Concepts for an integration of quick charging stations in weak power grids

The paper presents problems related to the impact of electric vehicles connected to the power grid on energy parameters. Basic methods of control in power grids were discussed and results of the simulation were presented with regards to the power distribution, voltage drops and losses in the transmission lines. The simulation was conducted based on the example of CIGRE 11, to which electric vehicle charging stations were connected in several selected points, with the possibility of energy release into the grid. The obtained results were compared for the simulation conducted in two variants – without the connected electric vehicles and with them. The obtained results were analyzed and commented upon.

Download Full-text

Behavioural Change in Green Transportation: Micro-Economics Perspectives and Optimization Strategies

Energies ◽

10.3390/en14133728 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3728

Author(s):

Chiara Bordin ◽

Asgeir Tomasgard

Keyword(s):

Behavioural Change ◽

Power Grids ◽

Real World Data ◽

Load Curve ◽

Price Structure ◽

Indirect Control ◽

Price Signals ◽

Increasing Demand ◽

Charging Stations ◽

Ev Charging

The increasing demand for Electric Vehicle (EV) charging is putting pressure on the power grids and capacities of charging stations. This work focuses on how to use indirect control through price signals to level out the load curve in order to avoid the power consumption from exceeding these capacities. We propose mathematical programming models for the indirect control of EV charging that aim at finding an optimal set of price signals to be sent to the drivers based on price elasticities. The objective is to satisfy the demand for a given price structure, or minimize the curtailment of loads, when there is a shortage of capacity. The key contribution is the use of elasticity matrices through which it is possible to estimate the EV drivers’ reactions to the price signals. As real-world data on relating the elasticity values to the EV driver’s behaviour are currently non-existent, we concentrate on sensitivity analysis to test how different assumptions on elasticities affect the optimal price structure. In particular, we study how market segments of drivers with different elasticities may affect the ability of the operator to both handle a capacity problem and properly satisfy the charging needs.

Download Full-text

Integration of quick charging stations in weak power grids

2014 IEEE International Energy Conference (ENERGYCON) ◽

10.1109/energycon.2014.6850604 ◽

2014 ◽

Author(s):

Constantinos Sourkounis ◽

Nora Becker

Keyword(s):

Power Grids ◽

Charging Stations

Download Full-text

Performance of Gradient-Based Optimizer on Charging Station Placement Problem

Mathematics ◽

10.3390/math9212821 ◽

2021 ◽

Vol 9 (21) ◽

pp. 2821

Author(s):

Essam H. Houssein ◽

Sanchari Deb ◽

Diego Oliva ◽

Hegazy Rezk ◽

Hesham Alhumade ◽

...

Keyword(s):

Management Strategy ◽

Network Reliability ◽

Power Grids ◽

Placement Problem ◽

Local Optima ◽

Charging Station ◽

Optimum Placement ◽

Differential Evaluation ◽

Gradient Based ◽

Charging Stations

The electrification of transportation is necessary due to the expanded fuel cost and change in climate. The management of charging stations and their easy accessibility are the main concerns for receipting and accepting Electric Vehicles (EVs). The distribution network reliability, voltage stability and power loss are the main factors in designing the optimum placement and management strategy of a charging station. The planning of a charging stations is a complicated problem involving roads and power grids. The Gradient-based optimizer (GBO) used for solving the charger placement problem is tested in this work. A good balance between exploitation and exploration is achieved by the GBO. Furthermore, the likelihood of becoming stuck in premature convergence and local optima is rare in a GBO. Simulation results establish the efficacy and robustness of the GBO in solving the charger placement problem as compared to other metaheuristics such as a genetic algorithm, differential evaluation and practical swarm optimizer.

Download Full-text

Aggregated Electric Vehicle Fast-Charging Power Demand Analysis and Forecast Based on LSTM Neural Network

Sustainability ◽

10.3390/su132413783 ◽

2021 ◽

Vol 13 (24) ◽

pp. 13783

Author(s):

Munseok Chang ◽

Sungwoo Bae ◽

Gilhwan Cha ◽

Jaehyun Yoo

Keyword(s):

Neural Network ◽

Electric Vehicle ◽

Short Term Memory ◽

Power Grids ◽

Peak Time ◽

Learning Approaches ◽

Power Demand ◽

Proposed Model ◽

Fast Charging ◽

Charging Stations

With the widespread use of electric vehicles, their charging power demand has increased and become a significant burden on power grids. The uncoordinated deployment of electric vehicle charging stations and the uncertainty surrounding charging behaviors can cause harmful impacts on power grids. The charging power demand during the fast charging process especially is severely fluctuating, because its charging duration is short and the rated power of the fast chargers is high. This paper presents a methodology to analyze and forecast the aggregated charging power demand from multiple fast-charging stations. Then, pattern of fast-charging power demand is analyzed to identify its irregular trend with the distribution of peak time and values. The forecasting model, based on long short-term memory neural network, is proposed in this paper to address the fluctuating of fast-charging power demand. The forecasting performance of the proposed model is validated in comparison with other deep learning approaches, using real-world datasets measured from fast-charging stations in Jeju Island, South Korea. The results show that the proposed model outperforms forecasting fast-charging power demand aggregated by multiple charging stations.

Download Full-text

Combinatorial method for determining the optimum flow distribution plan for mining and municipal an electric vehicle and charging stations

Collection of Research Papers of the National Mining University ◽

10.33271/crpnmu/58.178 ◽

2019 ◽

Vol 58 ◽

pp. 178-191

Author(s):

V Kravets ◽

◽

K Ziborov ◽

K Bass ◽

V Krivda ◽

...

Keyword(s):

Electric Vehicle ◽

Flow Distribution ◽

Combinatorial Method ◽

Charging Stations ◽

Optimum Flow

Download Full-text

Legal Providing of Application of Energy Effective Lightning Technology and Intellectual Networks in the Conditions of Digital Economy

Light & Engineering ◽

10.33383/2018-089 ◽

2019 ◽

pp. 123-128 ◽

Cited By ~ 1

Author(s):

Maksim V. Demchenko ◽

Rostislav O. Ruchkin ◽

Eugenia P. Simaeva

Keyword(s):

Public Relations ◽

New Technologies ◽

Electric Power Industry ◽

Legal Regulation ◽

Power Grids ◽

Smart Power ◽

Smart Power Grids ◽

Russian Economy ◽

Intellectual Networks ◽

Efficient Power

The article substantiates the expediency of improving the legal support for the introduction and use of energy-efficient lighting equipment, as well as smart networks (Smart Grid), taking into account the ongoing digitalization of the Russian economy and electric power industry. The goal of scientific research is formulated, which is to develop practical recommendations on optimization of the public relations legal regulation in the digital power engineering sector. The research methodology is represented by the interaction of the legal and sociological aspects of the scientific methods system. The current regulatory and legal basis for the transformation of digital electricity relations has been determined. The need to modernize the system of the new technologies introduction legal regulation for generation, storage, transmission of energy, intelligent networks, including a riskbased management model, is established. A set of standardsetting measures was proposed to transform the legal regulation of public relations in the field of energyefficient lighting equipment with the aim of creating and effectively operating a single digital environment, both at the Federal and regional levels. A priority is set for the development of “smart” power grids and highly efficient power equipment in the constituent entities of the Russian Federation through a set of legal, economic (financial), edu cational measures.

Download Full-text