication network bandwidth can lead to congestion during peak transmission periods. When a fault occurs, a surge of data floods the monitoring center simultaneously, potentially causing packet loss, delay, or even transmission interruption. This severely affects the monitoring system’s ability to grasp real-time system status and respond to faults quickly. In addition, communication network reliability remains a concern; adverse weather conditions and electromagnetic interference may cause communication failures, further weakening data transmission capability and posing potential risks to the safe and stable operation of the power system.

2.3 Inadequate System Security and Protection Measures

Sistemanên monitorîkên deng ya sistanên zihniyê bi cihaz û software yên zaf û modelan yên dinikan integre kirin, ku cihazên serekan, cihazên parastin, unitên measurement û control, û platformên monitorîkên software yên zaf û modelan yên dinikan integre kirin. Komponentan yên mêhur standard û specificationên din dikin, ku yekîtiyên integrasyon û interface standard nabe.

Ev alîkarî li ser protocolên komunikasyon û data interoperability û amadeyî informasyon bibin. Mînase, cihazên zihniyê protokolên komunikasyon û data interoperability û amadeyî informasyon bibin, ku dê amadeyî protocol conversion û adaptasyon bibin. Ev alîkarî li ser workload û çendînê bibin, ku dê amadeyî data transmission errors û delays bibin, ku dê performans û stabîlî sisteman monitorîkê bibin. Li ser bihêrî, li ser bihêrî, compatibility issues bibin, ku dê amadeyî integration complexity û limiting the full utilization of system functions bibin.

Finally, security protection technologies lag behind evolving attack methods, lacking effective detection and early warning capabilities against new threats. As a result, smart substation power monitoring systems appear ill-equipped to handle increasingly complex cybersecurity environments, struggling to ensure information security and stable operation.

2.4 Increased Complexity of Operation and Maintenance Management

The high level of intelligence and automation in smart substations has significantly increased the complexity of O&M management. On one hand, the wide variety of intelligent devices and rapid technological updates require O&M personnel to master diverse operational and maintenance skills, placing higher demands on their professional competence. For example, configuration and debugging methods for new intelligent secondary devices are more complex than those for traditional devices, requiring O&M staff to invest more time and effort to learn and adapt. 

On the other hand, O&M processes have become more complicated, involving multiple stages such as equipment status monitoring, data analysis, fault diagnosis, maintenance planning, and remote operations. Coordination among these stages is challenging. Moreover, as the scale of smart substations expands, so does the O&M scope. Achieving centralized and efficient management across multiple substations becomes a major challenge. In addition, various software platforms and tools within the O&M system face compatibility and usability issues, potentially hindering actual operations and affecting O&M efficiency and quality. This increases O&M costs and risks, undermining the long-term stable operation and sustainable development of smart substation power monitoring systems.

3. Optimization Strategies for Power Monitoring Systems Based on Smart Substations

3.1 Improving System Integration and Standardization

To effectively address integration and compatibility challenges, efforts should focus on strengthening system integration and standardization. First, unified system architecture standards should be established, clearly defining the functional roles and interface specifications of each device and subsystem within the monitoring framework, ensuring seamless interconnection and collaborative operation among equipment from different manufacturers.

Second, a comprehensive equipment certification system should be developed to ensure only standardized-compliant devices enter the market and are deployed in smart substations, guaranteeing compatibility from the source. During project implementation, system integrators should play a leading role, coordinating all resources and managing equipment selection, installation, commissioning, and joint testing throughout the process. This ensures integration quality and system stability, forming an integrated, highly coordinated whole that fully leverages the advantages of smart substations, improves operational efficiency and management levels, and lays a solid foundation for reliable and stable power supply.

3.2 Enhancing Data Processing Capacity and Communication Efficiency

To address data processing and communication bottlenecks, hardware upgrades to the data processing center are essential. High-performance server clusters, distributed storage systems, and advanced parallel computing technologies should be introduced to significantly enhance data processing capabilities, ensuring rapid handling of massive power data. Simultaneously, data processing algorithms should be optimized.

Technologies such as data mining and machine learning should be applied to deeply analyze real-time operational and equipment monitoring data, extracting valuable insights to support precise O&M decision-making. On the communication side, network infrastructure must be strengthened by expanding bandwidth and deploying high-speed, reliable transmission technologies like fiber-optic communications to build redundant communication links, improving network reliability and anti-interference capabilities.

For example, deploying high-speed industrial Ethernet within substations enables fast data transmission, while optimizing network topology and routing strategies can reduce latency and congestion. Additionally, wireless communication technologies can supplement coverage for remote or temporary monitoring points, ensuring the power monitoring system can acquire and transmit various types of data in real time and accurately, enhancing situational awareness and supporting safe and stable system operation.

3.3 Strengthening Cybersecurity and Information Protection

Given the severe cybersecurity challenges facing smart substation power monitoring systems, a comprehensive, multi-layered security defense system should be established. For network boundary protection, high-performance firewalls, Intrusion Detection Systems (IDS), and Intrusion Prevention Systems (IPS) should be deployed to strictly monitor and filter traffic between external and internal networks, blocking unauthorized access and attacks.

For example, firewalls based on Deep Packet Inspection (DPI) technology can effectively identify and block known and unknown network attacks, including Distributed Denial-of-Service (DDoS) and SQL injection attacks. Meanwhile, internal security authentication mechanisms should be improved by adopting Multi-Factor Authentication (MFA) technologies—such as combining passwords, fingerprint recognition, and dynamic tokens—to rigorously verify user identities, ensuring only authorized users can access the system. Access rights should be allocated based on user roles and responsibilities, restricting operational privileges to prevent internal errors or malicious actions.

For data encryption in transmission and storage, advanced algorithms like AES and RSA should be used to encrypt sensitive information, ensuring confidentiality and integrity during data transfer and storage. Furthermore, a cybersecurity monitoring and emergency response mechanism should be established to monitor system security status in real time, promptly detect and handle security incidents, conduct regular vulnerability scans and patches, and continuously upgrade protection technologies and strategies to counter increasingly complex and evolving cyber threats, safeguarding the information security and stable operation of power monitoring systems.

3.4 Promoting Intelligent Operation and Maintenance Management Systems

To address the increasing complexity of O&M management, efforts should focus on building intelligent O&M management systems. First, a unified O&M platform should be established, integrating functional modules such as equipment status monitoring, data analysis, fault diagnosis, maintenance planning, and remote operations, enabling procedural, standardized, and information-based O&M management.

Through this platform, O&M personnel can access real-time equipment status, leverage big data analytics and AI technologies for accurate fault prediction and rapid diagnosis, and develop scientific maintenance plans in advance, reducing unplanned outages. For example, using historical and real-time operational data, equipment health assessment models can be built, and machine learning algorithms can provide early warnings for equipment failures, offering timely and accurate decision support to O&M staff.

Second, training and skill development for O&M personnel should be strengthened through targeted training programs that familiarize them with the operation and maintenance of various smart substation devices and advanced O&M methodologies, cultivating a high-quality, specialized O&M team. Additionally, technologies such as Virtual Reality (VR) and Augmented Reality (AR) can provide remote assistance and visualized operational guidance, improving O&M efficiency and quality, ensuring the long-term stable and reliable operation of smart substation power monitoring systems, and enhancing the O&M management level and market competitiveness of power enterprises.

3.5 Adopting Advanced Artificial Intelligence and Big Data Technologies

Integrating advanced artificial intelligence (AI) and big data technologies into smart substation power monitoring systems can significantly enhance system performance and intelligence. Big data technologies should be used for efficient storage, management, and analysis of massive power data, uncovering underlying patterns and correlations to support system optimization, fault prediction, and equipment maintenance.

For example, deep analysis of historical operational data can establish load forecasting models to accurately predict load trends, aiding generation planning and grid dispatching, improving system efficiency and economy. At the same time, AI techniques such as machine learning and deep learning algorithms can enable automatic fault diagnosis and intelligent early warnings. By training models on extensive fault samples, the system can accurately identify abnormal equipment states and issue timely alerts, helping O&M personnel quickly locate faults and determine root causes, thus taking effective corrective actions, minimizing downtime, and improving system reliability and stability.

Additionally, AI can be used to optimize control strategies in the monitoring system, enabling intelligent regulation and operational optimization of power equipment, further enhancing overall system performance. This promotes the evolution of smart substations toward greater intelligence and automation, providing solid technical support for the transformation and upgrading of the power industry and meeting societal demands for high-quality power.

4. Conclusion

In summary, smart substations play a crucial role in power monitoring systems, not only enhancing real-time monitoring capabilities and ensuring safe and stable grid operation but also optimizing O&M management. However, current power monitoring systems in smart substations face challenges such as difficult system integration, data processing and communication bottlenecks, inadequate security protection, and complex O&M management.

To address these issues, a series of optimization strategies should be implemented, including improving system integration and standardization, enhancing data processing and communication efficiency, strengthening cybersecurity and information protection, building intelligent O&M management systems, and leveraging AI and big data technologies. These measures are expected to effectively overcome existing problems, fully realize the advantages of smart substation power monitoring systems, improve the reliability, safety, and intelligence level of power systems, promote sustained and stable development in the power industry, and ensure high-quality, efficient power supply.