Talabartuka da Yadda Ake Zama Ilimin Kirkiro Noma na Gwamnati na Tsawon Karkashin Noma

Ga wata tushen karkashin kungiyar zuwa nafin kai, an samun kungiyar da take daidai ne ya zama batu mai muhimmanci a cikin kungiyar zuwa. Da kungiyoyin kai na yankin da ke rage-rage, samun kungiyar da take daidai masu kai da kaza da harufa ta shirya damar kai na yankin. Wannan modeli yana taimaka waɗanda suke amfani da kai, yana haifar da kasa na kungiyar, yana haifar da kusa da kungiyar, kuma yana taimaka waɗanda suke amfani da kungiyar.

Idan kuna neman littattafan kungiyar, in ba da kyau a gudanar da kungiyoyin kungiyar. Karamin kungiyar na zamani suna bukatar harkokin kawo da kungiyar da kusa mafi inganci, musamman a lokacin da kuna samu kungiyar da take daidai. Don bayyana wannan abubuwa, an samu kungiyoyin kawo da kungiyar mai sauƙi, wadanda ke amfani da takardukan ma'a fahimtar gwamnati don in ba da kawo da kungiyar a baya. Littafin ya kaddamar da kungiyoyin kawo da kungiyar da kusa mafi inganci a cikin kungiyar da take daidai, tare da in taimaka waɗanda suke amfani da kungiyar da kusa mafi inganci don in ba da damar kai na yankin.

1. Kawo da Kungiyar
Kawo da kungiyar yana da muhimmanci a kan in ba da kawo da kungiyar a baya, in ba da bayanan kungiyar, kuma in ba da kawo da kungiyar. Kungiyoyin kawo da kungiyar yana da data acquisition units, data transmission networks, monitoring and management platforms, kuma alarm and response mechanisms. Data acquisition units yana ba da bayanan kungiyar daga kungiyoyin kungiyar—masu kungiyar, transformers, kuma distribution devices—kafin kusan parametoli masu muhimmanci kamar voltage, current, frequency, kuma power factor.

Bayanan da aka ba yana ba da ita tun daga data transmission networks (e.g., fiber optics, wireless transmission) zuwa center of monitoring. Data transmission network mai sauƙi yana ba da kawo da bayanan a baya, tare da in ba da damar bayanan, tare da in ba da kawo da kungiyar. Platform of monitoring and management yana ba da kawo da bayanan a baya, kuma yana amfani da takardukan ma'a fahimtar gwamnati don in ba da interfaces da kawo da kungiyar, tare da in taimaka waɗanda suke amfani da kungiyar a yi kawo da kungiyar.

2. Tushen System

2.1 Tushen Architecture

Tushen architecture na intelligent power monitoring system yana cikin Table 1.

A cikin tushen architecture na intelligent power monitoring system, functions of each layer yana kammala da key technologies, tare da in ba da framework mai sauƙi. Perception layer yana ba da bayanan a baya tun daga sensors and smart meters, tare da in ba da foundation and prerequisite for system functionality. Accuracy and timeliness of data yana haifar da kawo da kungiyar da kusa mafi inganci.

Network layer yana da muhimmanci a kan in ba da kawo da bayanan, tare da in ba da data transmission hub, tare da in ba da kawo da bayanan a baya. Yana amfani da optical fiber networks and wireless communication don in ba da kawo da bayanan a baya. Yana haifar da integrity and security of data, tare da in ba da kawo da kungiyar. Application layer yana da muhimmanci a kan in ba da kawo da bayanan a baya, tare da in ba da kawo da kungiyar, tare da in ba da kawo da kungiyar.

2.2 Hardware Selection

System hardware components and their main performance parameters yana cikin Table 2.

2.3 Data Communication Strategy

2.3.1 Data Collection and Transmission

Data collection and transmission yana da muhimmanci a cikin intelligent power monitoring system, tare da in ba da kawo da kungiyar. A cikin wannan process, various sensors and monitoring devices in the perception layer yana ba da bayanan kungiyar daga kungiyoyin kungiyar—kamar voltage, current, power, and frequency—kuma information on operational status from distributed generation sources.

Don in ba da kawo da kungiyar, acquisition devices yana da muhimmanci a kan in ba da high precision and high reliability [10]. Bayanan da aka ba yana ba da ita tun daga network layer, tare da in ba da modern communication technologies such as fiber optic communication, wireless communication, and Internet of Things (IoT) technologies. Fiber optic communication, with its high bandwidth and low latency, is suitable for large-scale data transmission scenarios. Wireless communication offers flexibility and convenience, effectively covering various monitoring points through wireless signals.

2.3.2 Security Measures

In intelligent power monitoring systems, security measures such as data encryption, network security protection, and access control form a multi-layered security framework. This framework effectively mitigates external attacks and internal risks, laying a secure foundation for the implementation of intelligent power management. Implementing strong encryption algorithms during data transmission prevents data from being intercepted or tampered with. The use of symmetric encryption algorithms such as the Advanced Encryption Standard (AES) ensures that only users with the correct decryption key can access the data, thereby protecting the integrity and confidentiality of sensitive information and ensuring that data remains unaltered during transmission. Regarding network security protection, the interconnection of multiple devices and systems significantly increases the risk of cyberattacks. Therefore, deploying security devices such as firewalls, Intrusion Detection Systems (IDS), and Intrusion Prevention Systems (IPS) enables real-time monitoring of network traffic, identification, and blocking of suspicious activities, preventing malicious attacks from affecting the system and enhancing overall security. User access control and authentication mechanisms, such as Role-Based Access Control (RBAC), ensure that only authorized users can access specific system functions and data. This reduces the risk of internal data leaks, improves system security, and effectively prevents unauthorized access.

3. Research Methodology

3.1 Research Design

This study adopts a combined approach of experimental and simulation methods, integrating real-world electricity market data with simulated power demand to construct multiple experimental scenarios.

These scenarios enable comprehensive testing and evaluation of the system. In the experimental design, system performance evaluation primarily focuses on metrics such as scheduling efficiency, resource utilization, and response time. By configuring different loads, resource allocations, and generation modes, the system’s performance under various operating conditions is simulated.Security evaluation, on the other hand, focuses on the system's resilience against unexpected events such as cyberattacks, system failures, and data breaches.

To comprehensively assess the performance of the intelligent power monitoring system, a scientific evaluation framework and indicator system were designed, encompassing performance metrics—including response time, scheduling success rate, resource utilization, and system stability—and security metrics—such as intrusion detection rate, vulnerability patching time, and data encryption strength.

3.2 Performance Evaluation

The performance evaluation of the intelligent power monitoring system in optimized control of distributed generation is shown in Table 3.

The security evaluation metrics in Table 4 provide comprehensive protective measures for the intelligent power monitoring system. These metrics cover aspects such as data encryption, intrusion detection, access control, vulnerability remediation, and malware protection, ensuring the system can effectively respond to potential threats including cyberattacks, data breaches, and malicious software.

For example, the data encryption level requires the use of AES-256 or higher encryption standards to ensure the security of data transmission and storage; the intrusion detection rate target is above 95%, ensuring the system can promptly identify and respond to abnormal access or attack behaviors. Access control effectiveness must achieve 100% compliance, ensuring user permission management strictly adheres to security policies. The target for security vulnerability remediation time is within 24 hours, enabling rapid resolution of identified vulnerabilities.

4. Experimental Results

4.1 Performance Test Results

The performance test results are shown in Table 5.

In this performance test, all system metrics performed well, meeting or exceeding the preset target values. The system’s response time was 1.8 s, satisfying the <2.0 s requirement, indicating high scheduling efficiency. The data processing speed reached 2,200 records per second, surpassing the 2,000 records/s requirement, demonstrating strong real-time data processing capability. System availability was 99.98%, higher than the 99.95% target, reflecting excellent stability and reliability. Energy loss rate was 2.5%, below the 3.0% target, optimizing power transmission efficiency. Optimization scheduling success rate reached 92%, effectively supporting the system's dispatch objectives. Fault recovery time and resource utilization were 4 minutes and 87%, respectively—both outperforming the established standards—demonstrating the system’s fast recovery capability under faults and efficient resource utilization. The results indicate that the intelligent power monitoring system exhibits strong overall performance in the optimized control of distributed generation.

4.2 Security Test Results

The security test results are shown in Table 6.

In the security testing, the system demonstrated a high level of protection, with all security metrics meeting or exceeding the expected targets. The data encryption level employs the AES-256 algorithm, complying with the highest standards and ensuring the security of data transmission and storage. The intrusion detection rate reached 97%, surpassing the 95% requirement, indicating the system’s ability to effectively identify and respond to potential cyberattacks.

The access control policy also performed excellently, with 100% compliance in all user permissions and access behaviors. The system achieved vulnerability remediation within 18 hours after detection, significantly faster than the 24-hour target, enhancing its responsiveness to emerging security threats. Additionally, testing of the system’s data backup and recovery strategy showed that both backup and recovery processes were completed successfully at a 100% success rate, further improving data security and business continuity. The intelligent power monitoring system performs exceptionally well in terms of security, demonstrating robust and effective protection capabilities.