Urban Grid Research Articles

Deduction of Strategic Planning Guidelines for Urban Medium Voltage Grids with Consideration of Electromobility and Heat Pumps

With the evolution of electromobility and heat pumps in urban areas, distribution system operators find themselves facing new challenges in reinforcing their grids. With this evolution, the power demand is developing rapidly and grid reinforcement is urgently needed. The electromobility and heat pump loads are introduced by giving the assumed development scenarios in Germany and their corresponding nominal power assumptions. Furthermore, a method for load modeling in grid planning is explained. Subsequently, several grid planning approaches are presented while dividing them into conventional and innovative planning strategies. Among the investigated innovative planning strategies are three variants of load management that regulate different load types. By analyzing several urban medium voltage grids, this contribution deduces a solid basis for distribution system operators in the form of planning guidelines. The implemented grid planning method leading to the planning guidelines is presented in detail along the contribution.

Understanding the Street Layout of Melbourne’s Chinatown as an Urban Heritage Precinct in a Grid System Using Space Syntax Methods and Field Observation

Melbourne’s Chinatown is the oldest in Australia. A large amount of research on this unique ethnic enclave has been conducted to elucidate its formation history, heritage significance, cultural influence and architectural features. However, the discussion of the precinct’s spatial characteristics remains mostly marginalised. As a heritage precinct in the centre of an urban grid form, the precinct offers a unique spatial experience to its visitors. To better fathom the street layout of the area, three objectives are addressed in this study, including understanding: (1) the precinct’s street network in the grid system, (2) the visibility relationship within the precinct and (3) the relationship between buildings and streets. A joint methodology framework is established to fulfil the research objectives by incorporating space syntax methods and field observation. The findings facilitate policymakers and planners in understanding the precinct’s unique street layout and making relevant preservation decisions. Further studies are encouraged to scrutinise other spatial and urban characteristics of the precinct and test the proposed methodology.

Comparison of Illuminance in Different Environments: A Case Study on Subway Stations

With urbanization and the rapid development of social economy, China’s rail transit industry has developed rapidly in recent years. In order to alleviate the pressure of road network, subways provide convenience as they are fast and space-saving. Subway stations are major energy consumers of urban power grid due to their large traffic volume and long operation time. On the premise of ensuring operation safety, reducing the energy consumption of subway helps in energy conservation and emission reduction as proposed in the 13th Five-Year Plan. According to the statistics of the energy-saving evaluation report of rail transit engineering, the lighting system accounts for 20%–30% of the total power consumption of the subway station. Due to the single lighting control mode of the lighting system in the subway station, the actual station illumination cannot be reported and adjusted in time, resulting in the waste of lighting energy and high power consumption of the system. Through in-depth research on the intelligent lighting system of subway station, this paper improves the system control, and finally summarizes the optimization scheme of subway station lighting design which can effectively save the power consumption of lighting system. The main contents of this paper are as follows: The research results of this paper can provide effective measures for energy saving of electric lighting in subway stations and reduce electric energy consumption; on the other hand, as an integral part of building lighting energy-saving system, it also has certain guiding significance for the research of building lighting energy-saving.

Editorial: Intelligent operation and control in next generation urban power grid

Editorial: Intelligent operation and control in next generation urban power grid

The Big Data Model for Urban Road Land Use Planning Is Based on a Neural Network Algorithm.

The spatial differentiation of land use induces traffic demand and guides the construction of traffic supply; traffic conditions are an important influencing factor in determining the nature of land use, and there is a close interaction between the two. This study uses a neural network-based approach at the urban grid level to portray representative phenomena of urban development and analyze the interaction between transportation and land use. The results reflect the model's effective simulation of urban laws, and the case study reveals the differences in the laws of different cities, to guide the benign development of cities and transportation. This article firstly conducts a study on the theoretical foundation; compares the development history, planning, and design methods and practical experience of road planning and resilient planning; summarizes the experience of resilient road system design; and analyzes the future development trend, based on the above basic theoretical research, to develop research ideas and methods. Secondly, the scenario analysis method is explicitly applied to analyze various scenarios that may occur in the future development process of simulated urban roads and rank the scenarios based on the probability of occurrence. For the impact of traffic on land use, the concepts of vitality and potential are introduced, and a multidimensional long and short-term memory network (MDLSTM) model is established. The model takes into account land use lags and potential transfer and has relatively higher prediction accuracy. The results show that larger cities with urban dominant industries and tertiary industries also have higher land use potential and the more significantly influenced by traffic.

Resilient power grid for smart city

Modern power grid has a fundamental role in the operation of smart cities. However, high impact low probability extreme events bring severe challenges to the security of urban power grid. With an increasing focus on these threats, the resilience of urban power grid has become a prior topic for a modern smart city. A resilient power grid can resist, adapt to, and timely recover from disruptions. It has four characteristics, namely anticipation, absorption, adaptation, and recovery. This paper aims to systematically investigate the development of resilient power grid for smart city. Firstly, this paper makes a review on the high impact low probability extreme events categories that influence power grid, which can be divided into extreme weather and natural disaster, human-made malicious attacks, and social crisis. Then, resilience evaluation frameworks and quantification metrics are discussed. In addition, various existing resilience enhancement strategies, which are based on microgrids, active distribution networks, integrated and multi energy systems, distributed energy resources and flexible resources, cyber-physical systems, and some resilience enhancement methods, including probabilistic forecasting and analysis, artificial intelligence driven methods, and other cutting-edge technologies are summarized. Finally, this paper presents some further possible directions and developments for urban power grid resilience research, which focus on power-electronized urban distribution network, flexible distributed resource aggregation, cyber-physical-social systems, multi-energy systems, intelligent electrical transportation and artificial intelligence and Big Data technology.

Optimization of a Three-Phase Coaxial 10 kV/1.5 kA HTS Power Cable for Balancing 3-Phase Current Distribution

With the increasing power load of urban power grid, the upgrading of conventional cable is facing with the problem of space resource shortage. Three-phase coaxial high temperature superconducting cable has the advantages of compact structure, low loss, and nearly 2/3 reduction in the consumption of HTS tape, which provides a new prospective solution for urban expansion. However, due to the different radius of each phase of the three-phase coaxial HTS cable, the symmetry of electromagnetic parameters of each phase are affected, resulting in the imbalance of the three-phase current, which will reduce the transmission efficiency. Based on the multi-loop method, we establish the differential equation of three-phase coaxial superconducting cable in this paper, by calculating the parameters of three-phase inductance and capacitance by a numerical method, and obtain the instantaneous variation rule of voltage and current in the three-phase coaxial HTS cable. We propose a novel two-section Particle Swarm Optimization to solve the problem of three-phase current imbalance in HTS cable. The algorithm divides the C-phase conductor and the copper shield layer into two segments with the same radius but different pitches and twist directions, which increases the variable by one-half. By changing the pitches and winding directions, considering the thickness of the insulation, optimization of current distribution of three-phase coaxial HTS cable is achieved. Finally, we designed a 10 kV/1.5 kA three-phase coaxial HTS cable. The results show that the current imbalance ratio of the superconducting cable is reduced from 41% to 1% after the two-section Particle Swarm Optimization. The mathematical model and the imbalance optimization algorithm of three-phase coaxial HTS cable both are verified. The optimization results provide important reference for the structural design and experimental research of three-phase coaxial HTS cable for urban power grid.

Optimal Planning of Electric Vehicle Battery Centralized Charging Station Based on EV Load Forecasting

This article studies the planning of swapping electric vehicle (SEV) battery centralized charging station (BCCS) based on EV spatial-temporal load forecasting. First, according to the road topology of the planning area, the road topology model is built. The driving energy consumption process and endurance mileage model of EVs are developed. Then, we analyze the travel demand of people, the driving segments of SEVs (e.g., swapping private EVs and swapping taxis) are analyzed. Next, the spatial distribution model of SEVs is built. Thus, the spatial-temporal load model of SEVs is established. The sizing and locating planning model based on operation analysis is established for BCCSs. In addition, the photovoltaic (PV) configuration model in the urban grid is also established. Finally, considering the coupling relationship between urban distribution system and power line pipes, a grid planning method considering power line pipes is proposed. The planning model of BCCS aimed at minimizing annual comprehensive cost considering distribution system with PV is constructed. The MATLAB/YALMIP toolbox is applied to optimize the planning model in this article, and the feasibility and effectiveness of the proposed method are verified.

High-Temperature Superconducting Cable Optimization Design Software Based on 2-D Finite Element Model

With the increasing electricity power demand in major cities, the existing conventional power cables is difficult to meet the requirements of high-density and large-capacity power transmission. Compared with conventional power cables, high-temperature superconducting cables can significantly increase transmission capacity, reduce power losses, and save land occupation, which have great potential in future urban high-density power transmission applications. However, the process of designing a complete set of HTS cable is very complex, and many factors need to be considered comprehensively, such as current distribution, AC loss calculation, thermal stability analysis. In this case, a HTS cable design software platform is under development to simplify design process and improve the work efficiency of designers. Based on the software, design schemes of three-phase 10kV/1.5kA HTS cable with two different structures are given. A 2-D AC loss finite element model of HTS cable is established and verified. The simulation results show that at low voltage level, the HTS cable with three-phase coaxial structure has good performance, and can save more land, which is more suitable for the expansion of urban power grid in the future.

Application of Blockchain Technology in Electric Vehicle Charging Piles Based on Electricity Internet of Things

With the continuous development of urban intelligence, as traffic, power grids, and electric vehicles are new ideas to solve energy shortages and air control problems, they have received widespread attention from the society and strong support from the government. The charging pile is a key hub for data exchange and has typical characteristics of IoT terminals. However, the guidance of the grid connection of electric vehicles is not standardized, and the security and stability of the power grid will inevitably be affected. The blockchain has the characteristics that data is difficult to tamper with and decentralized. Based on these two characteristics, the information recorded by the blockchain is more authentic and reliable. This paper is aimed at realizing the global unified identification and management of large terminal equipment based on ubiquitous power Internet of Things equipment with the help of blockchain technology and at providing safe, efficient, and stable online management services for a large number of devices in the ubiquitous power Internet of Things. In this paper, we analyze the application possibility of blockchain technology in the current electricity market and apply blockchain technology to the electricity market to solve the drawbacks of the electricity market, as well as adding blockchain analytics to the renewable energy electricity market. The experimental data analysis shows that with the increase of the length of the blockchain, the blocking time of the new area increases correspondingly, but the overall performance declines slightly, so this scheme can meet the practical needs of a large number of concurrent access terminals in the ubiquitous power Internet of Things. It can be seen that the successful application of blockchain technology based on the power Internet of Things in electric vehicle charging piles has greatly improved work efficiency.

On the Importance of Grid Tariff Designs in Local Energy Markets

Local Energy Markets (LEMs) were recently proposed as a measure to coordinate an increasing amount of distributed energy resources on a distribution grid level. A variety of market models for LEMs are currently being discussed; however, a consistent analysis of various proposed grid tariff designs is missing. We address this gap by formulating a linear optimization-based market matching algorithm capable of modeling a variation of grid tariff designs. A comprehensive simulative study is performed for yearly simulations of a rural, semiurban, and urban grids in Germany, focusing on electric vehicles, heat pumps, battery storage, and photovoltaics in residential and commercial buildings. We compare energy-based grid tariffs with constant, topology-dependent and time-variable cost components and power-based tariffs to a benchmark case. The results show that grid tariffs with power fees show a significantly higher potential for the reduction of peak demand and feed-in (30–64%) than energy fee-based tariffs (8–49%). Additionally, we show that energy-based grid tariffs do not value the flexibility of assets such as electric vehicles compared to inflexible loads. A postprocessing of market results valuing the reduction of power peaks is proposed, enabling a compensation for the usage of asset flexibility.

Three decades of global trends in urban microwave backscatter, building volume and city GDP

Most mapped urban information is essentially two-dimensional, e.g., areal extent by urban cover type. There is a gap in knowledge about patterns and changes of urban built-up volumes and development intensity globally. Here we use a new dataset of global microwave backscatter for 1993–2020 to explore this third dimension of urban growth across 477 large cities. Our results show that urban backscatter correlates with an independent estimate of building volume across 8000+ urban grid cells (0.05° lat/lon) in large cities in China, Europe, and the U.S.A. Regional rates of urban backscatter increase vary substantially across the three decades, with the highest rates in the 2010s across Asia, particularly in China and Southeast Asia. Microwave backscatter, a proxy for urban building volume, is correlated with Gross Domestic Product at the scale of urban grid cells across the globe, and at the city level across most regions. This time-series of scatterometer data provides an important tool for understanding both the spatial and temporal patterns of urban volumetric growth over the past several decades.

Military or trade port cities? About the form and function of the Hispanic colonial cities in Latin America and the Caribbean

ABSTRACT This work studies urban form and function in Hispanic American colonial port cities. By combining different research questions and points of view, new insights are given into matters such as the origin of their urban grids, the development of their fortifications throughout the colonial era, and the military versus trade function they accomplished. The focus is on Cartagena de Indias, Colombia, with other Hispanic colonial cities also included in the discussion. The field work is based on primary literature about colonial laws and ordinances and the reports of several viceroys in the eighteenth century as well as a wide array of secondary literature in different languages. The results show that, while these cities fulfilled an important role as trade nodes, this function was second to their military role. However, both functions are found to be interdependent in a number of ways.

Multistage Bilevel Planning Model of Energy Storage System in Urban Power Grid Considering Network Reconfiguration

The large-scale integration of renewable energy sources (RESs) and the rapid development of loads cause frequent transmission congestion in the urban power grid (UPG). Transmission system operators usually perform the high-voltage distribution network (HVDN) reconfiguration to mitigate the transmission congestion. However, as the loads and RESs change rapidly, the HVDN reconfiguration might be conducted frequently. This might cause severe security problem. An energy storage system (ESS) provides an effective way of alleviating the transmission congestion. If the ESS is installed and operated elaborately, the transmission congestion of UPG can be mitigated with a little HVDN reconfiguration. Hence, this study proposes a multistage bilevel planning model for the optimal allocation of ESS. The upper-level model aims at maximizing the annual comprehensive revenue of HVDN, and the lower-level model focuses on the minimization of the operational cost. Simulation results carried out on a real-world test system verify that the proposed method has the great potential of reducing the investment and operational cost while mitigating the transmission congestion.

Impacts of land-surface forcing on local meteorology and ozone concentrations in a heavily industrialized coastal urban area

In this study, the Weather Research and Forecasting/Community Multiscale Air Quality (WRF-CMAQ) model was used to investigate the interaction of urban land-surface forcing with local circulations and the impact on boundary layer ozone concentrations in southern Taiwan at an urban-scale resolution. Two simulations were performed with the same emissions but different land cover designations. URBAN was the baseline simulation representing the current urbanized condition, while NO-URBAN replaced all urban grid cells with cropland. The interaction of the sea-breeze with the urban-heat-island (UHI) convergent flow during the daytime in URBAN transports near-surface O3 precursors to the upper planetary boundary layer (PBL). When the UHI convergent flow stalls over the city center, a circulation flow is formed and traps the pollutants at an elevated height, increasing the reaction rate of hydroxyl radical with volatile organic compounds by 2.0–4.0 ppbv h−1 at 1000–1500 m. At nighttime, the deeper boundary layer of URBAN diluted the NOx mixing ratio by ~17 ppbv and weakened the titration effect, contributing to higher O3 by +15 ppbv in the urban area. However, once the daytime vertical mixing diminished, the O3 aloft also diffused downward to the surface level and further degraded the nighttime air quality.

Temporal-spatial risk assessment of COVID-19 under the influence of urban spatial environmental parameters: The case of Shenyang city.

Respiratory infection is the main route for the transmission of coronavirus pneumonia, and the results have shown that the urban spatial environment significantly influences the risk of infection. Based on the Wells-Riley model of respiratory infection probability, the study determined the human respiratory-related parameters and the effective influence range; extracted urban morphological parameters, assessed the ventilation effects of different spatial environments, and, combined with population flow monitoring data, constructed a method for assessing the risk of Covid-19 respiratory infection in urban-scale grid cells. In the empirical study in Shenyang city, a severe cold region, urban morphological parameters, population size, background wind speed, and individual behavior patterns were used to calculate the distribution characteristics of temporal and spatial concomitant risks in urban areas grids under different scenarios. The results showed that the correlation between the risk of respiratory infection in urban public spaces and the above variables was significant. The exposure time had the greatest degree of influence on the probability of respiratory infection risk among the variables. At the same time, the change in human body spacing beyond 1 m had a minor influence on the risk of infection. Among the urban morphological parameters, building height had the highest correlation with the risk of infection, while building density had the lowest correlation. The actual point distribution of the epidemic in Shenyang from March to April 2022 was used to verify the evaluation results. The overlap rate between medium or higher risk areas and actual cases was 78.55%. The planning strategies for epidemic prevention and control were proposed for the spatial differentiation characteristics of different risk elements. The research results can accurately classify the risk level of urban space and provide a scientific basis for the planning response of epidemic prevention and control and the safety of public activities.

An Improved Transition Probability Matrix for Crime Distribution Prediction.

The occurrence of crime has always been the main problem affecting urban public security and social security environment. Therefore, the prevention and control of crime is the focus of public security work. The traditional police strategy has poor timeliness and cannot respond and adjust in real time with the occurrence of criminal activities, and its deterrence and control of criminal activities are limited. To address the problem of low accuracy of existing crime distribution prediction models, an improved transition probability matrix for crime distribution prediction is proposed in this paper. Based on a large number of trajectory data of criminals, this paper quantitatively describes the temporal and spatial characteristics of crowd movement in different areas of the city by using the temporal and spatial transfer probability. Then, combining Markov chain and Bayes' theorem, the probability model of spatio-temporal transfer of criminal groups in regions is constructed. Finally, the model predicts the number of crimes in urban grid areas.

Sustainability Analysis and Scenarios in Groundwater Pumping Systems: A Case Study for Tenerife Island to 2030

Groundwater pumping systems using photovoltaic (PV) energy are increasingly being implemented around the world and, to a greater extent, in rural and electrically isolated areas. Over time, the cost of these systems has decreased, providing greater accessibility to freshwater in areas far from urban centers and power grids. This paper proposes a novel sustainability analysis of the groundwater pumping systems in Tenerife Island as an example of a medium-size isolated system, analyzing the current status and the business-as-usual projection to 2030, considering the water reservoirs available and the final use of water. The 2030 projection focused on the PV deployment, evaluation of the levelized cost of electricity (LCOE), and the availability of the groundwater resource. HOMER software was used to analyze the LCOE, and ArcGIS software was used for the visual modeling of water resources. As a result, the average LCOE for a purely PV installation supplying electricity to a pumping system in Tenerife is 0.2430 €/kWh, but the location and characteristic of each pumping system directly affect the performance and costs, mostly due to the solar availability.

Operating Renewable Energy Communities to Reduce Power Peaks in the Distribution Grid: An Analysis on Grid-Friendliness, Different Shares of Participants, and Economic Benefits

Improving the control of flexible assets in distribution grids, e.g., battery storages, electric vehicle charging points, and heat pumps, can balance power peaks caused by high renewable power generation or load to prevent overloading the grid infrastructure. Renewable energy communities, introduced as part of the recast of the Renewable Energy Directive, provide a regulatory framework for this. As a multi-site energy management method, they can tap flexibility potential. The present work quantifies stimulus for renewable energy communities to incentivize the grid-friendly operation of flexible assets, depending on the shares of participants in rural, suburban, and urban grid topologies. Results indicate that an operation of the community, driven by maximizing the economic benefits of its members, does not clearly reduce the annual peak load at the low-voltage substation, while the operation strategy of a grid-friendly renewable energy community achieves a peak power reduction of 23–55%. When there is not full participation, forecasts of the residual load of non-participants provided by the distribution system operator can be considered in the optimization of the renewable energy community. For all simulation cases, the economic benefit between the two operation strategies differs by less than one percent, resulting in a very low additional incentive required for grid-friendliness in terms of reduced peak power. Thus, grid-friendly renewable energy communities might be a cost-effective way to defer future grid reinforcements.

A population-based incremental learning algorithm to identify optimal location of left-turn restrictions in urban grid networks

The treatment of left turns at signalized intersections drives the development of signal phasing and timing plans and also plays an important role in overall traffic network operations. Accommodating left turns allows for the most direct routeing but reduces intersection capacity, whereas restricting left turns improves capacity but requires some vehicles to travel longer distances. This paper proposes a population-based incremental learning (PBIL) algorithm to determine at which intersections left-turn restrictions should be enacted to maximize a network's operational performance. The performance of each configuration is tested in a micro-simulation environment on both perfect and imperfect square grid networks. Comparison with a partial enumeration of feasible options reveals that the PBIL algorithm is effective at identifying a near-optimal configuration of left-turn restrictions. The resulting configurations suggest that left turns should be generally restricted at intersections that carry the most flow. These intersections typically occur in the central portion of the network when demands are relatively uniform. Doing so helps to provide additional intersection capacity at the locations where it is most necessary, while minimizing the additional travel distance that is incurred due to detours caused by the left-turn restrictions. These provide insight as to how urban traffic networks might be managed to improve network efficiency by only enacting left-turn restrictions at a subset of locations.