Reliability Benefits Research Articles

The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks

The selection of the optimal 35 kV network structure is crucial for modern distribution networks. To address the problem of balancing investment costs and reliability benefits, as well as to establish the target network structure, firstly, the investment cost of the distribution network is calculated based on the determined number of network structure units. Secondly, reliability benefits are measured by combining the comprehensive function of user outage losses with the System Average Interruption Duration Index (SAIDI). Then, a multi-objective planning model of the network structure is established, and the weighted coefficient transformation method is used to convert reliability benefits and investment costs into the total cost of power supply per unit load. Finally, by using the influencing factors of the network structure as the initial population and setting the minimum total cost of the unit load as the fitness function, the DE algorithm is employed to obtain the optimal grid structure under continuous load density intervals. Case studies demonstrate that different load densities correspond to different optimal network structures. For load densities ranging from 0 to 30, the selected optimal network structures from low to high are as follows: overhead single radial, overhead three-section with two ties, cable single ring network, and cable dual ring network.

Maintaining reliability in a 100% decarbonized power sector: The interrelated role of flexible resources

Reliability will remain a key requirement for decarbonized power sectors, but also a concern with the high penetration of variable renewable energy (VRE). The traditional approach for reliability is by producing enough energy and adapting rapidly to changes in load with the dispatch of fossil fuel power plants, especially natural gas power plants. However, this will have to evolve as decarbonization progresses. Can various flexibility resources such as transmission, storage and demand response provide the same reliability benefits? This paper uses a detailed, capacity expansion and hourly operation model to investigate the possibility and the cost of reaching different levels of planning reserve margins (PRM), in the multi-regional context of the North American Northeast. We find that while it is possible to entirely avoid natural gas power plants or nuclear ones to obtain high PRM, it would come at a very high cost and would require high levels of transmission, storage and demand response. We also detail why these three flexibility resources are needed in combination. The implications for energy policies are significant: in order for power system's cost to remain reasonable, reliability must count on some carbon-neutral natural gas or nuclear generation, along with interties with neighboring systems, storage and high levels of demand response.

Multi-objective Approach for Dynamic Economic Emission Dispatch Problem Considering Power System Reliability and Transmission Loss Prediction Using Cascaded Forward Neural Network

This study addresses the significant problem of Dynamic Economic Emission Dispatch (DEED), a critical consideration in power systems from both economic and environmental protection viewpoints. Reliability stands as another vital facet, impacting maintenance and operation perspectives. The integration of Artificial Neural Network (ANN)-based transmission loss prediction into the DEED model is also essential to address specific limitations and enhance the overall performance of the dispatch process. Traditionally, the DEED model relies on a single B-loss coefficient to estimate transmission losses. While this approach simplifies calculations, it fails to account for the significant variations in demand that occur throughout the dispatch period and it leads to inaccuracies in loss prediction, especially in dynamic environments. Using a single coefficient, the model cannot adequately capture the complex, non-linear relationships between power generation, load, and transmission losses under different operating conditions. To overcome this limitation, this study introduces an ANN-based loss prediction method integrated into the DEED model and uses trained ANN to replace the process of finding B-loss coefficients during each dispatch period. This paper also introduces a strategy leveraging the multi-objective northern goshawk optimizer algorithm, characterized by a non-dominated sorting and crowding distance mechanism, to enhance DEED considerations incorporating reliability (DEEDR). This novel algorithm improves the solution space effectively, maintains high population diversity and enables an even distribution of individuals sharing the same rank in the objective space. The fundamental objective of this study is to balance fuel cost, emission, and system reliability in power system operations. Compared with a few existing multi-objective optimization algorithms, this study demonstrates superior performance in generating a series of non-dominated solutions. The experimental results highlight its competitive and potential as an efficient tool in the DEED and DEEDR problems, promising a synergistic coordination of economy, environmental protection, and system reliability benefits in power system management.

Software-defined optical networking applications enabled by programmable integrated photonics

Data center networks are experiencing unprecedented exponential growth, mostly driven by the continuous computing demands in machine learning and artificial intelligence algorithms. Within this realm, optical networking offers numerous advantages, including low latency, energy efficiency, and bandwidth transparency, positioning it as a compelling alternative to its electronic counterparts. In this work, we showcase a range of software-defined optical networking applications deployed on a general-purpose programmable integrated photonic processor. Leveraging graph-based theory, we experimentally demonstrate dynamic optical interconnects, circuit switching, and multicasting on the same photonic platform, yielding remarkable results in terms of crosstalk and reconfiguration speed. Our approach harnesses the benefits of reconfigurability and reliability, paving the way for a new generation of high-performance optical devices tailored for data center and computing clusters.

Effect of lead-free solder thermal interface material thickness on the reliability of electronic components in a random vibration environment

The reliability of electronic components has persistently posed challenges for engineers. This study addresses the critical need of understanding the impact of random vibration on the reliability of lead-free solder as thermal interface materials (TIM) within electronic components. ANSYS software was deployed to design, develop, and simulate the electronic model, with a focus on the TIM. SAC405 lead-free solder served as the TIM, its thickness was varied between 0.01 to 0.06 mm (at 0.01 mm intervals). The results from this investigation reveal relevant correlations. As the TIM thickness increases, there's a noticeable reduction in stress and strain while the deformation increases. Remarkably, a direct relationship emerges between TIM thickness and fatigue life; thicker TIM correlates with increased fatigue life. In addition, at a TIM thickness of 0.01 mm, the fatigue life measurements were 2.76 x 104, 1.63 x 104, and 0.792 x 104 for Equations 1, 2, and 3, respectively. These findings carry profound implications for engineers, serving as a guiding framework to aid in the selection of optimal TIM thickness for electronic components if lead-free solders are used as TIM. Understanding these trade-offs between stress, strain, deformation, and fatigue life is pivotal, empowering engineers to make informed decisions during electronic system design and development, ultimately enhancing overall reliability. Using lead-free solders as TIM in electronic applications is proposed by this study due to the thermal and reliability benefits presented.

Deep Learning Based Cooperative MIMO Systems for Wireless Body Area Networks

Wireless Body Area Network (WBAN) is widely applied in various fields, including healthcare, sports, wellness, and assistive technologies, by offering the benefits of convenience, reliability, low latency, privacy, and customization. However, the propagation characteristics of the WBAN channel can impact the reliability of transmission, which is particularly crucial in healthcare systems. To address this issue, this article presents a novel approach using deep learning-based cooperative Multiple-Input Multiple-Output (MIMO) systems that leverage the autoencoder (AE) technique. In our proposed approach, we utilize the AE-based cooperative MIMO systems with two different techniques: Amplify-and-Forward (AE-AF) and Decode-and-Forward (AE-DF). The AE-AF scheme operates without needing training parameters at the relay node, whereas the AE-DF scheme necessitates training parameters at the relay node. Both schemes aim to overcome challenges such as multipath propagation phenomena, thereby enhancing the performance of on-body communication systems. Additionally, we introduce two combinators, Minimum Mean Square Error (MMSE) scheme and Radio Transformation Network (RTN), to effectively mitigate co-channel interference (CCI) in the received signal streams and improve the bit error rate performance of the AE-AF and AE-DF systems. We assess the performance of these systems in scenarios with and without direct links. Simulation results demonstrate significant performance improvements compared to baseline cooperative MIMO systems using MMSE combining, namely AF-MMSE and DF-MMSE systems. Notably, the proposed systems employing RTN combination, including both direct and relay paths, achieve a 7.5 dB gain over the baseline when all nodes are equipped with two transceiver antennas.

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Efficiency in the Last Mile of Autonomous Ground Vehicles with Lockers: From Conventional to Renewable Energy Transport

This research aims to compare autonomous ground vehicles with conventional and electric vans on the basis of associated vehicle costs and benefits related to their use, taking into account economic feasibility. Cost per vehicle kilometre is derived using the total cost of ownership method adjusted with the inclusion of labour costs and the impact of solar panel application on fuel efficiency while travel time-related and capacity occupations and reliability benefits serve as a basis for the total possible number of parcels delivered. The results show that, under the current structural and infrastructural conditions of urban delivery, the experimental model can be potentially successful in terms of cost per kilometre (0.133/km) but not as effective in terms of the total possible number of parcels delivered. This study defines autonomous ground vehicles with lockers as an innovative last mile solution and contributes to the academic literature by investigating the concept’s efficiency competitiveness.

Reaping Both Latency and Reliability Benefits With Elaborate Sanitization Design for 3D TLC NAND Flash

With the rising security concern on modern storage systems, the concept of data sanitization has been widely investigated recently. Among the existing works targeting data sanitization, an overwriting-based approach, namely one-shot sanitization, is one of the most efficient sanitization approaches. Nonetheless, we find that the one-shot sanitization approach would fail to achieve precise data sanitization for 3D TLC NAND flash, because of incurring undesired data errors. That is, how to simultaneously realize precise sanitization and high security with decent latency and reliability on emerging storage devices remains unsolved. This work proposes an elaborate sanitization design that skillfully manipulates the threshold voltage ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V_{t}$</tex-math></inline-formula> ) distribution of sanitized pages. Not only does the proposed design achieve precise sanitization and high security, but it also enhances read performance and data reliability. Specifically, this work elaborately sanitizes data by merging specific <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V_{t}$</tex-math></inline-formula> distributions of the target physical page on 3D TLC NAND flash. Besides, the proposed approach further takes lateral charge migration into consideration to improve data reliability. We conduct a series of experiments to evaluate our proposed approach on real 3D TLC NAND flash. The experiment results demonstrate the proposed approach can achieve elaborate data sanitization under various scenarios and improve read performance by 29%.

Multi-Intensity Planes Constellation and Code Design-Based Color-Shift Keying for Visible Light Communications

In this study, we develop multi-intensity planes color-shift keying (MIP-CSK) constellations to determine the effect of the MIP-based CSK design scheme on the reliability of visible light communication systems under the constraint of target color constraint. Based on a two-dimensional triangle partition constellation plane, we introduce algorithms to design the non-integral powers of two MIP-CSK constellations in three-dimensional symbol space by using set partition and intensity plane levels, which improves the minimum Euclidean distance. We then develop a coding scheme by designing an finite-state machine from the non-integral powers of two constellations to further improve the reliability under the white color constraint. Subsequently, by considering the spatial symmetric nature of the triangle partition constellation distribution, we study the design strategy of powers of two constellation symbols and further propose the powers of two MIP-CSK design scheme in a three-dimensional symbol space. Moreover, we investigate the reliability benefit obtained by set partition and optimal intensity levels for powers of two MIP-CSK constellations by improving the normalized minimum squared distance. The simulation results indicate that the error performance of the proposed new family of MIP-based design schemes outperforms its counterparts while complying with the white color constraint at the high signal-to-noise ratios.

Aggregate Modeling of Thermostatically Controlled Loads for Microgrid Energy Management Systems

Second-to-second renewable power fluctuations can severely hinder the frequency regulation performance of modern isolated microgrids, as these typically have a low inertia and significant renewable energy integration. In this context, the present paper studies the coordinated control of Thermostatically Controlled Loads (TCLs) for managing short-term power imbalances, and their integration in microgrid operations through the use of aggregate TCL models. In particular, two computationally efficient and accurate aggregate TCL models are developed: a virtual battery model representing the aggregate flexibility of TCLs considering solar irradiance heat gains and wall/floor heat transfers, and a frequency transient model representing the aggregate dynamics of a TCL collection considering communication delays and the presence of model uncertainty and time-variability. The proposed aggregate TCL models are then used to design a practical Energy Management System (EMS) integrating TCL flexibility, and study the impact of TCL integration on microgrid operation and frequency control. Computational experiments using detailed frequency transient and thermal dynamic models are presented, demonstrating the accuracy of the proposed aggregate TCL models, as well as the economic and reliability benefits resulting from using these aggregate models to integrate TCLs in microgrid operations.

A Micro-Nuclear Power Generator for Space Missions

The significance of reliable energy storage systems in spacecraft applications cannot be overstated, since they play a vital role in ensuring continuous power supply and prolonged mission durations. This research deals with the modeling of a hybrid multi-mission radioisotope thermoelectric generator (MMRTG)-lithium-ion (Li-ion) battery integrated energy storage system for spacecraft applications to combine the RTGs’ long lifespan and reliability benefits alongside the Li-ion battery’s rechargeability and high energy density to achieve a single energy unit. The investigation’s main problem was exploring a power unit that improves the limitations of MMRTG and Li-ion batteries to achieve a highly efficient and reliable power supply for autonomous systems, such as a spacecraft. The proposed hybrid system comprises a 110 W/32 V RTG and a 3.6 V/43 Ah Li-ion battery connected to a DC motor through power converters. Results demonstrate the potential of the adopted hybrid energy system in improving the efficiency, reliability, and mission duration of spacecraft missions. The assessment of the hybrid energy system under various load conditions shows that the highest power peak of 3500 W was achieved at a load resistance of 1 Ω. Furthermore, the results show that the hybrid energy system output voltage at temperatures of 253 °K and 293 °K are relatively equal. However, the power cycle was wider and required a long time before dropping.

Reliability Framework Integrating Grid Scale BESS Considering BESS Degradation

To ensure the future networks’ secure and flexible operation, NOs will increasingly rely upon grid-scale storage services as a secondary (ancillary) service. During critical contingencies, NOs may drive some battery energy storage systems (BESS) that operate at higher depth-of-discharge cycles for increasing reliability benefits. This eventually could lead to accelerated degradation of BESS. The reliability benefits versus the accelerated BESS degradation risks over the BESS lifetime are not deeply investigated in the up-to-date literature. This paper develops a reliability evaluation framework integrating a Bi-Level Sequential Monte Carlo loops with a detailed BESS degradation model. The integration captures the BESS normal and accelerated cycle and capacity degradation across a multi-year network analysis. Annualized indices are defined for assessing the risks of BESS accelerated degradation named as expected equivalent life cycle accelerated degradation (EELCAD), expected equivalent capacity degradation (EECD) and expected battery accelerated degradation costs (EBADC). In addition, it provides a techno-economic assessment of reliability benefits versus the degradation risks over the battery’s lifetime. Therefore, the paper presents an in-depth analysis of the benefits and risks associated with battery degradation and the potential implications in long-term planning studies.

Collaboration to improve cross-race face identification: Wisdom of the multi-racial crowd?

Face identification is particularly prone to error when individuals identify people of a race other than their own - a phenomenon known as the other-race effect (ORE). Here, we show that collaborative "wisdom-of-crowds" decision-making substantially improves face identification accuracy for own- and other-race faces over individuals working alone. In two online experiments, East Asian and White individuals recognized own- and other-race faces as individuals and as part of a collaborative dyad. Collaboration never proved more beneficial in a social setting than when individual identification decisions were combined computationally. The reliable benefit of non-social collaboration may stem from its ability to avoid the potential negative outcomes of group diversity such as conflict. Consistent with this benefit, the racial diversity of collaborators did not influence either general or race-specific face identification accuracy. Our findings suggest that collaboration between two individuals is a promising strategy for improving cross-race face identification that may translate effectively into forensic and eyewitness settings.

Grid-Forming Control of Wind Turbines for Diode Rectifier Unit Based Offshore Wind Farm Integration

Offshore wind farms are the main trend of future wind power exploitation. The diode rectifier unit (DRU) shows great potential in offshore wind power integration due to its economy and reliability benefits, and stable AC voltage control of the offshore gird is the key technology of the DRU based scheme. In this paper, the sensitivities of the DRU based system are defined and the sensitivity calculation method is proposed. According to the sensitivity characteristics analysis, the relationship between the wind turbine (WT) active power (or reactive power) and the WT output voltage (or system frequency) is clarified. On this basis, a grid-forming control strategy for WT converters is proposed. The stable operation mechanism of the grid-forming WTs in the DRU based system is demonstrated according to the analysis of steady state operation point existence and small disturbance stability. The time domain simulations of two DRU based offshore wind farm integration systems are carried out in PSCAD/EMTDC, and the feasibility of the proposed grid-forming control is verified.

Comparative Analysis of Traffic-Reduction Techniques for Seamless CAN-Based In-Vehicle Network Systems

Due to the benefits of better bandwidth and reliability, the automotive industry is moving towards Ethernet-based in-vehicle network (IVN) systems as the number of onboard electronic control units has increased. Considering that before long the well-known controller area network (CAN) will still be considered a standard protocol, our earlier work introduced a high-availability seamless redundancy (HSR)-based Ethernet network architecture that provides IVNs with fault tolerance, called seamless CAN. However, HSR is known for its redundant traffic generated for fault tolerance, which is a disadvantage in bandwidth-limited IVN systems. Therefore, in this paper, we propose a traffic-effective architecture for seamless CAN-based networks. We compared the proficiency of different traffic-reduction approaches as they were applied to our proposed architecture. Extensive simulation results showed that our proposed solution could reduce up to 54% of the total network traffic compared to a conventional architecture while still being able to guarantee a high level of fault tolerance.

A New 29-Level Switched-Diode Multilevel Inverter with Optimal Device Count

A novel single-phase 29-level asymmetrical switched-diode multilevel inverter (MLI) topology is presented in this paper with a reduced number of components. The developed topology can able to generate a maximum of 29-levels of output voltage using unequal DC sources. The basic 15-level MLI is developed and then further developed to 29-levels. The proposed topology reduces the circuit components, size and cost of the system. Apart from the several benefits of MLIs, reliability and accuracy plays a vital role because of the existence of more components count to reduce THD value. This can be considered as a major challenge employed to boost reliability without altering the best THD value. Various parameters are realized for both basic 15-level and the proposed 29-level switched-diode MLIs like total standing voltage (TSV), power loss, efficiency and cost function (CF). As the proposed MLI is undergone in dynamic load variations, the experimental results show the variations from R-load to L-load and L-load to R-load and it is found that the inverter is found to be stable throughout its operation. Experimental THD is represented, which is similar to the simulation THD which is under IEEE standards. TSV and cost factor of the proposed MLI is determined and is compared with several existing topologies and is observed to be cost-effective. A precise comparison is made on various parameters using graphical depiction. . The simulation for the proposed topology is done in MATLAB/Simulink and the experimental verification is done using the hardware prototype model under several conditions.

Irregular-Mapped Protograph LDPC-Coded Modulation: A Bandwidth-Efficient Solution for 6G-Enabled Mobile Networks

The huge amount of data produced in the 6G networks not only brings new challenges to the reliability and efficiency of mobile devices but also drives rapid development of new storage techniques. With the benefits of fast access speed and high reliability, NAND flash memory has become a promising storage solution for the 6G networks. In this paper, we investigate a protograph-coded bit-interleaved coded modulation with iterative detection and decoding (BICM-ID) utilizing irregular mapping (IM) in the NAND flash-memory systems. First, we propose an enhanced protograph-based extrinsic information transfer (EPEXIT) algorithm to facilitate the analysis of protograph codes in the IM-BICM-ID systems. With the use of EPEXIT algorithm, a simple design method is conceived for the construction of a family of high-rate protograph codes, called irregular-mapped accumulate-repeat-accumulate (IMARA) codes, which possess excellent decoding thresholds and linear-minimum-distance-growth property. Furthermore, motivated by the voltage-region iterative gain characteristics of IM-BICM-ID systems, a novel read-voltage optimization scheme is developed to acquire accurate read-voltage levels, thus minimizing the decoding thresholds (in dB) of protograph codes. Analyses and simulations indicate that the proposed IMARA-aided IM-BICM-ID scheme and read-voltage optimization scheme remarkably improve the convergence and decoding performance of flash-memory systems. Thus, the proposed protograph-coded IM-BICM-ID can be viewed as a reliable and efficient storage solution for the new-generation mobile networks, such as Internet of Vehicles.

Authentication of Covid-19 Vaccines Using Synchronous Fluorescence Spectroscopy

The present study demonstrates the potential of synchronous fluorescence spectroscopy and multivariate data analysis for authentication of COVID-19 vaccines from various manufacturers. Synchronous scanning fluorescence spectra were recorded for DNA-based and mRNA-based vaccines obtained through the NHS Central Liverpool Primary Care Network. Fluorescence spectra of DNA and DNA-based vaccines as well as RNA and RNA-based vaccines were identical to one another. The application of principal component analysis (PCA), PCA-Gaussian Mixture Models (PCA-GMM)) and Self-Organising Maps (SOM) methods to the fluorescence spectra of vaccines is discussed. The PCA is applied to extract the characteristic variables of fluorescence spectra by analysing the major attributes. The results indicated that the first three principal components (PCs) can account for 99.5% of the total variance in the data. The PC scores plot showed two distinct clusters corresponding to the DNA-based vaccines and mRNA-based vaccines respectively. PCA-GMM clustering complemented the PCA clusters by further classifying the mRNA-based vaccines and the GMM clusters revealed three mRNA-based vaccines that were not clustered with the other vaccines. SOM complemented both PCA and PCA-GMM and proved effective with multivariate data without the need for dimensions reduction. The findings showed that fluorescence spectroscopy combined with machine learning algorithms (PCA, PCA-GMM and SOM) is a useful technique for vaccination verification and has the benefits of simplicity, speed and reliability.

Distributed fault-passage indicators versus central fault location: Comparison for reliability centred planning of resonant-earthed distribution systems

Fault location methods are crucial for reducing fault restoration time, and thus improving a network’s system average interruption duration index (SAIDI) and customer outage cost. Resonant-earthed systems pose problems for traditional fault location methods, leading to poor accuracy and a need for additional complexity. In this context, methods that detect fault direction (fault-passage indicators, FPI) at multiple points in the network may show advantages over a central distance-estimation method using fault locators (FL) of poor accuracy. This paper includes a comparative study of these two major fault location methods, comparing the reliability benefit from a varied number of FPIs or a central method. The optimal placement of the fault locating devices is found by formulating a mixed-integer linear programming (MILP) optimization approach that minimizes both outage and investment costs and assesses SAIDI. This approach has been tested on an example distribution system. However, to justify the universality of the algorithm, the RBTS reliability test system has also been analysed. The comparison of location methods and placement method of FPIs are useful for reliability centred planning of resonant-earthed distribution systems where fault location is to be used. Results show that a small number of FPIs that give accurate identification of direction may give more cost effective increase in reliability than a distance estimate by FL with typical levels of inaccuracy.