scholarly journals Online Coordination of Plug-In Electric Vehicles Considering Grid Congestion and Smart Grid Power Quality

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2187 ◽  
Author(s):  
Sara Deilami
Keyword(s):  
Smart Grid ◽  
Power Quality ◽  
Electric Vehicles ◽  
Distribution System ◽  
Smart Grids ◽  
Low Voltage ◽  
Maximum Sensitivity ◽  
Power Losses ◽  
Nonlinear Load ◽  
Harmonic Power

This paper first introduces the impacts of battery charger and nonlinear load harmonics on smart grids considering random plug-in of electric vehicles (PEVs) without any coordination. Then, a new centralized nonlinear online maximum sensitivity selection-based charging algorithm (NOL-MSSCA) is proposed for coordinating PEVs that minimizes the costs associated with generation and losses considering network and bus total harmonic distortion (THD). The aim is to first attend the high priority customers and charge their vehicles as quickly as possible while postponing the service to medium and low priority consumers to the off-peak hours, considering network, battery and power quality constraints and harmonics. The vehicles were randomly plugged at different locations during a period of 24 h. The proposed PEV coordination is based on the maximum sensitivity selection (MSS), which is the sensitivity of losses (including fundamental and harmonic losses) with respect to the PEV location (PEV bus). The proposed algorithm uses the decoupled harmonic power flow (DHPF) to model the nonlinear loads (including the PEV chargers) as current harmonic sources and computes the harmonic power losses, harmonic voltages and THD of the smart grid. The MSS vectors are easily determined using the entries of the Jacobian matrix of the DHPF program, which includes the spectrums of all injected harmonics by nonlinear electric vehicle (EV) chargers and nonlinear industrial loads. The sensitivity of the objective function (fundamental and harmonic power losses) to the PEVs were then used to schedule PEVs accordingly. The algorithm successfully controls the network THDv level within the standard limit of 5% for low and moderate PEV penetrations by delaying PEV charging activities. For high PEV penetrations, the installation of passive power filters (PPFs) is suggested to reduce the THDv and manage to fully charge the PEVs. Detailed simulations considering random and coordinated charging were performed on the modified IEEE 23 kV distribution system with 22 low voltage residential networks populated with PEVs that have nonlinear battery chargers. Simulation results are provided without/with filters for different penetration levels of PEVs.

scholarly journals A Coordinated Charging Scheduling of Electric Vehicles Considering Optimal Charging Time for Network Power Loss Minimization

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5336
Author(s):  
Muhammad Usman ◽  
Wajahat Ullah Khan Tareen ◽  
Adil Amin ◽  
Haider Ali ◽  
Inam Bari ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Low Voltage ◽  
Combustion Engine ◽  
Cost Effective ◽  
Voltage Profile ◽  
Power Losses ◽  
Network Losses ◽  
Coordinated Charging ◽  
Network Power

Electric vehicles’ (EVs) technology is currently emerging as an alternative of traditional Internal Combustion Engine (ICE) vehicles. EVs have been treated as an efficient way for decreasing the production of harmful greenhouse gasses and saving the depleting natural oil reserve. The modern power system tends to be more sustainable with the support of electric vehicles (EVs). However, there have been serious concerns about the network’s safe and reliable operation due to the increasing penetration of EVs into the electric grid. Random or uncoordinated charging activities cause performance degradations and overloading of the network asset. This paper proposes an Optimal Charging Starting Time (OCST)-based coordinated charging algorithm for unplanned EVs’ arrival in a low voltage residential distribution network to minimize the network power losses. A time-of-use (ToU) tariff scheme is used to make the charging course more cost effective. The concept of OCST takes the departure time of EVs into account and schedules the overnight charging event in such a way that minimum network losses are obtained, and EV customers take more advantages of cost-effective tariff zones of ToU scheme. An optimal solution is obtained by employing Binary Evolutionary Programming (BEP). The proposed algorithm is tested on IEEE-31 bus distribution system connected to numerous low voltage residential feeders populated with different EVs’ penetration levels. The results obtained from the coordinated EV charging without OCST are compared with those employing the concept of OCST. The results verify that incorporation of OCST can significantly reduce network power losses, improve system voltage profile and can give more benefits to the EV customers by accommodating them into low-tariff zones.

The Italian Regulatory Framework for Developing Smart Distribution Grids

2012 ◽  
Vol 13 (5) ◽  
Author(s):  
Valeria Olivieri ◽  
Maurizio Delfanti ◽  
Luca Lo Schiavo
Keyword(s):  
Quality Of Service ◽  
Smart Grid ◽  
Distribution System ◽  
Smart Grids ◽  
Low Voltage ◽  
Selection Process ◽  
Renewable Energy Sources ◽  
Regulatory Framework ◽  
System Level

Abstract The integration of Dispersed Generation (DG) is by far the most important and challenging issue that modern power systems are facing nowadays, and is the only way of exploiting Renewable Energy Sources (RES) for electric production. This revolution is running particularly fast in Europe, where significant incentive schemes have been promoted by many Member States in order to match the targets decided by the European institutions. As a consequence of the important share of RES already connected (especially to low voltage and medium voltage networks), new technical challenges have to be faced both at a distribution network level and at a transmission system level. Some of these challenges are covered by Smart grids that represent a new framework for improved management of distribution and transmission networks with attention to interoperability, security, resilience problems, and quality of service (QoS). It is recognized that an intelligent use of Information and Communication Technology (ICT), as enabling technology, is the only approach able to solve new problems arising on energy networks due to larger DG penetration, without hindering system security and QoS.The paper focuses on the Italian case and in particular on the Italian regulatory framework for developing Smart Grids, and describes the technical foundations of the regulatory innovations introduced by the Italian energy regulatory authority (Autorità per l’energia elettrica e il gas - AEEG). After a selection process based on cost/benefit assessment, some demonstration projects for Smart Grid proposed by Distribution System Operators have been awarded with special capital cost remuneration (extra WACC of 2% for 12 years, on top of the ordinary WACC equal to 7% for distribution investments). The smart grid demonstration projects founded by AEEG introduce and test a new advanced management of DG in order to avoid the problems coming from reverse power flowing and maintain the necessary level of security, availability and quality of service.

Economic and environmental aspects of Smart Grid technologies implementation in Ukraine

2020 ◽  
pp. 28-37
Author(s):  
Oleksandra V. Kubatko ◽  
Diana O. Yaryomenko ◽  
Mykola O. Kharchenko ◽  
Ismail Y. A. Almashaqbeh
Keyword(s):  
Smart Grid ◽  
Environmental Sustainability ◽  
Distribution System ◽  
Energy Security ◽  
Smart Grids ◽  
Renewable Energy Sources ◽  
Average Energy ◽  
Time Of Day ◽  
Electricity Supply ◽  
Auxiliary Equipment

Interruptions in electricity supply may have a series of failures that can affect banking, telecommunications, traffic, and safety sectors. Due to the two-way interactive abilities, Smart Grid allows consumers to automatically redirect on failure, or shut down of the equipment. Smart Grid technologies are the costly ones; however, due to the mitigation of possible problems, they are economically sound. Smart grids can't operate without smart meters, which may easily transmit real-time power consumption data to energy data centers, helping the consumer to make effective decisions about how much energy to use and at what time of day. Smart Grid meters do allow the consumer to track and reduce energy consumption bills during peak hours and increase the corresponding consumption during minimum hours. At a higher level of management (e.g., on the level of separate region or country), the Smart Grid distribution system operators have the opportunity to increase the reliability of power supply primarily by detecting or preventing emergencies. Ukraine's energy system is currently outdated and cannot withstand current loads. High levels of wear of the main and auxiliary equipment of the power system and uneven load distribution in the network often lead to emergencies and power outages. The Smart Grid achievements and energy sustainability are also related to the energy trilemma, which consists of key core dimensions– Energy Security, Energy Equity, and Environmental Sustainability. To be competitive in the world energy market, the country has to organize efficiently the cooperation of public/private actors, governments, economic and social agents, environmental issues, and individual consumer behaviors. Ukraine gained 61 positions out of 128 countries in a list in 2019 on the energy trilemma index. In general, Ukraine has a higher than average energy security position and lower than average energy equity, and environmental sustainability positions. Given the fact that the number of renewable energy sources is measured in hundreds and thousands, network management is complicated and requires a Smart Grid rapid response. Keywords: economic development, Smart Grid, electricity supply, economic and environmental efficiency.

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

Electric vehicles and power quality in low voltage networks: Real data analysis and modeling

2022 ◽  
Vol 305 ◽  
pp. 117718
Author(s):  
S. Torres ◽  
I. Durán ◽  
A. Marulanda ◽  
A. Pavas ◽  
J. Quirós-Tortós
Keyword(s):  
Data Analysis ◽  
Power Quality ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Real Data ◽  
Real Data Analysis

scholarly journals A Methodology for Dependability Evaluation of Smart Grids

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1817 ◽  
Author(s):  
Gisliany Alves ◽  
Danielle Marques ◽  
Ivanovitch Silva ◽  
Luiz Affonso Guedes ◽  
Maria da Guia da Silva
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Information And Communication Technologies ◽  
Power Distribution ◽  
Smart Grids ◽  
Low Voltage ◽  
Hierarchical Topology ◽  
Automation Systems ◽  
Dependability Evaluation ◽  
Information And Communication

Smart grids are a new trend in electric power distribution, which has been guiding the digitization of electric ecosystems. These smart networks are continually being introduced in order to improve the dependability (reliability, availability) and efficiency of power grid systems. However, smart grids are often complex, composed of heterogeneous components (intelligent automation systems, Information and Communication Technologies (ICT) control systems, power systems, smart metering systems, and others). Additionally, they are organized under a hierarchical topology infrastructure demanded by priority-based services, resulting in a costly modeling and evaluation of their dependability requirements. This work explores smart grid modeling as a graph in order to propose a methodology for dependability evaluation. The methodology is based on Fault Tree formalism, where the top event is generated automatically and encompasses the hierarchical infrastructure, redundant features, load priorities, and failure and repair distribution rates of all components of a smart grid. The methodology is suitable to be applied in early design stages, making possible to evaluate instantaneous and average measurements of reliability and availability, as well as to identify eventual critical regions and components of smart grid. The study of a specific use-case of low-voltage distribution network is used for validation purposes.

scholarly journals An Insight into Practical Solutions for Electric Vehicle Charging in Smart Grid

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1545 ◽  
Author(s):  
Sara Deilami ◽  
S. M. Muyeen
Keyword(s):  
Smart Grid ◽  
Power System ◽  
Distribution System ◽  
Large Scale ◽  
Low Voltage ◽  
Co2 Reduction ◽  
Renewable Energy Resources ◽  
Smart Power ◽  
Electric Vehicle Charging ◽  
Ev Charging

The electrification of transportation has been developed to support energy efficiency and CO2 reduction. As a result, electric vehicles (EVs) have become more popular in the current transport system to create more efficient energy. In recent years, this increase in EVs as well as renewable energy resources (RERs) has led to a major issue for power system networks. This paper studies electrical vehicles (EVs) and their applications in the smart grid and provides practical solutions for EV charging strategies in a smart power system to overcome the issues associated with large-scale EV penetrations. The research first reviews the EV battery infrastructure and charging strategies and introduces the main impacts of uncontrolled charging on the power grid. Then, it provides a practical overview of the existing and future solutions to manage the large-scale integration of EVs into the network. The simulation results for two controlled strategies of maximum sensitivity selection (MSS) and genetic algorithm (GA) optimization are presented and reviewed. A comparative analysis was performed to prove the application and validity of the solution approaches. This also helps researchers with the application of the optimization approaches on EV charging strategies. These two algorithms were implemented on a modified IEEE 23 kV medium voltage distribution system with switched shunt capacitors (SSCs) and a low voltage residential network, including EVs and nonlinear EV battery chargers.

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