Residential Network Research Articles

Single and multi-threaded power flow algorithm for integrated transmission-distribution-residential networks

The rapid development of renewable sources has significantly increased interdependencies between electricity networks of all voltage levels, leading to bidirectional flows between transmission and distribution networks, and requiring analysis of Integrated Transmission-Distribution (ITD) network. The interconnectivity is further amplified by additional coupling with electricity, gas, heat and hydrogen networks, on both national and regional levels. Moreover, installation of solar, wind and storage on customers’ premises has indicated that residential networks need to be included in the overall integrated model, called Integrated Transmission-Distribution-Residential (ITDR) network. The main goal of the paper is to develop a general model of the ITD/ITDR networks and to solve the power-flow problem on large-scale networks in an efficient way. The general model includes three-phase transmission and multi-phase distribution models, as well as accurate control strategies for traditional and electronically coupled electricity resources. The proposed model is solved via novel single-threaded power flow procedure, which incorporates new network elements’ models and the developed algorithm for integrated power flow calculations in different domains. This is further improved by developing a multi-threaded approach. Analyses on a small-scale ITD network have shown that single- and multi-threaded approaches are, respectively, (1.5–4) and (2–5) times faster compared to the state-of-the-art procedures. As network size increases, the efficiency of the proposed multi-threaded procedure becomes more pronounced compared to the single-threaded one (up to 2.39 times).

The Use of CNN Network in the Generation of Clear Line Contours of Thangka Art

Thangka has been a crucial aspect of Buddhism for thousands of years. It acts as a visualization of the myths and legends that shaped Buddhism and attracted many devotees to worship. Furthermore, Thangka also serves as a reflection of the cultural, political and social aspect of Tibetan society in history. However, the paintings, especially the outlines, became extremely fragile after years of harsh environments. I utilized Deep learning, specifically the Convolutional neural network (CNN) as the main method for processing data. After numerous training the training loss gradually approaches 0, which means that the model no longer needs additional training. Under the CNN network I used max pooling which discards trivial information, rectified linear (ReLU) activation function, residential Network (ResNet), and other methods in this research to achieve a clear outline of Thangka. Through episodes of convolution and ReLU function, the image generated becomes gradually more defined in layer 1. However, as the image undergoes continuous process, it gradually becomes more abstract. Thus, the best results could be found in layer 1. This study aims to use the results from the CNN network convolution to aid researchers studying Thangka by helping to distinguish the outlines of the image effectively.

Techno-economic analysis of an optimal integration of PV and BIPV systems in a residential network

The escalating global demand for sustainable energy solutions has prompted an increasing focus on solar photovoltaic (PV) systems. This research paper comprehensively investigates the modelling, and techno-economic analysis of an optimal combination of sets of PV and a BIPV system based on floor areas of residential buildings. The study employs advanced simulation techniques to develop a precise mathematical and optimization model and considers the levelized cost of electricity (LCOE) during the installation of PV and BIPV systems while addressing the challenge of variations in generated energy. The research contends that a comprehensive evaluation of LCOE is instrumental in determining the economic viability of optimal combinations for different sets of PV and BIPV installations based on floor area of the building while considering sustainable approaches to fulfilling energy needs. The outcomes of this research contribute significantly to the burgeoning field of renewable energy by providing a robust framework for the assessment and optimization of a combined PV BIPV system leading to decision-making towards adoption of sustainable energy solutions.

Incentivizing Prosumer Voltage Regulation for Unbalanced Radial Distribution Networks

Voltage regulation in distribution networks is becoming extremely challenging with the increased penetration of rooftop photovoltaic (PV) generation. Many recent studies demonstrate the effectiveness of power control of smart inverters for voltage regulation purposes. However, how to fully incentivize demand-side participation in voltage regulation is yet to be answered. This paper seeks to address this challenge by designing a comprehensive voltage regulation incentive scheme for customers to control their smart inverters in unbalanced radial distribution networks. A three-phase residential network from a Distributed Network Service Provider (DNSP) in Australia is modelled in the open-source distribution system simulator OpenDSS with real load and PV data, and an control algorithm to optimize the households' smart inverters in a distributed fashion is developed using game theory. The proposed algorithm is implemented in MATLAB, which is guaranteed to approach the optimal solution. Simulation results show that the proposed scheme achieves better voltage regulation performance as the widely adopted localized voltage-var droop control method and, at the same time, with lower costs to the prosumers.

Load Losses and Short-Circuit Resistances of Distribution Transformers According to IEEE Standard C57.110

Load losses determine transformers’ efficiency and life, which are limited by overheating and deterioration of their elements. Since these losses can be characterized by short-circuit resistances, in this article, we have developed expressions for the short-circuit resistances of three-phase transformers according to IEEE Standard C57.110. Imposing the condition that these resistances must cause load losses of the transformer, two types of short-circuit resistance have been established: (1) the effective resistance of each phase (Rcc,z) and (2) the effective short-circuit resistance of the transformer (Rcc,ef). The first is closely related to the power loss distribution within the transformer. The second is just a mathematical parameter. Applying these resistances to the 630 kVA oil-immersed distribution transformer of a residential network, we have concluded that both types of resistances determine the total load losses of the transformer. However, only Rcc,z accurately provides the load losses in each phase. Rcc,ef can give rise to errors more significant than 16% in calculating these losses, depending on imbalances in the harmonic currents.

Multi-Carrier NOMA-Empowered Wireless Federated Learning With Optimal Power and Bandwidth Allocation

Wireless federated learning (WFL) undergoes a communication bottleneck in uplink, limiting the number of users that can upload their local models in each global aggregation round. This paper presents a new multi-carrier non-orthogonal multiple-access (MC-NOMA)-empowered WFL system under an adaptive learning setting of Flexible Aggregation. Since a WFL round accommodates both local model training and uploading for each user, the use of Flexible Aggregation allows the users to train different numbers of iterations per round, adapting to their channel conditions and computing resources. The key idea is to use MC-NOMA to concurrently upload the local models of the users, thereby extending the local model training times of the users and increasing participating users. A new metric, namely, Weighted Global Proportion of Trained Mini-batches (WGPTM), is analytically established to measure the convergence of the new system. Another important aspect is that we maximize the WGPTM to harness the convergence of the new system by jointly optimizing the transmit powers and subchannel bandwidths. This nonconvex problem is converted equivalently to a tractable convex problem and solved efficiently using variable substitution and Cauchy’s inequality. As corroborated experimentally using a convolutional neural network and an 18-layer residential network, the proposed MC-NOMA WFL can efficiently reduce communication delay, increase local model training times, and accelerate the convergence by over 40%, compared to its existing alternative.

Localized Demand Control of Flexible Devices for Peak Load Management

The increased adoption of electric vehicles poses a challenge for the traditional electricity grid, especially at the local residential network. The impact is primarily seen in terms of higher peak demands, system overloads, and voltage violations. This study proposes a non-wire solution to these challenges using a network-oriented demand response technology called Localized Demand Control. In this technology, the local grid is enabled to follow a preferred demand curve at the distribution transformer level through a distributed but coordinated actions of various flexible loads. The system functionality has been validated in a real-world setup using a 5-house microgrid facility. Realistic simulations of a 70-house representative network were also done to create recommended rates for gradual technology adoption in the next 20 years. Results show that the system is a practical solution for reducing peak demand, enhancing load factor, and improving network efficiency.

Development of IoT-Based Portable Power Quality Monitoring on Microgrids by Enhancing Protection Features

The need for small-scale renewable energy generation is predicted to increase. Distributed energy production, in general, can be more profitable due to the cost of distribution and use of energy storage, especially from the microgrid. However, the utility and consumers face difficulties maintaining demand imbalance, frequent load-shedding, and a drop in power quality. To address this issue, a portable power quality meter and protection based on the Internet of Things (IoT) for low-voltage distribution are proposed. The proposed prototype has several advantages. First, the procedure for implementing a portable IoT-based power meter with power quality and protection features for residential networks. Compared to other devices, this type has the advantages of power quality measurement, such as power factor, frequency, and harmonics. Second, an approach is proposed device with a parallel function in maintaining network security and quality. This increases the advantage of monitoring loads connected to the grid. Third, perform IoT power monitoring devices that provide notifications in real-time. Fourth, an experiment using a power meter on a microgrid connected to renewable energy combines a LiFePO4 battery and methanol to get the maximum benefit from green energy. The test results found that the IoT model can work reliably, where access to monitoring can be done via the website. The smart meter consists of a voltage transformer, current transformer, and microcontroller unit with an embedded communication module. The existence of more affordable monitoring and protection tools can increase the user’s opportunity to gain profitability.

Congestion mitigation in unbalanced residential networks with OPF-based demand management

This paper proposes a novel congestion mitigation strategy for low voltage residential feeders in which the rising power demand due to the electrification of the transport and heating systems leads to congestion problems. The strategy is based on requiring residential customers to limit their demand for a certain amount of time in exchange for economic benefits. The main novelty of the method consists of combining a thorough representation of the network physics with advanced constraints that ensure the comfort of residential users, in a scalable manner that suits real systems. The mitigation strategy is presented from a DSO perspective, and takes the form of contracts between users and system operator. The focus on user comfort aims to make the contracts appealing, encouraging users to voluntarily enroll in the proposed mitigation scheme. The presented solution is implemented as a mixed-integer multi-period optimal power flow problem which relies on a linearized three-phase power flow formulation. Calculations on 100 real-life distribution feeders are performed, to analyze the congestion-relieving potential of several possible system operator-user contracts. From a planning perspective, the results can help the system operator define contractual terms that make a specific congestion mitigation scheme effective and viable. From an operational perspective, the same calculations can be used to optimally schedule power reduction on a day-ahead basis.

A Tale of Three Videoconferencing Applications: Zoom, Webex, and Meet

Since the outbreak of the COVID-19 pandemic, videoconferencing has become the default mode of communication in our daily lives at homes, workplaces and schools, and it is likely to remain an important part of our lives in the post-pandemic world. Despite its significance, there has not been any systematic study characterizing the user-perceived performance of existing videoconferencing systems other than anecdotal reports. In this paper, we present a detailed measurement study that compares three major videoconferencing systems: Zoom, Webex and Google Meet. Our study is based on 62 hours’ worth of more than 1.1K videoconferencing sessions, which were created with a mix of emulated videoconferencing clients deployed in the cloud, as well as real mobile devices running from a residential network over two separate periods with nine months apart. We find that the existing videoconferencing systems vary in terms of geographic scope and resource provisioning strategies, which in turns determine streaming lag experienced by users. We also observe that streaming rate can change under different conditions (e.g., available bandwidth, number of users in a session, mobile device status), which affects user-perceived streaming quality. Beyond these findings, our measurement methodology enables reproducible benchmark analysis for any types of comparative or longitudinal study on available videoconferencing systems.

Estimation of Harmonics in Partly Monitored Residential Distribution Networks With Unknown Parameters and Topology

The generalized adoption of power-electronic-based loads in residential networks is leading to increasing concern about harmonic distortion levels. At the same time, residential distribution systems are insufficiently monitored to provide a reliable analysis of harmonic limits compliance at the point of common coupling of customers. To address this problem, this paper proposes a practical method to estimate voltage harmonic levels in real time at all connection points of residential consumers. The proposed methodology assumes unknown network parameters and topology according to the limited data availability which is usual in low voltage residential networks. The proposed harmonic estimation method uses information gathered from conventional smart meters typically installed in the network (which register fundamental voltage and power) and from a reduced number of installed power quality monitors. A penetration of power quality meters below 10% has proved to provide accurate estimations of voltage harmonic levels at the whole network. The paper also proposes a methodology to optimally locate these power quality meters in the network. Validation of the methodology is performed in two different European distribution test networks with 55 buses and 471 obtaining satisfactory results. The method’s robustness and the parameters affecting accuracy are also analyzed in the article.

Implementation of CSMA/CA and ALOHA random-access protocols for packetizing wireless networks with model-based design

Because of the reliability of deployment, cost efficiency, and flexibility of ad-hoc wireless local networks (WLAN). These wireless networks have grown to be the everywhere connection solution in residential and public access networking protocols. It is important to know which strategy performs better with the least amount of delay. The Multiple Access Control protocols (MAC) that are relied on ALOHA, and Carrier Sense Multiple Access with collision avoidance (CSMA/CA) as random access techniques, have substantially aided the rapid growth of such wireless access networks. This work provides a model-based design approach for modeling CSMA/CA and ALOHA random-access protocols for packetizing wireless networks. We analyze the TX and Back-off waveforms of the PHY/MAC transceiver of three radio nodes under CSMA/CA and ALOHA operation modes and compare the obtained results of the PHY/MAC Transceiver for the network nodes according to these modes. Every node is within a range such that the communication between each couple of nodes can be interfered with and received data from the third node. The MAC layer and the logical link control function composed the data link layer. Since the same radio band is used for TX and RX, the MAC function employed here is CSMA/CA and ALOHA, which had also called a random back-off. The MAC layer sends a control signal to the TX block to transmit either a data frame or an acknowledgment frame. The frame contents are loaded in the look-up tables. The contents can be changed in the workspace. The output of this block is a complex baseband IQ signal. The obtained results show the effectiveness of CSMA/CA over ALOHA modes when comparing the corresponding Back-off waveforms and when calculating the throughput values of the three network nodes

Housing pathways of female-headed households in the informal settlements of Kampala: a qualitative study

The number of female-headed households migrating into cities is increasing. Female-headed households compete for limited housing options with other households with varying socio-economic capacities. As a result, women have to choose from several housing pathways, utilising available social capital that occasionally covers inadequate financial resources. This may sometimes lead to social conflict and exploitation by landlords and brokers. This article seeks to understand the influence of women’s social capital and networks on pathways that female-headed households pursue in Kampala city. Using a snowball sampling strategy, in-depth interviews, focus group discussions, and document analysis, the article explores female-headed households’ pathways for housing options. Participants (n = 40) in this study were identified from the Katwe informal settlement of Kampala city. Findings indicate that the strength of social ties generated through; family attachments, friends, and socio-economic involvement influences female-headed household pathways. To a lesser extent, the use of informal brokers also may influence housing pathways. The article calls for specific legislation and guidelines to regulate the informal brokerage practice and professionalise the client-broker relationship. For adequate urban housing planning to ensue, responsible authorities could incorporate into government policy the unique preferences of residential pathways and networks that bond female-headed households together.

Hosting a community‐based local electricity market in a residential network

This paper presents the potential of building a local electricity market (LEM) to boost the deployment of the local energy communities, centred around active customers with distributed energy resources (DERs). To conduct a comprehensive and detailed study on different cases with reduced computational burdens, this paper adopts a simplified modelling approach where the market and network model simulations are performed in a cascaded, decoupled fashion. This allows achieving the optimal LEM output for the energy community with different DER assets that are not bounded by the network constraints. The investigation involves quantifying the benefits brought by LEM to energy communities by tapping the flexibility associated with trading inside the energy community. Moreover, it presents the influence of different types of DERs (mainly photovoltaics (PV) and energy storage (ES)) in customers' premises on the outcome of the LEM. The LEM demonstrates successfully the reduction of cost associated with the energy purchased from the energy retailer and maximises the consumption of locally generated clean electricity. Among the studied DER portfolios, the combination of PV and ES solution shows the highest economic potential but deteriorates the voltage profiles and shows high active power loss in the winter month among all the cases examined.

The Secure Lattice-Based Data Aggregation Scheme in Residential Networks for Smart Grid

With the rapid development of computer networks, the network architecture has been more and more complex and diverse. Smart grid is a kind of wireless sensor network consuming energy in smart city. Smart grid communications have developed rapidly in recent years, while the privacy, integrity, and confidentiality of user data have been the main security issues. However, lattice-based homomorphic cryptography can resist quantum attacks and effectively provide the security of the scheme. In this article, we proposed an aggregate signature scheme based on new Batch RSA. After that, a data aggregation scheme is proposed based on this aggregate signature scheme and the qualified homomorphic cryptosystem. Compared to the previous schemes, our scheme is more secure because we implement seven properties, such as post quantum, privacy, and so on. Compared to the representative scheme proposed by Abdallah <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , our scheme has lower computation and communication overhead. In addition, the cryptographic algorithms involved in our scheme are lightweight. The network model in our scheme is suitable for large intelligent communities. So, our scheme is very suitable for the residential area network.

Remarks on the Anonymous Collective Sponsorships in Post-Byzantine Epirus (Greece): The Case of an Eighteenth-Century Painting Workshop

Co-operative patronage is based on the joint effort of individuals, lay or clerical, couples, families, colleagues, ecclesiastical and military authorities, or fellow citizens. Through the donor inscriptions are revealed the different categories of such co-operative patronage in Byzantine and Post-Byzantine society. In the Greek-speaking Post-Byzantine world, such types of anonymous groups of donors and benefactors most often came from a community as a whole, or certain inhabitants of a region, while collective donations by groups of monks were also widespread. The present paper examines the practice of anonymous collective sponsorships in Post-Byzantine Epirus, presenting the surviving monuments from the sixteenth to the seventeenth century and, in detail, the cases of anonymous collective sponsorships in a specific painting workshop of the eighteenth century, that of the so-called Kapesovite painters. In Post-Byzantine period the special privileges from the Ottomans and the development of trade, contributed to the Epirus’s cultural development. The tectonic transformations in the residential network of Epirus began in the late sixteenth century and increased after the seventeenth century. During the eighteenth century, the flourishing of Post-Byzantine art is a fact, indicating the gradual rise to prevalence of the parishes and the communities over the monastic establishments and individual donors. The financial and commercial privileges, especially after the treaty of Kucuk Kaynarca (1774), contributed decisively to religious monuments’ construction or renovation. The financial circumstances and the social cohesion of the Orthodox Christians in Epirus favored the increase of anonymous collective sponsorship in the eighteenth century. The monuments of that period evidence a significant amount of co-operative patronage, in which “anonymity” starred among the donors. The anonymous collective sponsorships indicates the community’s cohesion and the benefactor’s desire to create a legacy for future generations.

Probabilistic assessment of the influence of transformer rating on power quality indices in future residential networks

This paper proposes a methodology to assess the influence of transformer rated power on the power quality indices in future low voltage residential networks. Taking into account the stochastic nature of residential loads and the possibility of photovoltaic generation, a Monte Carlo methodology is developed in order to account for the probabilistic aspects of the problem. In this work, different transformer ratings are simulated and the effect on power quality parameters, such as voltage unbalance and voltage total harmonic distortion, is assessed using probabilistic approach. These power quality indices are compared to the compliance limits proposed in standard En50160. Several case studies are presented for two different networks, the IEEE European Low Voltage network and a larger 471-buses residential network. These studies allow establishing general conclusions regarding desirable transformer size in order not to exceed power quality limits and considering the influence of photovoltaic generation on power quality parameters.

Network assessment and modeling the management of an epidemic on a college campus with testing, contact tracing, and masking.

There remains a great challenge to minimize the spread of epidemics, especially in high-density communities such as colleges and universities. This is particularly true on densely populated, residential college campuses. To construct class and residential networks data from a four-year, residential liberal arts college with 5539 students were obtained from SUNY College at Geneseo, a rural, residential, undergraduate institution in western NY, USA. Equal-sized random networks also were created for each day. Different levels of compliance with mask use (none to 100%), mask efficacy (50% to 100%), and testing frequency (daily, or every 2, 3, 7, 14, 28, or 105 days) were assessed. Tests were assumed to be only 90% accurate and positive results were used to isolate individuals. The effectiveness of contact tracing, and the effect of quarantining neighbors of infectious individuals, was tested. The structure of the college course enrollment and residence networks greatly influenced the dynamics of the epidemics, as compared to the random networks. In particular, average path lengths were longer in the college networks compared to random networks. Students in larger majors generally had shorter average path lengths than students in smaller majors. Average transitivity (clustering) was lower on days when students most frequently were in class (MWF). Degree distributions were generally large and right skewed, ranging from 0 to 719. Simulations began by inoculating twenty students (10 exposed and 10 infectious) with SARS-CoV-2 on the first day of the fall semester and ended once the disease was cleared. Transmission probability was calculated based on an R0 = 2.4. Without interventions epidemics resulted in most students becoming infected and lasted into the second semester. On average students in the college networks experienced fewer infections, shorter duration, and lower epidemic peaks when compared to the dynamics on equal-sized random networks. The most important factors in reducing case numbers were the proportion masking and the frequency of testing, followed by contact tracing and mask efficacy. The paper discusses further high-order interactions and other implications of non-pharmaceutical interventions for disease transmission on a residential college campus.

Optimal design and operation of distributed energy resources systems for residential neighbourhoods

Different designs of distributed energy resources (DER) systems could lead to different performance in reducing cost, environmental impact or use of primary energy in residential networks. Hence, optimal design and management are important tasks to promote diffusion against the centralised grid. However, current operational models for such systems do not adequately analyse their complexity. This paper presents the results of a mixed-integer linear programming (MILP) model of distributed energy systems in the residential sector which builds up on previous work in this field. A superstructure optimisation model for design and operation of DER systems is obtained, providing a more holistic overview of such systems by including the following novel elements: a) Design and utilisation of a network with integrated heating/cooling pipelines and microgrid connections between neighbourhoods; b) Exploration of use of feed-in tariffs (FITs), renewable heat incentives (RHIs) and the ability to buy/sell from/to the national grid. It is shown that the (DER network mitigates around 30–40% of the CO2 emissions per household, compared with “traditional generation”. Money from FITs, RHIs and sales to the grid, as well as reduced grid purchases, make DER networks far more economical, and even profitable, compared to the traditional energy consumption.

Impact of the deployment of solar photovoltaic and electrical vehicle on the low voltage unbalanced networks and the role of battery energy storage systems

The deployment of low carbon technologies (LCTs) such as solar photovoltaics (PVs) and electric vehicles (EVs) is increasing due to their various benefits. However, their rapid integration in the residential networks imposes critical technical issues to the network operators. In this paper, a sensitivity analysis is conducted to investigate the impact of these technologies on low voltage unbalanced residential networks located in Northern Ireland. Different penetrations are investigated, and the results are assessed using various technical indices. The simulations are performed using actual load measurements in a 10-minute resolution obtained from the network operator of Northern Ireland. The impact of LCTs on the phase imbalance is considered by analyzing the voltage unbalance and neutral losses. The results suggest that monitoring each feeder and phase separately and consider the voltage unbalance in the assessment as it can be violated without a voltage magnitude violation occurring, in addition, the farthest nodes from the transformer bus were found to be very sensitive to violations. The solution-based community battery energy storage systems (BESS) is investigated by introducing sizing and scheduling algorithms to solve the network issues and enhance the network performance using black-box optimization. The results proved the wide capability of the community BESS in providing the network with different services. The main purpose of this study is to provide a full understanding of the future challenges posed by the deployment of LCTs and the role of BESS in accelerating the transition towards a low carbon future by supporting the network operation.