Optimizatio Designis Systematum Monitorationis Intelligentiae Potentiae pro Generatione Distributiva

Contra fundum transitionis energiae globalis, generatio distributa iam fit component vitalis supply electricitatis. Cum progressibus continuis technologiis energiarum renovabilium, adoptions diffusa fontium energeticae distributae, sicut solaris et venti, novum momentum in realizationem economiae low-carbon injectavit. Hic modelus utilisationem efficientiam energeticae augescit, perditas transmissionis minuit, et flexibilitatem ac fiduciam systematum electricitatis meliorat.

Secundum theoria systematis electricitatis, fides et stabilitas rete multum dependet ex management efficaciter diversorum fontium generationis. Complexitas systematum electricitatis modernorum postulat control plus exactus et dispatch intra ambientes generationis distributae—praesertim inter fluctuationes crescentes onerum et incertitudinem resourciorum. Ad haec difficultates obviam ire, systemata monitoring intelligentia electricitatis emergent, utentes technologiis informationis et communicationis avancatas ad supervisionem real-time et adjustmentem dynamicam resourciorum electricitatis facere. Hoc scriptum explorationem design systematorum monitoring intelligentia electricitatis et control optimizatus in generatione distributa facit, ad contribuendum ad transitionem energiae et adiectionem metarum developmentis sustinabilis.

1. Monitoring Electricitatis
Monitoring electricitatis est methodus critical ad supervisionem real-time, acquisitionem datarum, et analysis operationum systematis electricitatis, ad securitatem, fiduciam, et efficientiam systematis electricitatis assecurandam. Systema monitoring electricitatis primarie constat unitatum acquisitionis datarum, retium transmissionis datarum, platformarum monitoring et management, et mechanismorum alarmis et responsionum. Unitates acquisitionis datarum collectant data operational de variis equipmentis electricitatis—sicut generatoribus, transformatoribus, et dispositivis distributionis—includens parametra claves sicut tensionem, currentem, frequentiam, et factor power.

Data collecta tunc transmittitur via retium communicationis stabilibus et securis (exempli gratia, fibra optica, transmission wireless) ad centrum monitoring. Retium transmissionis datarum efficiente tempore et integritate informationis assecurat, fundamentum fidum pro subsequente analysis praebens. Platforma monitoring et management conductionem real-time et analysis datarum acquisitionis factam agit, utentes technologias sicut analytics big data et computatio nubis ad interfaces visualizatos et support decisionum praebentes, auxiliantes operatores in decisionibus effectivis faciendis.

2.Design Systematis

2.1 Architectura Systematis

Architectura systematis monitoring intelligentia electricitatis in Tabula 1 ostenditur.

In architectura systematis monitoring intelligentia electricitatis, functiones cuiusque strati complement suas respectivas technologias claves, efficiens framework operationalem formantes. Stratum perceptionis datarum real-time per sensors et smart meters acquire, fundamentum et praerequisitum ad functionality systematis servans. Accuratia et temporalitate datarum directe affectant qualitatem subsequentis analysis.

Stratum reticuli agit ut hub transmissoris datarum, utentes technologias avancatas sicut fibrae opticae et communicatio wireless ad data celeriter et fideliter ad centrum monitoring transmittenda. Debet etiam integritatem et securitatem datarum assecurare, preveniens perditas vel alterationes durante transmissione. Stratum applicationis responsibile est pro analysis profunda datarum et visualization, utentes algorithmos processing data avancatos et technologias big data ad magnas collectiones datarum in insight valentes transformandas, adiuvantes managers in decisiones precisas faciendas.

2.2 Selectio Hardware

Componentes hardware systematis et eorum parametri performance principales in Tabula 2 ostenduntur.

2.3 Strategia Communicationis Data

2.3.1 Collectio et Transmissio Data

Collectio et transmissio data sunt componentes core systematis monitoring intelligentia electricitatis, directe influentes in performance real-time et effective systematis. In hoc processu, variis sensoribus et dispositivis monitoring in strato perceptionis collectant data key operationum systematis electricitatis—sicut tensionem, currentem, power, et frequentiam—as well as operational status information from distributed generation sources.

Ad accuratiam datarum assecurandam, dispositiva acquisitionis debent altam precisionem et fiduciam habere [10]. Post collectionem, data transmittitur ad stratum reticuli, principaliter utentes technologias communicationis modernas sicut fibra optic communication, wireless communication, et Internet of Things (IoT) technologies. Fibra optic communication, cum suo bandwidth alto et latency bassa, apta est ad scenaria transmissionis datarum larga scala. Wireless communication offert flexibilitatem et commoditatem, effective covering various monitoring points through wireless signals.

2.3.2 Measures Security

In systematis monitoring intelligentia electricitatis, measures security sicut encryption data, protection network security, et access control formant framework security multilayered. Hic 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. Methodology Research

3.1 Design Research

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.