Urban Power Distribution Network Research Articles

A Stochastic Charging Station Deployment Model for Electrified Taxi Fleets in Coupled Urban Transportation and Power Distribution Networks

A Stochastic Charging Station Deployment Model for Electrified Taxi Fleets in Coupled Urban Transportation and Power Distribution Networks

Impact of cost-based smart electric vehicle charging on urban low voltage power distribution networks

Impact of cost-based smart electric vehicle charging on urban low voltage power distribution networks

Generalized User Equilibrium for Coordination of Coupled Power-Transportation Network

The increasing proliferation of electric vehicles (EVs) tightens the interaction between urban power distribution network (PDN) and transportation network (TN). This paper proposes the generalized user equilibrium (GUE) method for the coupled power-transportation network (CPTN) operation. First, the GUE concept is proposed to describe the steady traffic flow distribution as an extension of user equilibrium (UE), which could no longer exist due to the constraints placed by PDN operation on TN. Second, the GUE-based coordination model is established for CPTN with PDN generation scheduled and TN traffic assigned simultaneously. Finally, a decomposition method is developed to solve the model efficiently, which is converted into a master problem and a series of feasible/optimal path generation subproblems for individual origin-destination (O-D) pairs. The case studies on a real-world network have verified the effectiveness of the proposed model and method. The results demonstrate the necessity of GUE and its potential in improving the CPTN operation.

A Distributed Coordination Method for Coupled Traffic-Power Network Equilibrium Incorporating Behavioral Theory

The increasing penetration of electric vehicles (EVs) gradually evolves the urban transportation network (UTN) and power distribution network (PDN) from being independent to being coupled. To analyze the impact of drivers' behavior on the coupled network, and reveal the relationship between the two networks, a coupled traffic-distribution (CTD) model is proposed, in which the total traveling cost of UTN and the power service cost of PDN is minimized. In the CTD model, A stochastic user equilibrium traffic assignment problem (SUE-TAP) with elastic traffic demand and discrete path selection of drivers is formulated to capture the traffic flow distribution comprised of EVs and gasoline vehicles (GVs). An alternative current optimal power flow (ACOPF) model of PDN is utilized to provide the optimal charging price and scheduling plan. Besides, the SUE-TAP with nonlinear functions is difficult to solve, a novel piecewise linear approximation method is presented to deal with the nonlinear items of the SUE-TAP caused by drivers' traveling cost and traveling tendency incorporating perception. Incorporating the behavioral theory, a distributed coordination method derived from optimal condition decomposition is proposed for the coupled traffic-power network equilibrium. The proposed distributed scheme is examined using a coupled network, which consists of a 20-road UTN and a 33-bus PDN. Numerical results demonstrate the effectiveness and practicability of the proposed model and the distributed coordination method.

Fault section location in urban distribution network based on fault marking

The goal is to propose an effective method for locating a fault segment in urban power distribution networks. Urban distribution networks have multiple outgoing lines, switches with multiple connections and have variable topology characteristics. It is found that the fault location method based on matrix algorithm has low adaptive capability and fault tolerance when dealing with complex and variable topology. Therefore, this paper proposes an efficient fault segment location method based on special fault indicators, which can significantly improve the accuracy and reliability of fault location. Accordingly, to improve the accuracy and reliability of fault location, a fault segment location method based on fault marking is proposed. The approach proposed in the paper relies on the analysis of the incident matrix, which describes the relationship between nodes and branches, and allows the use of graph theory. The branch state vector is added to obtain the adjacency matrix, which allows to describe the state of change in the dynamics of the distribution network topology. In the next step, a set of nodes and branches, which reflect the incoming and outgoing interconnections of the nodes, is established based on the selected direction of the network binding. According to the direction of the node fault current, the suspicious branches are identified and labeled to indicate the fault. By cumulative calculation and analysis of the labels, the target branches are screened out and the faulty sections of the city power supply network are identified. The results of the case study conducted in the paper show that the proposed method has good adaptability to the variable topology and increases the fault tolerance and accuracy of the developed matrix algorithm. The topological operating state of the network can be changed by controlling the switches to optimize the operation and improve the reliability of the power supply. Thus, the algorithm for fast and accurate fault location is of great importance for improving the safety and quality of urban power supply.

Coordinated Operation of Hydrogen-Integrated Urban Transportation and Power Distribution Networks Considering Fuel Cell Electric Vehicles

Under the pressure of climate change, hydrogen has been advocated as a promising energy carrier to achieve low-carbon integration of urban transportation network (UTN) and power distribution network (PDN). In this article, the control strategy based on hydrogen refueling service fee (HRSF) is proposed for the smart city department to guide hydrogen fuel cell electric vehicles (HFCEVs) in selecting the hydrogen refueling stations. Correspondingly, the HRSF-based coordinated operation model is established to minimize the total of UTN travel cost, PDN operation cost, and the environmental cost, while the nodal carbon intensity restriction, the uncertainties of renewable distributed generators output, and origin-destination traffic demand are also taken into account. Afterward, the proposed model is solved by the decentralized alternative direction method of multipliers algorithm, and verified on the hydrogen-integrated UTN and PDN in Sioux Falls. Numerical results demonstrate that popularizing HFCEVs contributes to emission reduction, and the HRSF-based coordinated operation strategy is effective in reducing the overall emissions, promoting renewable energy accommodation, and improving the holistic operation efficiency of the hydrogen-integrated UTN and PDN.

Bi-Level Decentralized Optimal Economic Dispatch for Urban Regional Integrated Energy System Under Carbon Emission Constraints

Based on the real-time environmental constraints in urban regional construction, this paper constructed a bi-level decentralized low-carbon optimal dispatching model of the urban regional integrated energy system (RIES), including the park integrated energy systems (IESs). In this model, a bi-level optimal allocation model of carbon emission constraints between the urban and the park is proposed for the first time. The upper urban will formulate the real-time carbon emission constraints based on real-time environmental monitoring, decomposing the historical carbon emissions to the lower park IESs; the lower park will meet the real-time carbon emission constraints during optimization. We through the upper urban with the lower park between the bi-level decentralized optimization to ensure that the objective function’s upper urban power, natural gas, and heat distribution network system is minimum total network loss. In addition, it is necessary to ensure the minimum operating cost of each park IESs and focus on how to meet the requirements of the overall environment of urban RIES. Furthermore, we study the influence of optimal allocation strategy of carbon emission constraints on network loss, and operating cost of urban RIES under different scenarios. Then, an improved analytical target cascading (ATC) method is applied to solve the bi-level decentralized optimal dispatching model of urban RIES. Finally, an example under three different scenarios is given to verify the superiority and effectiveness of the proposed model and the improved method.

Coordinated pricing of coupled urban Power-Traffic Networks: The value of information sharing

The growing demand for the fast charging of electric vehicles has created stronger interdependency between the operation of urban traffic networks and power distribution networks. This paper investigates the necessity and feasible mechanism of coordinated pricing in coupled urban power-traffic networks. The retail charging pricing of the power distribution network operator and congestion pricing of the urban traffic network operator will simultaneously affect the routing and charging decision choices for electric vehicles. Then, the response of multiclass vehicles—i.e., the aggregated traffic flow and charging load—will in return affect the operation performance—i.e., power loss and traffic congestion—of the coupled networks. However, due to operators’ differing pricing goals and limited access to user information, the actual response for vehicles might deviate from the respective expectation of the two operators under isolated pricing. With the growing penetration of electric vehicles, such deviation might become more evident, calling for a focus on pricing coordination. To investigate the necessity of coordinated pricing, the Stackelberg game framework is employed to model the pricing interactions between operators (leaders) and vehicles (followers). Accounting for privacy issues, a decentralized coordination framework of the two networks is proposed for information sharing. The numerical test results confirm the negative impacts of isolated pricing and demonstrate the effectiveness of coordinated pricing. Sensitivity analysis is conducted to examine the influence of critical parameters: e.g., charging electric vehicle penetration and total travel demand.

Tapping on the Aggregate Flexibility of Heterogeneous Load Groups for EV Fast Charge Accommodation in Urban Power Distribution Networks

Smart sustainable grids are characterized with sophisticated demand response schemes. Flexible loads are the key in the concept of demand response and, if well-planned, can save significant costs and emissions through optimal use of energy resources. On the other hand, fast charge electric vehicles, despite their appeal, represent a special type of loads demanding an immediate attendance upon admission to charging stations. This may counterbalance the efforts toward flexible load management. Moreover, there is a rising demand for fast-charge stations with a more balanced spatial distribution. In this paper, a comprehensive multi-stage residential load planning scheme is proposed incorporating the most diverse load groups in a realistic market environment. Within this procedure, a unique concept is implemented which taps into the aggregated residential load flexibility to support fast charge of electric vehicles. Through cluster-wise scheduling for different load classes, the proposed approach aggregates the flexibility of a heterogeneous population of different multi-apartment loads including air conditioning and water heating devices as well as slow-charging EVs to also plan for fast-charge-powered EVs. The results demonstrate the feasibility of the successful implementation of the proposed framework within urban neighborhoods which proves efficient in reducing fast-charge load on the grid besides financial benefits for aggregators.

Optimal Pricing of Public Electric Vehicle Charging Stations Considering Operations of Coupled Transportation and Power Systems

Recognized as an efficient approach to reduce fossil fuel consumption and alleviate environment crisis, the adoption of electric vehicles (EVs) in urban transportation system is receiving more and more attention. EVs will tightly couple the operations of urban transportation network (UTN) and power distribution network (PDN), necessitating the interdependent traffic-power modeling to optimize the on-road EV charging decisions. In this article, the optimal charging pricing problem of public electric vehicle charging stations (EVCSs) considering the interdependent operations of UTN and PDN is modeled from the view of the charging network operator (CNO), which is formulated as a bi-level optimization problem. In order to match the spatial size of UTN and power capacity of PDN, multiple PDNs are incorporated in the modeling to support EVCSs at different parts of UTN, permitting charging load migration across PDNs. Fixed point theory is used to analyze properties of the CNO's optimal charging pricing problem. An iterative method is designed to obtain the optimal charging pricing result, which solves the CNO's pricing subproblem and PDN market clearing subproblem in turn. Numerical case study results validate the effectiveness of proposed models and methods, and demonstrate the impacts of the CNO pricing on the operations of UTN and PDN.

Research on Green Comprehensive Evaluation Model of Urban Distribution Network Electric Energy Based on CRITIC-Order Relation Analysis Method Combination Weighting

The green evaluation of urban power distribution network is the main reference basis for power grid transformation and upgrading. Based on this, this article constructs a comprehensive evaluation index system from the four dimensions of power supply side, consumer side, platform area and related policies; To comprehensively consider the difference and relevance of indicators, this paper adopts the order relationship analysis method and the CRITIC weighting method for subjective and objective combination weighting, and uses linear weighting to score indicators; Finally, combining the four evaluation dimensions to analyze the application approach of the comprehensive evaluation model to verify the practicability of the model.

Research on Urban Distribution Network Planning and Optimization Measures Based on Real 3D Scenes

With the continuous advancement of smart grid construction, the structure of the power grid is becoming increasingly large and complex, and it is increasingly difficult to adapt to the requirements of grid development using traditional 3D drawings for grid design and operation and maintenance. The emerging 3D real-world modeling technology can visually and comprehensively display terrain, landforms, equipment appearance dimensions, wiring methods and other information. To promote the application of real-world 3D scene technology, electric power companies have repeatedly carried out 3D design of power grid projects and construction of data centers Optimized distribution network planning. Realize the linkage of real-world 3D scene plan maps, building information models, etc. through geographic connections, provide real feedback on site conditions, reduce the number of site surveys, save manpower and resources, and effectively implement urban power distribution network planning.

Electric load forecast of long-period rail transit based on fuzzy mathematics

The urban rail transit power supply system is an important part of the urban power distribution network and the power source of the rail transit system. It is responsible for providing safe and reliable electrical energy to urban rail trains and power lighting equipment. This paper processes the obtained long-period rail transit power load learning sample data matrix, according to the principle of normalization processing, effectively eliminates irregular data in the sample set and fills in possible missing data, thereby eliminating bad data or fake data for model learning. Moreover, this avoids the generation of huge errors that cause exponential growth in the model due to the increase in the learning sample size and the irregularity of the data. According to the characteristics of power load, this paper comprehensively considers the influence of temperature and date type on the maximum daily load, applies the fuzzy neural network model to the long-period load forecasting of long-period rail transit, and introduces the whole process of establishing the forecasting model in detail. Through detailed analysis of the actual data provided by the EUNITE network, the relevant factors affecting the daily maximum load were determined, and then the appropriate fuzzy input was selected to establish the corresponding fuzzy neural network prediction model, and a relatively ideal prediction result was obtained. The experimental results fully proved the great potential of fuzzy neural network in long-term power load forecasting.

Grounding Systems for Power Supply Facilities

The goal of this work is creation of optimal grounding model at the substation 10/0.4 kV of the urban power distribution network. The electric current can pose a major threat to the man’s life and health. In addition to pose a threat for health, the rise of the short circuit, as a consequence of insulation faults, poses a threat to retirement of electric systems and fire risks. The reliable grounding system design has significant implications for protection of human being as well as for electrical facility protection. The set objective was performed on the base of analytical and software-based methods. Analytical method gives a qualitative indication at each step in analysis. It also allows evaluating the values effect on the result, but the method is not susceptible of tolerable accuracy, that is why analytical method serves as initial approximation in differentiating. Specified estimation can be performed in such software package as MATLAB or ETAP. Software-based estimation is based on the finite element method (FEM), the main advantage of which is the ability to create different forms of grounding and allows obtaining distribution graphs of the step potential on the earth’s surface and touch potential. The calculation results in comparison of analytical and software-based methods taking into account the grounding optimization. There are conclusions on the most effective ground network.

On Optimal Cost Planning of Low Voltage Direct Current Power Distribution Networks

In this article, optimal planning problem of large-scale urban power distribution network, in the presence of low-voltage direct current (LVDC) distribution technology, is formulated. The problem is modeled as a minimization of cost function comprising construction and loss costs. Simulations are performed on an urban test-case; spatial load forecasting is adopted and imperialist competitive algorithm (ICA) is utilized to find the optimal solution. Results show that the smaller sizes (large numbers) of MV substation (distribution transformer and rectifier) give the optimal solution. MV substations have standard sizes up to 2500 kVA; the proposed planning approach opted substations of size up to 315 kVA—for a total cost function comprising costs of LV feeders and MV substations.

Hydrogen vector for using PV energy obtained at Esperanza Base, Antarctica

The use of solar photovoltaic (PV) is universally considered valuable for its renewable and clean nature; solar energy is especially important in regions far from urban centers and power distribution networks. It is known that the loss due to the latitude and the atmospheric layer is partially offset in very different annual distribution (i.e., by the long summer days) and in sparsely populated areas, because of the clearer atmosphere. Even with these assumptions, low temperatures (snow often combined with strong winds) and the effects of seasonality are difficult obstacles for the proper use of solar PV energy at high latitudes.In this work, both analytical and experimental data of the solar resource at Esperanza Base, Antarctica, are presented. The PV modules were installed in a vertical configuration and NW–NE orientation, which not only maximizes performance but also mitigates the adverse effects due to the latitude. In order to overcome the very asymmetric annual irradiance distribution, the use of a system of hydrogen production and accumulation, is proposed for effective energy storage.The results of two years of evaluation of PV potential at Esperanza Base show that duplicating the PV capture area in Esperanza allows to obtain the same total annual energy than the maximum acquired in Buenos Aires (PV module facing north with optimum tilt for solar capture).To effectively overcome discontinuity of solar energy and its sharp drop in four of the twelve months of the year an appropriate hydrogen vector system is proposed and analyzed.

Impact of Electric Vehicle Charging on Voltage Unbalance in an Urban Distribution Network

During the last few years, assessment and evaluation of power quality index due to large-scale penetration of electric vehicles in the system have gained significant attention. Voltage unbalance in the low voltage distribution network is amongst the main power quality issues caused by electric vehicles and therefore it has been quantified and analyzed in this paper. A CIGRE benchmark model of low voltage distribution network is taken as test network and simulations are performed on a sample urban power distribution network. An electric vehicle grid integration and its charging model is implemented in Simulink. Results for two charging strategies including uncontrolled charging and tariff based electric vehicle charging under different electric vehicle penetration levels and uneven charging scenarios have been obtained. The presented results show that an uneven EV charging scenario can cause significant voltage unbalance that goes beyond its allowed limit of 2 %.

Impact of Interdisciplinary Research on Planning, Running, and Managing Electromobility as a Smart Grid Extension

The smart grid is concerned with energy efficiency and with the environment, being a countermeasure against the territory devastations that may originate by the fossil fuel mining industry feeding the conventional power grids. This paper deals with the integration between the electromobility and the urban power distribution network in a smart grid framework, i.e., a multi-stakeholder and multi-Internet ecosystem (Internet of Information, Internet of Energy, and Internet of Things) with edge computing capabilities supported by cloud-level services and with clean mapping between the logical and physical entities involved and their stakeholders. In particular, this paper presents some of the results obtained by us in several European projects that refer to the development of a traffic and power network co-simulation tool for electro mobility planning, platforms for recharging services, and communication and service management architectures supporting interoperability and other qualities required for the implementation of the smart grid framework. For each contribution, this paper describes the inter-disciplinary characteristics of the proposed approaches.

A 6(10) kV Cable Section Reliability Assessment Model Including Power Distribution Network Configurations and Relay Protection Circuits

Urban power distribution network reliability depends on the resource of 6 (10) kV cables, which are its longest element. In the context of long-term operation of the distribution network, it is necessary to know when the cable network must be renewed to avoid damage, with due account of network configurations and regimes. The relevance of retrospective analysis and developong forecast methods is pointed out in the reliability concepts of the electricity industry. A number of statistical models are known. However, the reliability indicators of their operation in the distribution network must be assessed comprenehsively to improve the functioning of the existing cable network, taking into account their conditions, network configuration, and relay protection circuits. A model based on the Monte-Carlo method has developed in the LabVIEW software environment so as to estimate the probability of no-failure operation of an urban area cable section, and/or to identify renovations required to reduce the failure rate. The model permits testing different combinations of the failure rate parameters, thus producing “rich” statistical material. Cable line failure rates and urban distribution network configurations are obtained via retrospective analysis. The developed model can be applied to such cable networks.

Determining the Number and Sites for New Substations in Terms of Perspective Development of Urban Power Distribution Networks

Determining the Number and Sites for New Substations in Terms of Perspective Development of Urban Power Distribution Networks