Enhanced Power Management Research Articles

AI-Driven Hardware Testing: Overcoming the Challenges of Modern Hardware Architecture and Power Management

With the rapid development of hardware technology, the diversity of architectures, the complexity of hardware modules, and the growing demand for real-time capabilities, enhanced power management, adaptability, and flexibility all present new challenges. These challenges include managing the complexity of hardware architecture, performance, and energy efficiency, which traditional testing methods struggle to address effectively. To solve these problems, this paper proposes a new standard for integrating Artificial intelligence with hardware test systems. The system can automatically identify key performance indicators according to the hardware characteristics, dynamically adjust the test strategy, optimize the test process, improve efficiency, and ultimately shorten the time to market.

A transformer-less DC-DC converter for grid-connected PV systems using TSTS-ZSI voltage boost-buck technique

This research introduces an innovative design for a grid-connected photovoltaic (PV) system utilizing a transformer-less DC-DC converter. The converter is based on the TSTS-ZSI (Three-Switch Transformer-less Z-Source Inverter) voltage boost-buck technique, which enhances voltage regulation and energy transfer, making it ideal for micro-inverter applications. The primary goal of the study is to improve energy efficiency while ensuring seamless integration with the grid. The proposed system not only boosts voltage but also ensures efficient buck operation, leading to enhanced power injection into the grid under fluctuating conditions. By utilizing advanced control techniques, the converter minimizes power losses, reduces stress on the components, and maintains stability in a wide range of grid scenarios. Simulations performed using MATLAB/Simulink demonstrate that the converter delivers stable and efficient power with minimal energy loss. The results validate its effectiveness in small-scale grid-connected systems, achieving enhanced power management under various operating conditions. The converter's ability to operate efficiently without a transformer reduces magnetic losses and electromagnetic interference, making it a cost-effective and compact solution. The research presents a valuable contribution to the field of renewable energy integration, with its applications extending to both residential and commercial grid-connected PV systems.'

A Machine Learning-Based Smart Grid Protection and Control Framework Using Kalman Filters for Enhanced Power Management

A Machine Learning-Based Smart Grid Protection and Control Framework Using Kalman Filters for Enhanced Power Management

IoT Sensor Data Retrieval and Analysis in Cloud Environments for Enhanced Power Management

The Internet of Things (IoT) brings new products to everyone to improve daily life. Concurrently other emerging technologies, including Big Data, Cloud Services, and surveillance, can participate through these technological advances. This research work explores the synergies among four systems to identify their shared functionalities and integrate them to create useful potential applications. Despite the limitations of the smart city concept, researchers would seek innovative methods to collect and process sensor information within an IoT-enabled smart building. A cornerstone of the proposed system is the utilization of cloud services as the foundational technology for a schema management platform. This platform efficiently gathers data generated by sensors within smart industrial units. Leveraging the capabilities of IoT technology, the data can be remotely managed and accessed using mobile devices with network connectivity. The proposed work addresses the challenges related with the smart city perception and supports for revolutionary approaches in the collection and manipulation of IoT Sensor data. By doing so, it imagines the creation of green, smart schemes that contribute to sustainable urban development.

IoT Sensor Data Retrieval and Analysis in Cloud Environments for Enhanced Power Management

The Internet of Things (IoT) brings new products to everyone to improve daily life. Concurrently other emerging technologies, including Big Data, Cloud Services, and surveillance, can participate through these technological advances. This research work explores the synergies among four systems to identify their shared functionalities and integrate them to create useful potential applications. Despite the limitations of the smart city concept, researchers would seek innovative methods to collect and process sensor information within an IoT-enabled smart building. A cornerstone of the proposed system is the utilization of cloud services as the foundational technology for a schema management platform. This platform efficiently gathers data generated by sensors within smart industrial units. Leveraging the capabilities of IoT technology, the data can be remotely managed and accessed using mobile devices with network connectivity. The proposed work addresses the challenges related with the smart city perception and supports for revolutionary approaches in the collection and manipulation of IoT Sensor data. By doing so, it imagines the creation of green, smart schemes that contribute to sustainable urban development.

Fully integrated LDO based on push-pull circuitry for enhanced power management in embedded systems

Fully integrated LDO based on push-pull circuitry for enhanced power management in embedded systems

Fully Integrated LDO based on Push-pull Circuitry for Enhanced Power Management in Embedded Systems.

Fully Integrated LDO based on Push-pull Circuitry for Enhanced Power Management in Embedded Systems.

Techno-economic configuration of a hybrid backup system within a microgrid considering vehicle-to-grid technology: A case study of a remote area

This paper assesses the feasibility of the hybrid backup system within the microgrid that incorporates vehicle-to-grid (V2G) technology. The proposed strategy is verified through a real case study in a remote area of Egypt. Several operating configurations for the hybrid backup system are studied. In this study, the proposed backup sources are the battery energy storage system (BESS), the hydrogen energy storage system (HESS), and the electric vehicle battery (EVB). To improve the robustness and reliability of the system, an enhanced power management strategy for the hybrid backup system is implemented. The main objectives are to minimize the operational costs, the wasted energy in the dummy load, and the loss of power supply probability (LPSP). The optimization problem is performed using the african vultures optimization algorithm (AVOA). The results clearly indicate that the proposed AVOA outperforms other recent algorithms, specifically the reptile search algorithm (RSA) and the snake optimizer (SO). The AVOA shows a 14.377 % reduction in computational time compared to the RSA, while it is nearly equal to the computational time of SO. Based on the technical and economic analysis, the configuration that combines the three backup sources has superiority over the other configurations. When using AVOA, the cumulative operating cost throughout the day for this configuration is approximately 13066.21$. The BESS/EVB backup system has an operating cost of 13120.66 $, while the BESS/HESS and BESS backup systems have operating costs of 13084.27 $ and 13,085 $, respectively. Regarding accuracy, the three algorithms achieve close results.

Multilevel Dynamic Master-Slave Control Strategy for Resilience Enhancement of Networked Microgrids

Conventional power management methods of networked microgrids (NMGs) are limited to the failure of pinned communication terminals and heavy communication burdens. This paper proposes a multilevel dynamic master-slave control strategy via two-level dynamic leaders to realize the resilience enhanced power management of NMGs. The first level dynamic leader with considerations of distributed energy resources (DERs) feature is selected to guide the output of DERs and achieve the power management within individual microgrid (MG). Subsequently, the secondary level leader considering each MG feature is selected among the bidirectional interlinking converters (BICs), whose signals would be shared with other BICs by communication to achieve power management among MGs. Moreover, the local weight selecting method (LWSM) is proposed to automatically select the two-level dynamic leaders according to the real-time system operation state. Compared with conventional methods, the communication among MGs is essentially realized through the dynamic DER leaders instead of pinned ones. Therefore, unreliability issues in the event of pinned terminal outage and converters’ communication failure can be fully addressed and the communication bus within each only needs to transmit one DER’s signals. The proposed strategy can be also extended to NMGs with various topologies and provide the “plug and play” capabilities of DERs or MGs. Finally, the effectiveness and feasibility of the proposed strategy are verified through the PSCAD/EMTDC platform.

A novel PWM scheme for grid-tied inverter in micro-grid with enhanced power quality using silicon cells

This paper presents a cost effective solution to reduce harmonics and improved power factor in grid tied inverter by varying the control pulses instead of using hardware components like filtering and multilevel inverter. A two-level inverter is taken for simulation study and a new pulse width modulation method is proposed by tying altered space vector pulse width modulation method and hysteresis current control. This novel scheme provides low harmonic content, improved power factor, enhanced power management, enriched storage and maxim extraction of power. The simulation work of grid-tied inverter integrated with micro-grid is carried out with MATLAB/Simulink 2018 and the performance of the proposed novel pulse width modulation approach is analysed in terms of harmonics content in output current.

SECURE AND SUSTAINABLE SMART GRID FRAMEWORK USING THE CLOUD COMPUTING

The smart grid developments turning out to a promising technology for the two way communication of the electricity and the information are becoming more prominent in the present scenario due to the increasing demands in the power requirements. The smart grid utilizing the modern communication and the computing infrastructure makes this possible. This utilization of the modern communication and the computing systems make them even prone to the vulnerabilities, mishandlings and the miscommunications and necessary for a complex frame work for managing of the power distribution and generation to make them sustainable. So the paper proposes the cloud computing for the proper management and the protection of the smart grids to make them more secure against threats and sustainable by reducing the Co2 emission by the perfect management. The validation of the smart grid frame work using cloud computing by monitoring the power distribution, management and the security achieved over multiple usages show the enhanced power management and the security services provided by the cloud for the smart grid.

Enhanced power management scheme for embedded road side units

In this study, a green vehicular ad-hoc network (VANET) infrastructure is suggested. The main players in such an infrastructure are the road side units (RSUs) which are able to harvest the energy needed for their work from the surrounding environment, especially the solar energy. Such a suggestion permits to install the RSUs in any place without considering the power supply availability and hence, an extensive area is covered by the VANET infrastructure with an improved performance. To achieve this goal, a new distributed power management scheme called duty cycle estimation-event driven duty cycling is suggested and installed locally in the RSUs in order to decrease their power consumption and to extend the lifetime of their batteries. Embedded UBICOM IP2022 network processer platform is adopted to implement the proposed RSU and the detailed design steps are described, while the necessary values of the system components such as the number of solar cell panels, battery cells capacity and so on, are tuned to suit the design goals. The suggested method is compared with other duty cycling methods to show its effectiveness to build a green VANET infrastructure.

Dynamic power management in Wi-Fi Direct for future wireless serial bus

This paper presents a performance analysis of Wi-Fi Direct power management schemes and exploits their problems to design a novel, enhanced power management for future wireless USB (WSB) applications. Wi-Fi Direct will become a key technology for the support of future WSB services that require high standards of service quality and power efficiency at the same time. To provide this, Wi-Fi Direct defines two power management schemes, opportunistic power save mode and notice-of-absence. Even though each scheme has its own characteristics and advantages, specification does not have any definition of how to select the schemes and its parameters based on the type of WSB application being serviced. We analyze the properties of the two power management schemes of Wi-Fi Direct, and discover that their performance can greatly vary depending on the number and type of WSB applications that is being transmitted in the network. To solve this problem, we propose a novel power saving algorithm that can dynamically change the power management of Wi-Fi Direct. Our work is extensively evaluated using the Wi-Fi Direct module implemented in the NS-3 simulator.

Enhanced power management unit for the Artificial Accommodation System

Article Enhanced power management unit for the Artificial Accommodation System was published on September 7, 2013 in the journal Biomedical Engineering / Biomedizinische Technik (volume 58, issue SI-1-Track-O).